gstack/docs/skills.md

Skill Deep Dives

Detailed guides for every gstack skill — philosophy, workflow, and examples.

Skill	Your specialist	What they do
/office-hours	YC Office Hours	Start here. Six forcing questions that reframe your product before you write code. Pushes back on your framing, challenges premises, generates implementation alternatives. Design doc feeds into every downstream skill.
/spec	Spec Author	Turn vague intent into a precise, executable spec in five phases. Backlog-ready output that downstream skills can pick up. Optional agent spawn at the end.
/plan-ceo-review	CEO / Founder	Rethink the problem. Find the 10-star product hiding inside the request. Four modes: Expansion, Selective Expansion, Hold Scope, Reduction.
/plan-eng-review	Eng Manager	Lock in architecture, data flow, diagrams, edge cases, and tests. Forces hidden assumptions into the open.
/plan-design-review	Senior Designer	Interactive plan-mode design review. Rates each dimension 0-10, explains what a 10 looks like, fixes the plan. Works in plan mode.
/design-consultation	Design Partner	Build a complete design system from scratch. Knows the landscape, proposes creative risks, generates realistic product mockups. Design at the heart of all other phases.
/review	Staff Engineer	Find the bugs that pass CI but blow up in production. Auto-fixes the obvious ones. Flags completeness gaps. Advisory simplification lens flags over-built code — never blocks, never auto-applies.
/investigate	Debugger	Systematic root-cause debugging. Iron Law: no fixes without investigation. Traces data flow, tests hypotheses, stops after 3 failed fixes.
/design-review	Designer Who Codes	Live-site visual audit + fix loop. 80-item audit, then fixes what it finds. Atomic commits, before/after screenshots.
/design-shotgun	Design Explorer	Generate multiple AI design variants, open a comparison board in your browser, and iterate until you approve a direction. Taste memory biases toward your preferences.
/design-html	Design Engineer	Generates production-quality Pretext-native HTML. Works with approved mockups, CEO plans, design reviews, or from scratch. Text reflows on resize, heights adjust to content. Smart API routing per design type. Framework detection for React/Svelte/Vue. Previews render through your Aside browser.
/design-motion	Motion Designer	Turns an approved design into a showcase loop: rebuilds the exact frame, loads it from empty, one story per visual, then an MP4 for X, a website GIF and an 800×500 GIF after seam, rest and overflow checks.
/qa	QA Lead	Explore browser and functional behavior (APIs, CLIs, jobs, workers, webhooks), reproduce defects, prove regressions fail before repair, then fix and re-verify.
/qa-only	QA Reporter	Explore the same surfaces and propose regression cases with evidence, without changing product code or tests.
/scrape	Browser Data Extractor	Pull structured data off a web page — tables, lists, prices — in your Aside browser with the page's real logged-in state. Same driver contract as /browse. On the fallback browser, a codified browser-skill answers a repeat intent in ~200ms.
/skillify	Skill Codifier	Fallback-browser skill: walks back through your conversation, finds the last /scrape prototype, synthesizes script + test + fixture, runs the test, asks before committing. On Aside, durable per-site automation belongs to Aside's own skills.
/ship	Release Engineer	Sync main, run tests, explore changed behavior within a bound, audit coverage and docs before final verification, then push and open or update a PR. Bootstraps test frameworks when appropriate.
/land-and-deploy	Release Engineer	Merge the PR, wait for CI and deploy, verify production health. One command from "approved" to "verified in production."
/modernize	Stale-PR Maintainer	Bring an aging PR onto its current base and decide whether it should still exist: MODERNIZE, REWORK or CLOSE. Reads what moved under the PR for conflicts in meaning, proves the rebase with git range-diff, pushes with a lease pinned to the observed head, and never closes a PR on its own.
/canary	SRE	Post-deploy monitoring loop. Watches for console errors, performance regressions, and page failures in your Aside browser.
/benchmark	Performance Engineer	Baseline page load times, Core Web Vitals, and resource sizes. Compare before/after on every PR. Track trends over time.
/ubicloud	Remote Runner	Run a heavy suite, build or eval on an ephemeral 16-vCPU Ubicloud VM: TTL-named VMs with a reaper, quota preflight, a hang watchdog and one committed verify per repository.
/cso	Chief Security Officer	Supported security findings with explicit coverage. Static assessment remains available without catalog profiles; contained runtime/scanner execution requires matching qualified profiles. Runtime-tested bundles authenticate separate external assertions. Project-test completion remains self_reported because target code controls the test process; tested is reserved for a future target-independent completion witness.
/document-release	Technical Writer	Audit relevant docs on every ship before final verification; standalone runs can also update docs after a PR exists. Catches stale READMEs and reports unresolved gaps.
/document-generate	Technical Writer	Generate Diataxis docs (tutorial / how-to / reference / explanation) for a feature from code.
/retro	Eng Manager	Team-aware weekly retro. Per-person breakdowns, shipping streaks, test health trends, growth opportunities.
/browse	QA Engineer	Give the agent eyes. Drives your Aside browser first — real sessions, real clicks, real screenshots — through deterministic aside repl scripts, and falls back to gstack's own Chromium (~100ms per command) when Aside isn't there.
/setup-browser-cookies	Session Manager	Copy selected cookies from Chrome, Chromium, Brave, Edge, Windows-only Opera and Opera GX, or macOS-only Comet and Arc into the fallback browser. Choose your profile and domains; check sign-in separately. Unnecessary on Aside, which already has your sessions.
/autoplan	Review Pipeline	One command, fully reviewed plan. Runs CEO → design → DX → eng review automatically (eng always last, so the shipping gate reviews the final amended plan) with encoded decision principles. Surfaces only taste decisions for your approval.
/plan-devex-review	DX Reviewer	Plan-stage DX review. TTHW (time-to-hello-world), magical moments, friction points, persona traces, and error messages scored for the agents that read them (agent-ready errors). Three modes: Expansion, Polish, Triage.
/devex-review	DX Reviewer (live)	Live developer experience audit. Walks the actual onboarding flow, measures TTHW, catches the docs lies, and triggers CLI errors the way an agent meets them (no terminal, contained, redacted) through gstack-error-capture.
/plan-tune	Question Tuner	Self-tune AskUserQuestion sensitivity per question. Mark questions as never-ask, always-ask, or only-for-one-way.
/spec	Spec Author	Turn vague intent into a precise, executable spec in five phases. Files a GitHub issue, optionally spawns a Claude Code agent in a fresh worktree, and lets /ship close the source issue on merge.
/learn	Memory	Manage what gstack learned across sessions. Review, search, prune, and export project-specific patterns and preferences.
/context-save	Save State	Save working context (git state, decisions, remaining work) so any future session can resume.
/context-restore	Restore State	Resume from a saved context, even across Conductor workspace handoffs.
/health	Code Quality Dashboard	Wraps type checker, linter, tests, dead code detection. Computes a weighted 0-10 score; tracks trends over time.
/deslop-shared-libs	Shared Code Reviewer	Find worthwhile shared-code extractions in recent work. Recommendations only.
/write-skill	Skill Editor	Write or improve an agent skill without bloat: edit ladder, size per level, skill-to-bin drift check, full diets with a before/after test.
/test-audit	Test Auditor	Sweep existing tests for low-value, implementation-coupled or duplicate tests. Report-only unless you approve a batch.
/landing-report	Ship Queue Dashboard	Read-only snapshot of the workspace-aware ship queue. Which version slots are claimed, which sibling workspaces have WIP.
/captain	Crew Controller	Run many coding agents from one controller. Lanes build and send a READY block; the controller validates it, merges through trains (stamp on call, verify, merge with the expected head, verify again; train land per slot under changelog_fragments), keeps the digest, relays approvals in three fixed shapes and runs a daily flaky-fix pass. Also answers to /crew.
/benchmark-models	Model Benchmark	Side-by-side cross-model benchmark for skills (Claude vs GPT vs Gemini). Latency, tokens, cost, optional LLM-judged quality.
/eval-plan	Eval Planner	Preregister a paid eval (bars, arms, decoys, stop rules), dry-run it for $0 with the stub model, pilot three priced items, then approve the spend from the extrapolation table.
Multi-AI
/codex	Second Opinion	OpenAI Codex review, challenge, and consultation. Available outside the Codex harness.
/claude-code	Second Opinion	Claude Code review, challenge, and consultation. Available outside the Claude Code harness; used for automatic outside reviews in Codex.
/pair-agent	Remote Agent Bridge	Pair a remote AI agent (OpenClaw, Codex, Cursor, Hermes) with gstack's own browser. Scoped tunnel, locked allowlist, session token. Fallback-browser skill; agents driving Aside open their own tabs.
/setup-gbrain	Memory Sync	Set up gbrain for cross-machine session memory sync. One command from zero to live.
/sync-gbrain	Keep Brain Current	Refresh gbrain against this repo's code; teach the agent when to use gbrain search/code-def over Grep. Idempotent; safe to re-run.
Safety & Utility
/careful	Safety Guardrails	Warns before destructive commands (rm -rf, DROP TABLE, force-push, git reset --hard). Override any MEDIUM warning; root/home recursive deletes and default-branch force-pushes are hard-denied. Common build cleanups whitelisted.
/freeze	Edit Lock	Restrict all file edits to a single directory. Blocks Edit, Write and NotebookEdit outside the boundary. Accident prevention for debugging.
/guard	Full Safety	Combines /careful + /freeze in one command. Maximum safety for prod work.
/unfreeze	Unlock	Remove the /freeze boundary, allowing edits everywhere again.
/open-gstack-browser	GStack Browser	Launch gstack's own browser headed, with sidebar, anti-bot stealth, auto model routing, cookie import, and Claude Code integration. The visible face of the fallback engine; with Aside open you watch the agent's tabs there.
/setup-deploy	Deploy Configurator	One-time setup for /land-and-deploy. Detects your platform, production URL, and deploy commands.
/gstack-upgrade	Self-Updater	Upgrade gstack to the latest version. Detects global vs vendored install, syncs both, shows what changed.
/make-pdf	PDF Generator	Turn any markdown file into a publication-quality PDF. Proper margins, page numbers, cover pages, clickable TOC. Mermaid/excalidraw fences render as vector diagrams; --to html|docx for other formats. Prints through your Aside browser (macOS 15+), or gstack's bundled browser when Aside is absent.
/diagram	Diagram Maker	English in, diagram out: mermaid source + editable .excalidraw (open it on excalidraw.com, hand-drawn style) + rendered SVG/PNG. Fully offline, rendered through your Aside browser (macOS 15+) or gstack's bundled browser when Aside is absent.
/ios-qa	iOS QA Lead	Live-device iOS QA via USB CoreDevice tunnel + embedded StateServer. Reads Swift source, codegens accessors, drives the real iPhone or iPad. Optionally exposes the device over Tailscale for remote agents.
/ios-fix	iOS Autonomous Fixer	Closes the find→fix→verify loop on a real iPhone. Captures a reproducing snapshot, fixes the source, rebuilds, redeploys, verifies.
/ios-design-review	iOS Designer's Eye	10-dimension Apple HIG audit on a real iPhone. Rates each screen, says what would make it a 10.
/ios-clean	iOS Bridge Cleanup	Convenience wrapper to strip DebugBridge SPM + #if DEBUG wiring. The structural Release-build guard is in Package.swift + CI; this skill is for guided manual removals.
/ios-sync	iOS Bridge Resync	Regenerate accessors and Swift templates against the latest upstream gstack. Run when you add new @Observable classes or upgrade gstack.

---

/office-hours

This is where every project should start.

Before you plan, before you review, before you write code — sit down with a YC-style partner and think about what you're actually building. Not what you think you're building. What you're actually building.

The reframe

Here's what happened on a real project. The user said: "I want to build a daily briefing app for my calendar." Reasonable request. Then it asked about the pain — specific examples, not hypotheticals. They described an assistant missing things, calendar items across multiple Google accounts with stale info, prep docs that were AI slop, events with wrong locations that took forever to track down.

It came back with: "I'm going to push back on the framing, because I think you've outgrown it. You said 'daily briefing app for multi-Google-Calendar management.' But what you actually described is a personal chief of staff AI."

Then it extracted five capabilities the user didn't realize they were describing:

1. Watches your calendar across all accounts and detects stale info, missing locations, permission gaps
2. Generates real prep work — not logistics summaries, but the intellectual work of preparing for a board meeting, a podcast, a fundraiser
3. Manages your CRM — who are you meeting, what's the relationship, what do they want, what's the history
4. Prioritizes your time — flags when prep needs to start early, blocks time proactively, ranks events by importance
5. Trades money for leverage — actively looks for ways to delegate or automate

That reframe changed the entire project. They were about to build a calendar app. Now they're building something ten times more valuable — because the skill listened to their pain instead of their feature request.

Premise challenge

After the reframe, it presents premises for you to validate. Not "does this sound good?" — actual falsifiable claims about the product:

1. The calendar is the anchor data source, but the value is in the intelligence layer on top
2. The assistant doesn't get replaced — they get superpowered
3. The narrowest wedge is a daily briefing that actually works
4. CRM integration is a must-have, not a nice-to-have

You agree, disagree, or adjust. Every premise you accept becomes load-bearing in the design doc.

Implementation alternatives

Then it generates 2-3 concrete implementation approaches with honest effort estimates:

• Approach A: Daily Briefing First — narrowest wedge, ships tomorrow, M effort (human: ~3 weeks / CC: ~2 days)
• Approach B: CRM-First — build the relationship graph first, L effort (human: ~6 weeks / CC: ~4 days)
• Approach C: Full Vision — everything at once, XL effort (human: ~3 months / CC: ~1.5 weeks)

Recommends A because you learn from real usage. CRM data comes naturally in week two.

Two modes

Startup mode — for founders and intrapreneurs building a business. You get six forcing questions distilled from how YC partners evaluate products: demand reality, status quo, desperate specificity, narrowest wedge, observation & surprise, and future-fit. These questions are uncomfortable on purpose. If you can't name a specific human who needs your product, that's the most important thing to learn before writing any code.

Builder mode — for hackathons, side projects, open source, learning, and having fun. You get an enthusiastic collaborator who helps you find the coolest version of your idea. What would make someone say "whoa"? What's the fastest path to something you can share? The questions are generative, not interrogative.

The design doc

Both modes end with a design doc written to ~/.gstack/projects/ — and that doc feeds directly into /plan-ceo-review and /plan-eng-review. The full lifecycle is now: office-hours → plan → implement → review → QA → ship → retro.

After the design doc is approved, /office-hours reflects on what it noticed about how you think — not generic praise, but specific callbacks to things you said during the session. The observations appear in the design doc too, so you re-encounter them when you re-read later.

---

/plan-ceo-review

This is my founder mode.

This is where I want the model to think with taste, ambition, user empathy, and a long time horizon. I do not want it taking the request literally. I want it asking a more important question first:

What is this product actually for?

I think of this as Brian Chesky mode.

The point is not to implement the obvious ticket. The point is to rethink the problem from the user's point of view and find the version that feels inevitable, delightful, and maybe even a little magical.

Example

Say I am building a Craigslist-style listing app and I say:

"Let sellers upload a photo for their item."

A weak assistant will add a file picker and save an image.

That is not the real product.

In /plan-ceo-review, I want the model to ask whether "photo upload" is even the feature. Maybe the real feature is helping someone create a listing that actually sells.

If that is the real job, the whole plan changes.

Now the model should ask:

• Can we identify the product from the photo?
• Can we infer the SKU or model number?
• Can we search the web and draft the title and description automatically?
• Can we pull specs, category, and pricing comps?
• Can we suggest which photo will convert best as the hero image?
• Can we detect when the uploaded photo is ugly, dark, cluttered, or low-trust?
• Can we make the experience feel premium instead of like a dead form from 2007?

That is what /plan-ceo-review does for me.

It does not just ask, "how do I add this feature?" It asks, "what is the 10-star product hiding inside this request?"

Four modes

• SCOPE EXPANSION — dream big. The agent proposes the ambitious version. Every expansion is presented as an individual decision you opt into. Recommends enthusiastically.
• SELECTIVE EXPANSION — hold your current scope as the baseline, but see what else is possible. The agent surfaces opportunities one by one with neutral recommendations — you cherry-pick the ones worth doing.
• HOLD SCOPE — maximum rigor on the existing plan. No expansions surfaced.
• SCOPE REDUCTION — find the minimum viable version. Cut everything else.

Visions and decisions are persisted to ~/.gstack/projects/ so they survive beyond the conversation. Exceptional visions can be promoted to docs/designs/ in your repo for the team.

---

/plan-eng-review

This is my eng manager mode.

Once the product direction is right, I want a different kind of intelligence entirely. I do not want more sprawling ideation. I do not want more "wouldn't it be cool if." I want the model to become my best technical lead.

This mode should nail:

• architecture
• system boundaries
• data flow
• state transitions
• failure modes
• edge cases
• trust boundaries
• test coverage

And one surprisingly big unlock for me: diagrams.

LLMs get way more complete when you force them to draw the system. Sequence diagrams, state diagrams, component diagrams, data-flow diagrams, even test matrices. Diagrams force hidden assumptions into the open. They make hand-wavy planning much harder.

So /plan-eng-review is where I want the model to build the technical spine that can carry the product vision.

Example

Take the same listing app example.

Let's say /plan-ceo-review already did its job. We decided the real feature is not just photo upload. It is a smart listing flow that:

• uploads photos
• identifies the product
• enriches the listing from the web
• drafts a strong title and description
• suggests the best hero image

Now /plan-eng-review takes over.

Now I want the model to answer questions like:

• What is the architecture for upload, classification, enrichment, and draft generation?
• Which steps happen synchronously, and which go to background jobs?
• Where are the boundaries between app server, object storage, vision model, search/enrichment APIs, and the listing database?
• What happens if upload succeeds but enrichment fails?
• What happens if product identification is low-confidence?
• How do retries work?
• How do we prevent duplicate jobs?
• What gets persisted when, and what can be safely recomputed?

And this is where I want diagrams — architecture diagrams, state models, data-flow diagrams, test matrices. Diagrams force hidden assumptions into the open. They make hand-wavy planning much harder.

That is /plan-eng-review.

Not "make the idea smaller." Make the idea buildable.

One note on invocation: in plan mode, the skill skips the "what should I review?" scope question and reviews your active plan automatically, announcing its pick in one line ("Scope gate: plan mode — auto-selected B") so you can redirect it. Name a target explicitly ("review PLAN.md") and your choice wins in any mode. Outside plan mode with nothing named, it asks first — that gate is a hard stop.

Review Readiness Dashboard

Every review (CEO, Eng, Design) logs its result. At the end of each review, you see a dashboard:

+====================================================================+
|                    REVIEW READINESS DASHBOARD                       |
+====================================================================+
| Review          | Runs | Last Run            | Status    | Required |
|-----------------|------|---------------------|-----------|----------|
| Eng Review      |  1   | 2026-03-16 15:00    | CLEAR     | YES      |
| CEO Review      |  1   | 2026-03-16 14:30    | CLEAR     | no       |
| Design Review   |  0   | —                   | —         | no       |
+--------------------------------------------------------------------+
| VERDICT: CLEARED — Eng Review passed                                |
+====================================================================+

Eng Review is the only required gate (disable with gstack-config set skip_eng_review true). CEO and Design are informational — recommended for product and UI changes respectively.

Diff reviews use the review_freshness grade computed by gstack-review-read, shared by /ship and /land-and-deploy. CURRENT requires a clean, reviewer-reported completed and converged pass whose captured start and finish fingerprints match the current working-tree content. Tracked edits and non-ignored untracked source both count; an identical commit hash or zero commits since review is not a fallback.

A captured pass with different start/end content grades STALE, as does a previously verified pass whose fingerprint no longer matches. Missing or reused start receipts, legacy log-only records, incomplete or nonconverged passes, and unresolved findings cannot grade CURRENT; missing evidence grades UNVERIFIED. Ship telemetry is not a review pass. After fixes, run a genuine full re-review with a new start receipt rather than capturing one only to log the result. Completion remains reviewer-reported, not independent proof that a model read the source.

Plan-file reviews retain their existing seven-day freshness handling and optional plan-hash comparison; repository-content rules do not apply to them. A diff review must grade CURRENT before it can clear Eng Review, in addition to the dashboard's existing age and clean-status requirements.

Plan-to-QA flow

When /plan-eng-review finishes the test review section, it writes a test plan artifact to ~/.gstack/projects/. When you later run /qa, it picks up that test plan automatically — your engineering review feeds directly into QA testing with no manual copy-paste.

---

/plan-design-review

This is my senior designer reviewing your plan — before you write a single line of code.

Most plans describe what the backend does but never specify what the user actually sees. Empty states? Error states? Loading states? Mobile layout? AI slop risk? These decisions get deferred to "figure it out during implementation" — and then an engineer ships "No items found." as the empty state because nobody specified anything better.

/plan-design-review catches all of this during planning, when it's cheap to fix.

It works like /plan-ceo-review and /plan-eng-review — interactive, one issue at a time, with the STOP + AskUserQuestion pattern. It rates each design dimension 0-10, explains what a 10 looks like, then edits the plan to get there. The rating drives the work: rate low = lots of fixes, rate high = quick pass. Like /plan-eng-review, it skips the "what should I review?" scope question in plan mode and targets your active plan automatically (announced in one line so you can redirect); an explicitly named target wins in any mode.

Seven passes over the plan: information architecture, interaction state coverage, user journey, AI slop risk, design system alignment, responsive/accessibility, and unresolved design decisions. For each pass, it finds gaps and either fixes them directly (obvious ones) or asks you to make a design choice (genuine tradeoffs).

Example

You:   /plan-design-review

Claude: Initial Design Rating: 4/10

        "This plan describes a user dashboard but never specifies
         what the user sees first. It says 'cards with icons' —
         which looks like every SaaS template. It mentions zero
         loading states, zero empty states, and no mobile behavior."

        Pass 1 (Info Architecture): 3/10
        "A 10 would define primary/secondary/tertiary content
         hierarchy for every screen."
        → Added information hierarchy section to plan

        Pass 2 (Interaction States): 2/10
        "The plan has 4 UI features but specifies 0 out of 20
         interaction states (4 features × 5 states each)."
        → Added interaction state table to plan

        Pass 4 (AI Slop): 4/10
        "The plan says 'clean, modern UI with cards and icons'
         and 'hero section with gradient'. These are the top 2
         AI-generated-looking patterns."
        → Rewrote UI descriptions with specific, intentional alternatives

        Overall: 4/10 → 8/10 after fixes
        "Plan is design-complete. Run /design-review after
         implementation for visual QA."

When you re-run it, sections already at 8+ get a quick pass. Sections below 8 get full treatment. For live-site visual audits post-implementation, use /design-review.

---

/design-consultation

This is my design partner mode.

/plan-design-review audits a site that already exists. /design-consultation is for when you have nothing yet — no design system, no font choices, no color palette. You are starting from zero and you want a senior designer to sit down with you and build the whole visual identity together.

It is a conversation, not a form. The agent asks about your product, your users, and your audience. It thinks about what your product needs to communicate — trust, speed, craft, warmth, whatever fits — and works backward from that to concrete choices. Then it proposes a complete, coherent design system: aesthetic direction, typography (3+ fonts with specific roles), color palette with hex values, spacing scale, layout approach, and motion strategy. Every recommendation comes with a rationale. Every choice reinforces every other choice.

But coherence is table stakes. Every dev tool dashboard looks the same — clean sans-serif, muted grays, a blue accent. They are all coherent. They are all forgettable. The difference between a product that looks "nice" and one that people actually recognize is the deliberate creative risks: the unexpected serif for headings, the bold accent nobody else in your category uses, the tighter spacing that makes your data feel authoritative instead of airy.

That is what /design-consultation is really about. It does not just propose a safe system. It proposes safe choices AND risks — and tells you which is which. "Here are the choices that keep you literate in your category. And here is where I think you should break from convention, and why." You pick which risks to take. The agent checks that the whole system still coheres either way.

If you want, the agent will research what's already out there in your space — take screenshots of real sites, analyze their fonts and colors and spacing — so you can see the landscape before you make choices. This is not about copying. It is about getting in the ballpark so you know what the conventions are, and then deciding which ones are worth breaking.

After you agree on the system, it generates an interactive HTML preview page — not just swatches and font samples, but realistic product pages. If you are building a dashboard, you see a dashboard with a sidebar, data tables, and stat cards. If you are building a marketing site, you see a hero section with real copy and a CTA. Everything rendered in your design system, with your product name, in light and dark mode. You see what your product could feel like before a single line of production code is written.

Then it writes DESIGN.md to your repo root — your project's design source of truth — and updates CLAUDE.md so every future Claude Code session respects the system. From that point on, /design-review can audit against it, and any agent working on your frontend knows the rules.

The file is written in the open DESIGN.md format (google-labs-code/design.md): every token in YAML front matter (colors, typography, rounded, spacing, components), the rationale in the spec's canonical sections, so impeccable, Google Stitch, and anything else that reads the format share one file. If you already have a legacy gstack DESIGN.md, the skill offers a conversion once (a backup is kept) and records your answer in the file so it never asks again. A PRODUCT.md in the repo root prefills the product questions instead of re-asking them.

Example

You:   /design-consultation

Claude: From the README, this looks like a developer analytics dashboard
        for engineering teams. Sound right? Tell me about the feeling
        you want — and would you like me to look at what's out there
        first so we can see the landscape?

You:    Yes, it's for eng managers. Show me what's out there.

Claude: [browses Linear, Vercel, Datadog, Posthog — takes screenshots]

        Here's the landscape. They all converge on clean sans-serifs
        and muted blue-gray palettes. Linear stands out with dark-first
        and tight spacing. The rest feel interchangeable.

        Here's my proposal — and where I'd play it safe vs. take risks:

        AESTHETIC: Industrial/Utilitarian — data-first, every pixel earns its place
        TYPOGRAPHY: Geist (body + UI), Instrument Serif (display), JetBrains Mono (data)
        COLOR: Restrained — slate neutrals, single teal accent (#0D9488)
        SPACING: 4px base, compact density
        LAYOUT: Grid-disciplined, 12-column
        MOTION: Minimal-functional — only transitions that aid comprehension

        SAFE CHOICES (match category expectations):
          Geist for body — your users already know this font from Vercel
          Slate neutrals — warm grays feel right for data-heavy UIs
          Grid-disciplined layout — dashboards need predictable alignment

        RISKS (where you'd stand out):
          Instrument Serif for display headings — nobody in dev tools
            uses a serif. It creates instant hierarchy contrast and
            signals "we care about craft" in a space full of sans-serifs.
          Single teal accent instead of blue — everyone else in this space uses blue.
            Teal is close enough to feel trustworthy, different enough
            to be recognizable.
          4px compact density — tighter than Linear, says "we respect
            your screen real estate."

        The safe choices keep you literate. The risks are where your
        product gets its own face. Which risks appeal to you?

You:    Love the serif risk. Let's see it.

Claude: Preview opened in your browser.
        [/tmp/design-consultation-preview-1710000000.html]

        The page shows a realistic dashboard: sidebar nav, header with
        avatar, stat cards, data table — all in your design system.
        Instrument Serif at hero scale, Geist in body text, JetBrains
        Mono in the data table. Teal accent on buttons and active states.
        Light and dark mode toggle in the corner.

        How does it feel? Want to adjust anything before I write DESIGN.md?

You:    Ship it.

Claude: Wrote DESIGN.md (typography, color, spacing, layout, motion).
        Updated CLAUDE.md with design system guidelines.
        All future sessions will respect these choices.

---

/design-review

This is my designer who codes mode.

/plan-design-review reviews your plan before implementation. /design-review audits and fixes the live site after.

It runs an 80-item visual audit on your live site — in your Aside browser, so it sees exactly what a logged-in you sees — then enters a fix loop: for each design finding, it locates the source file, makes the minimal CSS/styling change, commits with style(design): FINDING-NNN, re-navigates to verify, and takes before/after screenshots. One commit per fix, fully bisectable.

The self-regulation heuristic is tuned for design work — CSS-only changes get a free pass (they are inherently safe and reversible), but changes to component JSX/TSX files count against the risk budget. Hard cap at 30 fixes. If the risk score exceeds 20%, it stops and asks.

Design detector. When you have impeccable installed, its engine runs first: on a URL the page's rendered DOM is dumped (linked styles inlined) and scanned; on a feature branch with no URL the changed frontend files are scanned (.dart files excepted: they count as frontend scope, but the engine reads web sources). Every mechanical finding arrives as a FINDING-NNN tagged with its rule id ([nested-cards], [low-contrast]), and the report closes with Detector: N → M. gstack never runs impeccable's installer; when no engine is present it offers, once, to download the engine binary (checksum-pinned, logged in the egress ledger) and remembers the answer; without it the audit is unchanged. gstack-config set design_detector off disables the pre-pass.

Example

You:   /design-review https://myapp.com

Claude: [Runs full 80-item visual audit on the live site]
        Design Score: C  |  AI Slop Score: D
        12 findings (4 high, 5 medium, 3 polish)

        Fixing 9 design issues...

        style(design): FINDING-001 — replace 3-column icon grid with asymmetric layout
        style(design): FINDING-002 — add heading scale 48/32/24/18/16
        style(design): FINDING-003 — remove gradient hero, use bold typography
        style(design): FINDING-004 — add second font for headings
        style(design): FINDING-005 — vary border-radius by element role
        style(design): FINDING-006 — left-align body text, reserve center for headings
        style(design): FINDING-007 — add hover/focus states to all interactive elements
        style(design): FINDING-008 — add prefers-reduced-motion media query
        style(design): FINDING-009 — set max content width to 680px for body text

        Final audit:
        Design Score: C → B+  |  AI Slop Score: D → A
        9 fixes applied (8 verified, 1 best-effort). 3 deferred.

        [Report with before/after screenshots saved to ~/.gstack/projects/<slug>/designs/design-audit-<date>/]

Nine commits, each touching one concern. The AI Slop score went from D to A because the three most recognizable patterns (gradient hero, 3-column grid, uniform radius) are gone.

---

/design-shotgun

This is my design exploration mode.

You know the feeling. You have a feature, a page, a landing screen... and you're not sure what it should look like. You could describe it to Claude and get one answer. But one answer means one perspective, and design is a taste game. You need to see options.

/design-shotgun generates 3 visual design variants using the GPT Image API, opens a comparison board in your browser, and waits for your feedback. You pick a direction, request changes, or ask for entirely new variants. The board supports remix, regenerate, and approval actions.

The loop

1. You describe what you want (or point at an existing page)
2. The skill reads your DESIGN.md for brand constraints (if it exists)
3. It generates 3 distinct design variants as PNGs
4. A comparison board opens in your browser with all 3 side-by-side
5. You click "Approve" on the one you like, or give feedback for another round
6. The approved variant saves to ~/.gstack/projects/$SLUG/designs/ with an approved.json; for a landing, pricing or campaign screen, it also records the page archetype you picked (classic-hero, long-form-story, minimal-conversion or comparison) and its section outline

That approved.json is one way to feed /design-html. The design pipeline chains: shotgun picks the direction, design-html renders it as working code. But /design-html also works with CEO plans, design reviews, or just a description.

Taste memory

The skill remembers your preferences across sessions. If you consistently prefer minimal designs over busy ones, it biases future generations. This isn't a setting you configure... it emerges from your approvals.

Example

You:   /design-shotgun — hero section for a developer tools landing page

Claude: [Generates 3 variants]
        Variant A: Bold typography, dark background, code snippet hero
        Variant B: Split layout, product screenshot left, copy right
        Variant C: Minimal, centered headline, gradient accent

        [Opens comparison board at localhost:PORT]

You:    [Clicks "Approve" on Variant A in the browser]

Claude: Approved Variant A. Saved to ~/.gstack/projects/myapp/designs/
        Next: run /design-html to generate production HTML from this mockup.

---

/design-html

This is my design-to-code mode.

Every AI code generation tool produces static CSS. Hardcoded heights. Text that overflows on resize. Breakpoints that snap instead of flowing. The output looks right at exactly one viewport size and breaks at every other.

/design-html fixes this. It generates HTML using Pretext by Cheng Lou (ex-React core, Midjourney frontend). Pretext is a 15KB library that computes text layout without DOM measurement. Text reflows. Heights adjust to content. Cards size themselves. Chat bubbles shrinkwrap. All sub-millisecond, all dynamic.

It works with multiple input sources: an approved mockup from /design-shotgun, a CEO plan from /plan-ceo-review, design review context from /plan-design-review, a PNG you provide, or just a description of what you want. It detects what context exists and asks how you want to proceed.

Smart API routing

Not every page needs the full Pretext engine. The skill reads the design and picks the right tools:

• Simple layouts (landing, marketing): prepare() + layout() for resize-aware heights
• Card grids (dashboard, listing): prepare() + layout() for self-sizing cards
• Chat UIs: walkLineRanges() for tight-fit bubbles with zero wasted pixels
• Editorial layouts: layoutNextLine() for text flowing around obstacles
• Complex editorial: Full engine with layoutWithLines() for manual line rendering

The refinement loop

1. Reads the approved mockup from approved.json, plus any page archetype and section outline you picked on the board, which it builds as given instead of asking again
2. Uses GPT-4o vision to extract implementation spec (colors, typography, layout)
3. Generates self-contained HTML with Pretext inlined (15KB, zero network dependency)
4. Spins up a live-reload server so you see changes instantly
5. Screenshots at 3 viewports (mobile, tablet, desktop) to verify layout
6. AskUserQuestion: what needs to change?
7. Surgical edits via the Edit tool (not full regeneration)
8. Repeat until you say "done"

Slop gate. If you have impeccable installed, the finalized page gets one scan through its engine before the verification screenshots: findings trigger a single surgical fix pass over the non-advisory rules, then one more scan. Whatever remains is presented as accepted-with-reason (the approved mockup contains it, DESIGN.md blesses it, or you agreed to an inline impeccable-disable comment). One pass, never a loop; without impeccable the step is skipped silently. The skill's never-include list carries the same rule ids the detector reports, from lib/design-catalog.ts.

Framework detection

If your project uses React, Svelte, or Vue (detected from package.json), the skill offers to generate a framework component instead of vanilla HTML. Framework output uses npm install @chenglou/pretext instead of inline vendoring.

Example

You:   /design-html

Claude: Found approved mockup: variant-A.png (hero section)
        Design type: simple layout → using prepare() + layout()

        [Generates HTML with Pretext, opens live-reload server]
        [Screenshots at 375px, 768px, 1440px — all verified]

        The HTML is live at localhost:3456. Resize your browser.
        Text reflows dynamically. What needs to change?

You:    Make the headline bigger and add more spacing below the CTA

Claude: [Edits font-size and margin, browser auto-reloads]
        Updated. Two changes applied.

You:    Done

Claude: Saved to ~/.gstack/projects/myapp/designs/hero-20260330/finalized.html

---

/design-motion

This is my showcase mode.

A launch post on X wants the product moving, not a static mockup. Screen-recording a page in real time gives you dropped frames, a loop that jumps at the seam, and a card that drifts out of its container halfway through.

/design-motion takes an approved mockup from /design-shotgun, a finalized.html from /design-html, or a URL. It rebuilds the exact frame as one self-contained page, starts it from an empty state, loads it in with a soft rise-and-resolve, and gives each visual one story: a chart gets read, a list receives a new item, a prompt retypes itself. Then it dissolves and repeats.

Nothing is recorded in real time. bin/gstack-motion-capture.ts drives the page on Playwright's fake clock in whole-millisecond steps that average 1000/60, so frame N is always the same pixels. bin/gstack-motion-encode check then proves the loop with ffmpeg's PSNR: the first frame equals the frame one cycle later (seam), the empty beat equals the frame before the start (no JS state left over), the last frame before the dissolve equals the still design (every story came home), and nothing moves outside the containers (overflow). Only then does export write an MP4 for X, a 960 px website GIF and an 800×500 GIF.

On a website it follows gstack's design rules instead: one authored motion moment per page, content visible without script, and no pulsing dots or marquees left running. ffmpeg is optional; without it the skill builds the page and tells you how to install it. A Figma source works when a FIGMA_TOKEN is set.

Adapted from Elaya's design-to-motion (MIT, © 2026 Elaya).

Example

You:   /design-motion

Claude: Found approved mockup: variant-B.png (analytics bento, 1440×990)
        Context: showcase. Layout: separate cards (4).
        Stories: chart scrubber, a new lead lands on the stack, KPI counts up.
        Cycle: 12 s.

        [Rebuilds the frame, still matches the mockup at 37 dB]
        [Captures 744 frames on a fake clock]

        MOTION_CHECK: seam pass
        MOTION_CHECK: empty-beat pass
        MOTION_CHECK: rest pass
        MOTION_CHECK: overflow pass

        bento-x.mp4 (1744×1200, 60 fps, 12 s), bento-loop.gif, bento-800x500.gif

---

/review

This is my paranoid staff engineer mode.

Passing tests do not mean the branch is safe.

/review exists because there is a whole class of bugs that can survive CI and still punch you in the face in production. This mode is not about dreaming bigger. It is not about making the plan prettier. It is about asking:

What can still break?

This is a structural audit, not a style nitpick pass. I want the model to look for things like:

• N+1 queries
• stale reads
• race conditions
• bad trust boundaries
• missing indexes
• escaping bugs
• broken invariants
• bad retry logic
• tests that pass while missing the real failure mode
• forgotten enum handlers — add a new status or type constant, and /review traces it through every switch statement and allowlist in your codebase, not just the files you changed

Fix-First

Findings get action, not just listed. Obvious mechanical fixes (dead code, stale comments, N+1 queries) are applied automatically — you see [AUTO-FIXED] file:line Problem → what was done for each one. Genuinely ambiguous issues (security, race conditions, design decisions) get surfaced for your call.

Completeness gaps

/review now flags shortcut implementations where the complete version costs less than 30 minutes of CC time. If you chose the 80% solution and the 100% solution is a lake, not an ocean, the review will call it out.

One exception: a shortcut you took deliberately and logged. A gstack-shortcut(dec-<id>) marker whose decision id resolves in the decision ledger downgrades the finding to acknowledged debt. An orphan marker — one with no ledger entry behind it — doesn't suppress anything; the gap is reported normally and the marker itself gets flagged.

Design pass. When the diff touches frontend files, the Design specialist reads review/design-checklist.md, which is generated from lib/design-catalog.ts, so /review, /ship, and /design-review flag the same patterns under the same rule ids. If you have impeccable installed, its engine scans the changed frontend files first (.dart files get the checklist pass only): its rows bucket by tier (auto-fix, ask, possible), a detector hit and a checklist hit at the same file:line collapse into one row, and your repo's .impeccable/config*.json ignores are read as settled decisions. Without it, the checklist pass runs alone.

Example

Suppose the smart listing flow is implemented and the tests are green.

/review should still ask:

• Did I introduce an N+1 query when rendering listing photos or draft suggestions?
• Am I trusting client-provided file metadata instead of validating the actual file?
• Can two tabs race and overwrite cover-photo selection or item details?
• Do failed uploads leave orphaned files in storage forever?
• Can the "exactly one hero image" rule break under concurrency?
• If enrichment APIs partially fail, do I degrade gracefully or save garbage?
• Did I accidentally create a prompt injection or trust-boundary problem by pulling web data into draft generation?

That is the point of /review.

I do not want flattery here. I want the model imagining the production incident before it happens.

---

/investigate

When something is broken and you don't know why, /investigate is your systematic debugger. It follows the Iron Law: no fixes without root cause investigation first.

Instead of guessing and patching, it traces data flow, matches against known bug patterns, and tests hypotheses one at a time. If three fix attempts fail, it stops and questions the architecture instead of thrashing. This prevents the "let me try one more thing" spiral that wastes hours.

---

/qa

This is my QA lead mode.

/browse gives the agent eyes. /qa gives it a testing methodology.

The most common use case: you're on a feature branch, you just finished coding, and you want to verify everything works. Just say /qa — it uses your request, repository contracts, test plan and diff to select browser, functional (API, CLI, job, worker or webhook), or mixed surfaces. No URL or manual test plan is required. Browser targets still open affected pages in Aside tabs (or gstack's fallback browser); functional-only targets use documented native commands and isolated local fixtures without starting a browser.

Choose Full, Quick or Regression depth; diff-aware selects what to test:

• Diff-aware (automatic on feature branches) — selects changed and adjacent behavior. Standalone /qa first resolves a dirty working tree through its commit/stash/abort question; it tests the resulting checkout. For browser targets it identifies affected pages and tests them specifically.
• Full — browser QA systematically explores the entire app (typically 5-15 minutes, documenting 5-10 well-evidenced issues); functional QA covers applicable documented contracts and reports blocked or untested ones separately.
• Quick (--quick) — browser QA keeps its 30-second homepage + top-five-navigation smoke; functional QA checks a successful operation and the highest-risk changed edge, marking other contracts not run.
• Regression (--regression <previous-report-or-baseline>) — browser QA runs full mode and diffs against a previous baseline.json; functional QA requires a readable prior functional report and replay evidence, repeats its failed probes against the intended contract, then checks changed adjacent behavior. A browser-only baseline is not a functional baseline.

Exploration retains a written trail: before each next discovery probe, QA saves an exploration-NNN.json checkpoint in its owned report directory with the previous command and result, the hypothesis and the next exact command. The final report links those files. /qa-only and the bounded review/ship pass use the same evidence contract without gaining permission to edit product code or tests.

Time limits include checkpoint and evidence work; unfinished probes remain untested. New runs preserve prior reports and baselines, using a fresh owned run directory when the selected output directory already contains artifacts. Mixed runs put browser and functional results in separate sections of one report; browser scores never apply to functional coverage. Conflicting Quick/Regression requests are resolved before probing.

Automatic regression tests

For a reproduced defect, /qa writes a native regression test when infrastructure is available and proves it fails for that defect before the repair; CSS-only defects may use browser evidence instead. After the root-cause repair, it requires the original probe, adjacent happy path and native regression when available to pass before calling the fix verified. Tests trace back to the QA report. /qa-only can propose the case and retain replayable evidence but never changes product code or tests; missing native test infrastructure remains an explicit coverage limit, not permission to install a new framework for functional QA.

Example

You:   /qa https://staging.myapp.com

Claude: [Explores 12 pages, fills 3 forms, tests 2 flows]

        QA Report: staging.myapp.com — Health Score: 72/100

        Top 3 Issues:
        1. CRITICAL: Checkout form submits with empty required fields
        2. HIGH: Mobile nav menu doesn't close after selecting an item
        3. MEDIUM: Dashboard chart overlaps sidebar below 1024px

        [Full report with screenshots saved to .gstack/qa-reports/]

Testing authenticated pages: with Aside, nothing to set up. Aside is your browser, so /qa already has your sessions; if it hits a sign-in wall, sign in inside Aside and tell it you're done — it re-runs the step. It never types a password for you. On the fallback browser, run /setup-browser-cookies first to import your real sessions, or log in once in headed mode.

---

/ship

This is my release machine mode.

Once I have decided what to build, nailed the technical plan, and run a serious review, I do not want more talking. I want execution.

/ship is for the final mile. It is for a ready branch, not for deciding what to build.

This is where the model should stop behaving like a brainstorm partner and start behaving like a disciplined release engineer: sync with main, run the right tests, make sure the branch state is sane, update changelog or versioning if the repo expects it, push, and create or update the PR.

Test bootstrap

If your project doesn't have a test framework, /ship sets one up — detects your runtime, researches the best framework, installs it, writes 3-5 real tests for your actual code, sets up CI/CD (GitHub Actions), and creates TESTING.md. 100% test coverage is the goal — tests make vibe coding safe instead of yolo coding.

Coverage audit

Every /ship run builds a code path map from your diff, searches for corresponding tests, and produces an ASCII coverage diagram with quality stars. Gaps get tests auto-generated. Your PR body shows the coverage: Tests: 42 → 47 (+5 new).

/review and /ship also run a bounded exploratory pass on changed behavior and nearby risks, even for a small diff without a plan or web server. Their existing approval and test rules govern any fixes or permanent tests; a blocked probe remains a coverage gap, not a passing QA result.

Review gate

/ship displays historical review readiness in the Review Readiness Dashboard during preflight. A missing Eng Review is reported without an extra question; it does not replace or waive the current pre-landing review. Step 9 still runs the checklist, one batched specialist (Testing and Security, plus the checklists scope selects) and bounded exploratory QA, with its existing approval and completion gates.

A lot of branches die when the interesting work is done and only the boring release work is left. Humans procrastinate that part. AI should not.

The PR body

/ship writes the PR body from the diff, the receipt and the review, and a reader who was not in the session decides the merge from it. On Capy (CAPY_PR: on) the body opens with four sections, in this order, before the standard Summary, Test plan and Documentation sections:

1. ## What changed: one to three captioned before/after images from gstack-pr-shots or a UI screenshot, highest-signal first, with a collapsed text version under each.
2. ## Why: two or three sentences. The first states the problem in the person's words (the issue, the message, the failing run), then the cause and the user-visible effect.
3. ## Blast radius: what else the change touches and the one fact that makes that safe, with the evidence-ladder rung that fact reached (a test that exercises the shared path, a grep over every caller, a measured run). A change to a shared helper, a generated file, a selection list or a policy default always has one; a leaf fix says so in one line.
4. ## Approvals: the table from gstack-approvals render, verbatim.

Before the body is composed, gstack-prose-lint reads the Why, Summary and Blast radius drafts (--sections 'Why,Summary,Blast radius' --gate) and the CHANGELOG entry (--base origin/<base> --gate), and a PROSE_LINT_FOUND line names the sentence to rewrite; the rest of the body is advisory. The Captain's merge-ask template (captain/templates/merge-ask.md) carries the same four sections, so a READY report and its PR say the same thing.

Versions: where /ship looks, and when it ships without one

/ship bumps a version only when the project says where the version lives. It checks, in order:

1. --version-path <path> passed to gstack-version-bump / gstack-next-version.
2. .gstack/version-path: a committed one-line file holding the version file's repo-relative path, for example package.json or apps/web/package.json. A .json path is read and written as its "version" field; 3-digit semver stays 3-digit.
3. A root VERSION file (gstack's own 4-digit MAJOR.MINOR.PATCH.MICRO format).

A root package.json on its own does not count, because many apps carry a placeholder there. To have /ship version it, run echo package.json > .gstack/version-path and commit the file.

When none of these exist, /ship ships without a version change: no bump, no CHANGELOG version header, no v1.2.3 title prefix, no tag. It prints:

Shipped without a version change: no version source is configured (no VERSION file, no .gstack/version-path). To version releases, create VERSION or write the version file's path (for example package.json) to .gstack/version-path.

It does the same, with the reason, when release-please, Changesets or semantic-release is configured, when the repo is a workspace monorepo, or when package.json holds a placeholder such as 0.0.0-development; those tools own the version. /land-and-deploy and /document-release read the same signal. A configured version file that is missing, empty, unreadable or malformed stops /ship with the file's path and the problem; gstack never substitutes 0.0.0.0.

Third-party web actions (v1.72.0.0+)

Sometimes the release work leaves the terminal: registering an API key, creating a vendor account, wiring a webhook or OAuth app. Instead of handing you a manual step list, /ship (and /spec, /office-hours, /land-and-deploy, /setup-deploy) offers to drive the browser for you. Aside first — it acts across your real logged-in sessions, which is exactly what vendor dashboards need. No Aside? gstack's own visible browser (headed $B with handoff for sign-in) is the fallback on every platform, with one pointer to aside.com (macOS 15+) per task.

The consent rules are strict and pin-tested: one explicit question per task naming the exact site and actions, no standing permission, no auto-install ever (on a Mac without Aside you get one download pointer — aside.com, macOS 15+ — once per task). Passwords, payment, CAPTCHAs, and identity verification stay yours; Apple credential creation is never a drive target in any skill. A captured secret never appears in chat — it lands in an owner-only file and gets verified with one read-only API call before gstack claims success.

---

/land-and-deploy

This is my deploy pipeline mode.

/ship creates the PR. /land-and-deploy finishes the job: merge, deploy, verify.

It confirms PR readiness and your merge approval, merges, then monitors CI and deployment before checking production. If deployment breaks, it reports what failed and whether rollback is available. If the new revision's deployment cannot be confirmed, it reports that uncertainty rather than treating a healthy old page as proof.

The first run, or a changed deployment configuration, triggers a dry-run walk-through so you can verify the pipeline before anything irreversible happens. An unchanged, previously confirmed configuration skips that walkthrough, not readiness checks or merge approval. Approval is bound to the exact PR head and destination branch; changing either requires fresh readiness and approval.

Setup

Run /setup-deploy first. It detects your platform (Fly.io, Render, Vercel, Netlify, Heroku, GitHub Actions, or custom), discovers your production URL and health check endpoints, and writes the config to CLAUDE.md. One-time, 60 seconds.

Example

You:   /land-and-deploy

Claude: Merging PR #42...
        CI: 3/3 checks passed
        Deploy: Fly.io — deploying v2.1.0...
        Health check: https://myapp.fly.dev/health → 200 OK
        Canary: 5 pages checked, 0 console errors, p95 < 800ms

        Production verified. v2.1.0 is live.

---

/modernize

/ship merges the base into a branch you are working on. /modernize is for the other case: a pull request that has sat for weeks, often someone else's, where the real question is not "does it rebase" but "should it still exist".

You: /modernize 2187

Claude: Claim: #2187 caches the skill census so `bun run skill:check` stops
        re-reading 57 directories. It relies on the census being read once per run.

        Moved under it: 41 base commits since the merge base; 3 touch its files.
        Conceptual: a2f9c01 (v1.91.240.0) made the census a shared helper that
        already memoizes per process. The cache the PR adds would be a second one.

        Verdict: CLOSE. The base solves the problem another way (a2f9c01). Nothing
        was pushed and the PR stays open; say "close it" and I will post the reason
        and the superseding commit, with thanks to its author.

Three verdicts, one chosen before anything is pushed. MODERNIZE: the claim still holds, so the branch is rebased with the author's commits kept as theirs, git range-diff proves no intent was lost (every changed hunk gets a one-line reason), the repository's own tests run, and the push is --force-with-lease=<branch>:<sha observed before the rebase>, so a push someone else made meanwhile is refused rather than overwritten. REWORK: the problem is real but this diff is no longer the way to solve it; the skill says what the new change would be and pushes nothing. CLOSE: the problem is gone, solved another way, or decided against; the skill recommends closing with the superseding commit and leaves the PR open until someone with the authority says otherwise. A clean git rebase is not evidence the PR is current, and the age of a PR is not evidence either way.

/canary

This is my post-deploy monitoring mode.

After deploy, /canary watches the live site for trouble. It loops through your key pages in your Aside browser (one aside repl script per page, so every cycle is a fresh load), checking for console errors, performance regressions, page failures, and visual anomalies. Takes periodic screenshots and compares against pre-deploy baselines.

Use it right after /land-and-deploy, or schedule it to run periodically after a risky deploy.

You:   /canary https://myapp.com

Claude: Monitoring 8 pages every 2 minutes...

        Cycle 1: ✓ All pages healthy. p95: 340ms. 0 console errors.
        Cycle 2: ✓ All pages healthy. p95: 380ms. 0 console errors.
        Cycle 3: ⚠ /dashboard — new console error: "TypeError: Cannot read
                   property 'map' of undefined" at dashboard.js:142
                 Screenshot saved.

        Alert: 1 new console error after 3 monitoring cycles.

---

/deslop-shared-libs

Find shared code worth extracting from recent work. By default, the skill reviews the preceding 14 UTC days of commits and PRs, plus relevant current-branch work. It checks existing helpers, verifies compatible authored callers, and compares up to five new opportunities before recommending up to three. Estimates include tests and integration, so moving code into a new file does not count as savings. Fewer recommendations, including none, are valid.

You: /deslop-shared-libs
You: /deslop-shared-libs — focus on the API and workers over the past 30 days

The report links the reviewed source, names the smallest useful helper and its callers, explains reliability gains and shared-failure risks, and separates work already covered by PRs. It checks older open PRs for candidate overlap within a bounded scan and discloses inaccessible history or incomplete coverage. It reads raw uncommitted source without running project hooks or filters. It never edits code, runs project tests, saves a report, or creates issues or PRs.

/plan-eng-review applies the same criteria to the plan and proposed callers. /review checks the diff and related callers even on tiny changes. These scoped checks do not run the history audit. Optional extractions are advisory and require approval; they do not block a clean review or reduce its score. Actual defects keep their normal fix handling.

/write-skill

Every skill is read in full each time it runs, so every extra line costs tokens on every run, and a skill that names a command the tool no longer has produces wrong calls that pass CI. /write-skill keeps skills lean and correct, for gstack's own templates and for any skill folder you own.

• Find the skill. gstack-skill-bill <name|folder> resolves exact names only and says what you are holding: a folder you own, a gstack checkout template (edit SKILL.md.tmpl, then bun run gen:skill-docs), or an installed gstack skill, which it never edits because gstack-upgrade overwrites it.
• Edit ladder. Stop at the first step that handles the change: fix the tool (a clearer error, a flag, a test); add nothing a fresh session already does; edit the line that covers the idea instead of appending; put the fact on the lowest level that reaches the agent in time (description, SKILL.md, references/, the tool's --help, the tool's errors); write the rule and put the story in the commit message.
• Size. gstack-skill-bill prints bytes and estimated tokens per level, and in a gstack checkout the skill's eval task file (EVAL TASKS:). Commits carry Skill-Size: <before>→<after> bytes; a skill more than 10% over its last Skill-Diet: commit is DUE, and a red context-budget ratchet means diet, not a higher ceiling.
• Drift. test/skill-bin-drift.test.ts fails when a template or rendered skill calls a gstack bin or flag that does not exist (bun run scripts/skill-bin-drift.ts --skill <name> for one skill). Its allowlist only shrinks.
• Full diet. Report first, write the eval tasks before any cut (test/fixtures/skill-evals/<skill>/tasks.json), lock them (gstack-evals skill-eval --lock, then commit tasks.lock.json; the shared eval refuses a paid run without it), cut, then prove before vs after vs no skill with the shared skill eval (docs/designs/SKILL_EVAL_CONTRACT.md). A diet ships only when no task that passed before fails after.

/write-skill is not /skillify: /skillify codifies a browser scrape into a browser-skill. Adapted from nicobailon/skill-diet (MIT). The first diet, /learn, cut its template from 5,797 to 2,955 bytes.

/test-audit

Find existing tests that cost more than they protect. /review, /ship, /qa and /plan-eng-review apply the same test value bar to tests in a diff; /test-audit sweeps the tests that already exist.

You: /test-audit
You: /test-audit test/ --max-candidates 5
You: /test-audit --since origin/main

A mechanical pre-filter shortlists assertion-free probes, source greps, export-list copies and near-duplicate files before any model reading. Each candidate gets a retirement card (what it detects, non-test callers with the search command, the stronger remaining proof, history, what retiring it unlocks, and the validation command). Contract tests such as SKILL.md goldens and prompt-byte checks (machine-read tokens, not English sentences; see the value bar) are retained. The report and a JSON sidecar land in ~/.gstack/projects/<slug>/. Nothing is edited unless you approve a batch; spawned sessions stay report-only. Tests marked gstack:test-value keep reason="..." are skipped and listed in the report's appendix.

/eval-plan

Preregister a paid eval before the first priced call.

You: /eval-plan
You: /eval-plan how much will the retrieval eval cost before I run it?

bin/gstack-eval-plan prereg --init writes the preregistration (question, bars, arms, decoys, stop rules, cap) and --check refuses to continue while a field is blank (PREREG_INCOMPLETE). arms resolves the eval-arms model role against lib/pricing.ts and stops on an unpriced model (EVAL_PRICE_MISSING); dry-run runs every row through the stub model for $0 and flags malformed rows (EVAL_DRY_RUN_FAILED); pilot start|settle|release|report runs three priced items, records actual spend, extrapolates to the full set against the cap (EVAL_BUDGET_EXHAUSTED) and prints the spend table the approval question shows. The skill's closing section lists the tier-3 items (instrument audit, steady state, sealed paths, off-machine persistence, memory preflight, power tables, QA soak) as tier 3, after P7; none of them run yet.

/benchmark

This is my performance engineer mode.

/benchmark establishes performance baselines for your pages: load time, Core Web Vitals (LCP, CLS, INP), resource counts, and total transfer size. Run it before and after a PR to catch regressions.

It measures in your Aside browser — the page's own performance navigation and resource entries from a real load, not synthetic estimates. Each page runs five times and is reported as the median with its range (--quick is a single-run ballpark). Results persist so you can track trends across PRs.

You:   /benchmark https://myapp.com

Claude: Benchmarking 5 pages (5 runs each)...

        /           load: 1.2s  LCP: 0.9s  CLS: 0.01  resources: 24 (890KB)
        /dashboard  load: 2.1s  LCP: 1.8s  CLS: 0.03  resources: 31 (1.4MB)
        /settings   load: 0.8s  LCP: 0.6s  CLS: 0.00  resources: 18 (420KB)

        Baseline saved. Run again after changes to compare.

---

/ubicloud

This is my Remote Runner.

A suite that takes an hour on a 4-core sandbox takes minutes on a standard-16 VM. /ubicloud runs it there through one entry point, bin/gstack-ubi (scripts/ubicloud/ubi-runner.sh), with the discipline a shared quota needs: every VM is named ubirun-<owner>-<epoch>-<suffix>-t<hours>, so its owner (UBI_OWNER, required to create one) and TTL (UBI_TTL_HOURS, default 3) are visible to everyone; every up first reaps VMs whose TTL ended, whichever owner made them, and its own owner's VMs with no TTL once they are 4 hours old; every run ends with UBICLOUD: left=0 or fails; the quota preflight refuses before the create request when the project's running VMs plus the new size exceed the known ceiling (UBI_QUOTA_VCPUS, or the maximum the last refusal printed; UBI_QUOTA_WAIT waits for room instead); a watchdog kills a remote command silent for UBI_IDLE_TIMEOUT seconds (1800) with exit 124 and its last 40 lines, and prints a heartbeat every UBI_HEARTBEAT seconds; and gstack-ubi verify runs the repository's committed .gstack/ubicloud.json (setup, command, size, env, pass, pull) instead of a wrapper per lane, with the file confined to the checkout: setup and pull paths resolve inside --src, and a pass name is forwarded only when the command line grants it (--pass NAME or --trust-config), never UBICLOUD_*. The skill insists on a watched launch (a background operation that is waited on, or gstack-detach), because the runner destroys its VM on every exit path only while it is alive.

You:   /ubicloud run the full verify

Claude: UBICLOUD_API_KEY: set; UBI_OWNER=lane7
        gstack-ubi verify  (.gstack/ubicloud.json: bootstrap.sh, "bash scripts/verify.sh", standard-16)
        ubi-runner: reap: no expired VMs
        ubi-runner: creating eu-central-h1/ubirun-lane7-1761500000-9f3a2c10-t3 (standard-16)
        ubi-runner: ubirun-lane7-1761500000-9f3a2c10-t3 carries a 3h TTL (any later run of this script reaps it); if this process dies first: gstack-ubi down ubirun-lane7-1761500000-9f3a2c10-t3
        ubi-runner: heartbeat: command 300s elapsed, last output 2s ago
        ubi-runner: command exited 0 after 1140s
        ubi-runner: destroyed eu-central-h1/ubirun-lane7-1761500000-9f3a2c10-t3
        UBICLOUD: left=0 owner=lane7 vm=ubirun-lane7-1761500000-9f3a2c10-t3 others=0

---

/cso

This is my Chief Security Officer.

Run /cso for a bounded static investigation with an application model, challenged findings, and explicit coverage; static assessment remains available when no runtime or scanner catalog profile is qualified. With matching qualified profiles, /cso --comprehensive can prepare Node/Bun, Python, and Rails applications in contained local runtimes, reproduce a defect, and retain a reviewable repair candidate without changing the working branch. An out-of-process witness can authenticate the external boot, legitimate-control, and security assertions and issue a runtime_tested bundle. Project-test completion remains self_reported because target code shares that process and can forge reporter output or terminate the runner; recorded command, count, exit, and output hashes are diagnostic evidence, not a target-independent completion witness. Every report shows assertion, test-completion, and review assurance separately. The tested state is reserved for a future target-independent witness and is not emitted today. /cso --doctor, --resume, --replay, and --recheck diagnose prerequisites, recover interrupted work, repeat recorded verification, and establish current-source closure from fresh evidence.

You:   /cso

Claude: complete — assessed application routes, tenant authorization, secrets,
        dependency exposure, and deployment configuration.

        HIGH: Cross-tenant invoice access (app/controllers/invoices.rb:47)
        Confidence: high — caller, middleware, and policy checks traced
        Evidence: supported static finding; runtime not requested

        1 supported finding. Run ID: cso-…

---

/document-release

This is my technical writer mode.

On every /ship run, including reruns and existing-PR updates, a ship-owned /document-release audit checks relevant authored docs against committed and selected uncommitted changes before the final commit, verification and publication. Clear factual corrections join the checked change; the ship parent owns versioning, Git and PR publication. A blocked or incomplete audit requires recovery or explicit acceptance of the named documentation risk before shipping, and never silently becomes current. You can still invoke /document-release standalone after a PR exists; that workflow retains its own approval, commit and PR-body steps.

You:   /document-release

Claude: Analyzing 21 files changed across 3 commits. Found 8 documentation files.

        README.md: updated skill count from 9 to 10, added new skill to table
        CLAUDE.md: added new directory to project structure
        CONTRIBUTING.md: current — no changes needed
        TODOS.md: marked 2 items complete, added 1 new item

        All docs updated and committed. PR body updated with doc diff.

It also polishes CHANGELOG voice (without ever overwriting entries), cleans up completed TODOS, checks cross-doc consistency, and asks about VERSION bumps only when appropriate.

---

/retro

This is my engineering manager mode.

At the end of the week I want to know what actually happened. Not vibes — data. /retro analyzes commit history, work patterns, and shipping velocity and writes a candid retrospective.

It is team-aware. It identifies who is running the command, gives you the deepest treatment on your own work, then breaks down every contributor with specific praise and growth opportunities. It computes metrics like commits, LOC, test ratio, PR sizes, and fix ratio. It detects coding sessions from commit timestamps, finds hotspot files, tracks shipping streaks, and identifies the biggest ship of the week.

It also tracks test health: total test files, tests added this period, regression test commits, and trend deltas. If test ratio drops below 20%, it flags it as a growth area.

Example

You:   /retro

Claude: Week of Mar 1: 47 commits (3 contributors), 3.2k LOC, 38% tests, 12 PRs, peak: 10pm | Streak: 47d

        ## Your Week
        32 commits, +2.4k LOC, 41% tests. Peak hours: 9-11pm.
        Biggest ship: one browser contract for every browser skill (Aside).
        What you did well: shipped a complete feature with encryption, UI, and
        18 unit tests in one focused push...

        ## Team Breakdown

        ### Alice
        12 commits focused on app/services/. Every PR under 200 LOC — disciplined.
        Opportunity: test ratio at 12% — worth investing before payment gets more complex.

        ### Bob
        3 commits — fixed the N+1 query on dashboard. Small but high-impact.
        Opportunity: only 1 active day this week — check if blocked on anything.

        [Top 3 team wins, 3 things to improve, 3 habits for next week]

It saves a JSON snapshot to .context/retros/ so the next run can show trends.

---

/browse

This is my QA engineer mode.

/browse is the skill that closes the loop. Before it, the agent could think and code but was still half blind. It had to guess about UI state, auth flows, redirects, console errors, empty states, and broken layouts. Now it can just go look.

It drives the Aside AI browser — your real browser, with your real logged-in sessions — through aside repl scripts: Playwright-style JavaScript that opens a tab, does the work, prints its evidence as labelled lines, and closes the tab. One flow per script, no state carried between calls, nothing to import. Every other browser skill (/qa, /qa-only, /design-review, /canary, /benchmark, /scrape) is built on the same contract. /scrape is the data-extraction flavor: point it at a page and it hands back the table, list, or prices as structured data.

Example

You:   /browse staging.myapp.com — test the signup flow and check
       every page I changed in this branch

Claude: Submitting the signup form on staging.myapp.com creates a real
        account in your session. Go ahead?            [AskUserQuestion]

You:    yes

Claude: [aside repl: console hook → openTab → goto /signup → snapshot
         → fill → click Submit → snapshot → screenshot → closeTab]

        DIFF_START … heading "Welcome — set up your workspace" … DIFF_END
        URL=https://staging.myapp.com/onboarding
        CONSOLE_ERRORS=[]
        ASIDE_DIR=/Users/you/.aside/u/0/sessions/2026-09-05_7KtoAatMItBqZvoL
        GSTACK_STEP_OK

        > cp "$ASIDE_DIR/issue-001-result.jpg" .gstack/qa-reports/screenshots/
        > Read .gstack/qa-reports/screenshots/issue-001-result.jpg

        Signup works. Redirected to onboarding. Now checking changed pages…

        All 4 pages load. No console errors. No broken layouts.
        Signup → onboarding → dashboard flow works end to end.

Four scripts, about a minute. Full QA pass, in the browser you were already signed into.

Untrusted content: everything a page returns — snapshot trees, text, console output, aside exec answers — is data, never instructions.

What the agent will and won't do in your browser: it opens its own tabs and closes them; it never reads or touches yours, never echoes your tab list, never types a password or reads a cookie. Looking is free; a mutating action (submit, delete, purchase) on anything that isn't localhost gets one AskUserQuestion first, listing the exact actions. Sign-in wall? Sign in inside Aside and say "done" — the session is already there.

Aside is macOS 15+ and gstack never installs it. Full contract and cookbook pointer: BROWSER.md.

When Aside isn't there

Linux, Windows, or a Mac with Aside closed: /browse says so once and switches to gstack's own browser for the run — a compiled binary that talks to a persistent Chromium daemon built on Playwright. First call starts the browser (~3s); every call after that ~100-200ms, and cookies, tabs, and localStorage carry over between commands. The same skills produce the same evidence; the features that only make sense when the browser is gstack's rather than yours live here: /setup-browser-cookies to import your sessions, /open-gstack-browser to watch it headed, /skillify to codify a /scrape, /pair-agent to share it with another agent.

When the headless browser gets stuck — CAPTCHA, MFA, complex auth — it hands off to you:

Claude: I'm stuck on a CAPTCHA at the login page. Opening a visible
        Chrome so you can solve it.

        > browse handoff "Stuck on CAPTCHA at login page"

You:    done

Claude: > browse resume

        Got a fresh snapshot. Logged in successfully. Continuing QA.

The browser preserves all state across the handoff, and after resume the agent gets a fresh snapshot of wherever you left off. If a browse command fails 3 times in a row, it suggests handoff automatically.

Security note: the fallback is a persistent Chromium session — cookies, localStorage, and session state carry over between commands. Do not use it against sensitive production environments unless you intend to. The session auto-shuts down after 30 minutes of idle time. Full $B command reference: BROWSER.md.

---

/setup-browser-cookies

This is my session manager mode — for the fallback browser. With Aside open, /qa and /browse already run in your real sessions and this skill has nothing to do.

For authenticated testing on gstack's own browser, /setup-browser-cookies copies selected cookies from your daily browser. Sites may also need storage or a fresh login, so copying cookies is not proof that the session works.

The picker detects Chrome, Chromium, Brave, Edge, Windows-only Opera and Opera GX, and macOS-only Comet and Arc. Choose the browser, account/profile, and domains. Profile labels use the current Local State name with a directory discriminator, so renamed profiles and duplicate names are distinguishable. No cookie values are displayed; source/profile labels are still sensitive.

You:   /setup-browser-cookies

Claude: Cookie picker opened. Select your browser, profile, and domains,
        then tell me when you're done.

        [You choose a browser/profile and pick github.com, myapp.com]

You:    done

Claude: Imported 2 domains (47 cookies). Sign-in has not been checked.

For direct import, select the browser and profile first and navigate to a matching target. Do not infer an account from the CLI's legacy Comet default:

You:   /setup-browser-cookies github.com from Chrome, Profile 2

Claude: Imported 12 cookies; sign-in has not been checked.

--verify-auth is explicit and requires a selector and expected identity configured privately in the daemon environment before startup. It checks one exact visible identity on the captured target, not just HTTP 200 or a cookie count. Missing configuration fails before mutation. --clear-storage is separate, opt-in recovery for Chromium targets: it clears only the captured origin's localStorage (shared across that origin's tabs) and the target tab's sessionStorage in an isolated world with a native deadline. Other target engines retain import/auth checks but reject reset. It is never automatic and cannot be combined with --all. Partial imports and unsuccessful checks remain visible rather than becoming a false "ready."

macOS may prompt for Keychain approval; Linux uses its supported keyring/fallback paths; Windows can import DPAPI-compatible cookies, but native App-Bound Encryption extraction remains disabled pending qualification. Closing Chrome does not bypass Chrome 136+ default-directory protection. Use manual sign-in in the headed fallback browser when needed and a display is available, never a TCP downgrade or real-profile copy. Full flags, configuration, and privacy guidance: cookie import reference.

---

/make-pdf

Turn any markdown file into a publication-quality PDF: proper margins, page numbers, cover page, clickable TOC, mermaid and excalidraw fences rendered as vector diagrams, --to html|docx when you need another format. The compiled pdf binary does the typesetting; the printing happens in a browser — your Aside browser first. make-pdf serves the finished HTML from your machine on loopback, opens it in a tab Aside closes when it is done, prints through the browser's own PDF engine (tagged PDF, document outline, header and footer templates all intact), and copies the file out. Nothing leaves the box. When Aside is absent (Linux, Windows, or the app closed) the same pipeline prints through gstack's bundled browser instead, so a PDF comes out on every platform. Full guide to fences and formats: howto-diagrams-and-formats.md.

---

/diagram

English in, diagram out. Describe the diagram (or paste mermaid source) and you get a triplet: the mermaid source, an editable .excalidraw file you can open on excalidraw.com in hand-drawn style, and rendered SVG + PNG. The mermaid and excalidraw runtimes are vendored in lib/diagram-render/ and rendered by bin/gstack-render.ts, the same one-script render make-pdf uses — through your Aside browser when it is open, through gstack's bundled browser otherwise — so it is fully offline on every platform.

---

/autoplan

This is my review autopilot mode.

Running /plan-ceo-review, then /plan-design-review, then /plan-eng-review individually means answering 15-30 intermediate questions. Each question is valuable, but sometimes you want the gauntlet to run without stopping for every decision.

/autoplan reads the review skills from disk and runs them sequentially: CEO → Design (if UI scope) → DX (if developer-facing scope) → Eng, always last — the required shipping gate reviews the final amended plan, not a stale one. It makes decisions automatically: each question resolves to its recommended option by default, with six encoded principles (prefer completeness, match existing patterns, choose reversible options, prefer the option the user chose for similar past decisions, defer ambiguous items, and escalate security) breaking ties and deciding questions that carry no recommendation. Taste decisions (close approaches, borderline scope expansions, cross-model disagreements) get saved and presented at a final approval gate.

One command, fully reviewed plan out.

You:   /autoplan

Claude: Running CEO review... [4 scope decisions auto-resolved]
        Running design review... [3 design dimensions auto-scored]
        Running eng review... [2 architecture decisions auto-resolved]

        TASTE DECISIONS (need your input):
        1. Scope: Codex suggested adding search — borderline expansion. Add?
        2. Design: Two approaches scored within 1 point. Which feels right?

        [Shows both options with context]

You:    1) Yes, add search. 2) Option A.

Claude: Plan complete. 9 decisions auto-resolved, 2 taste decisions approved.

---

/learn

This is my institutional memory mode.

gstack learns from every session. Patterns, pitfalls, preferences, architectural decisions... they accumulate in ~/.gstack/projects/$SLUG/learnings.jsonl. Each learning has a confidence score, source attribution, and the files it references.

/learn lets you see what gstack has absorbed, search for specific patterns, prune stale entries (when referenced files no longer exist), and export learnings for team sharing. The real magic is in other skills... they automatically search learnings before making recommendations, and display "Prior learning applied" when a past insight is relevant.

You:   /learn

Claude: 23 learnings for this project (14 high confidence, 6 medium, 3 low)

        Top patterns:
        - [9/10] API responses always wrapped in { data, error } envelope
        - [8/10] Tests use factory helpers in test/support/factories.ts
        - [8/10] All DB queries go through repository pattern, never direct

        3 potentially stale (referenced files deleted):
        - "auth middleware uses JWT" — auth/middleware.ts was deleted
        [Remove, keep, or update each one?]

---

/open-gstack-browser

This is my co-presence mode — for the fallback browser. With Aside open, you already watch the agent's tabs in Aside; this skill is how you watch it when the browser is gstack's own.

Without Aside, /browse runs headless by default. You don't see what the agent sees. /open-gstack-browser changes that. It launches GStack Browser (rebranded Chromium with anti-bot stealth) controlled by Playwright, with the sidebar extension auto-loaded. You watch every action in real time.

The sidebar chat is a Claude instance that controls the browser. It auto-routes to the right model: Sonnet for navigation and actions (click, goto, fill, screenshot), Opus for reading and analysis (summarize, find bugs, describe). One-click cookie import from the sidebar footer. The browser stays alive as long as the window is open... no idle timeout in headed mode. The menu bar says "GStack Browser" instead of "Chrome for Testing."

The sidebar agent ships a layered prompt injection defense: a local 22MB ML classifier scans every page and tool output, a Haiku transcript check votes on the full conversation, a canary token catches session-exfil attempts, and a verdict combiner requires two classifiers to agree before blocking. A shield icon in the header shows status (green/amber/red). Details in ARCHITECTURE.md.

You:   /open-gstack-browser

Claude: Launched GStack Browser with sidebar extension.
        Anti-bot stealth active. All $B commands run in headed mode.
        Type in the sidebar to direct the browser agent.
        Sidebar model routing: sonnet for actions, opus for analysis.

---

/setup-deploy

One-time deploy configuration. Run this before your first /land-and-deploy.

It auto-detects your deploy platform (Fly.io, Render, Vercel, Netlify, Heroku, GitHub Actions, or custom), discovers your production URL, health check endpoints, and deploy status commands. Writes everything to CLAUDE.md so all future deploys are automatic.

You:   /setup-deploy

Claude: Detected: Fly.io (fly.toml found)
        Production URL: https://myapp.fly.dev
        Health check: /health → expects 200
        Deploy command: fly deploy
        Status command: fly status

        Written to CLAUDE.md. Run /land-and-deploy when ready.

If you answer "Nothing is deployed yet", /setup-deploy stops and writes nothing, because there is no production deploy to record. How to bring up your first production deploy covers that first step; run /setup-deploy again once the app is live.

---

/codex

This is my second opinion mode.

/codex brings OpenAI Codex CLI to review the same diff independently. It is available on every harness except Codex itself. External harnesses install it as /gstack-codex. Compare its findings with the native review to distinguish corroborated findings from issues only one reviewer caught.

Without a role, gstack-owned Codex calls select a request-specific model, then GSTACK_CODEX_MODEL, then Codex native settings, falling back to gpt-6-astra. This also applies to resumed consultations. Generated commands pass the selection through -c model=..., overriding the CLI's configured model for that call. Native review also sets -c review_model=... to that selection, overriding any separate review-model pin.

On Codex hosts, the Claude outside-voice skill is gstack-claude-code. Its review, challenge, and consult calls preserve Claude's configured model. GSTACK_CLAUDE_MODEL=<model> supplies an explicit override, including resumed sessions; a model named in your request takes precedence. Harness routing is independent of model selection.

An explicit --role plan-review uses the configured plan-review tier instead; request and environment overrides still win, and host mode restores native selection. See model policy for pins, precedence and recovery.

Three modes

Review — run codex review against the current diff. Codex reads every changed file, classifies findings by severity (P1 critical, P2 high, P3 medium), and returns a PASS/FAIL verdict. Any P1 finding = FAIL. The review is fully independent — Codex doesn't see Claude's review.

A severity-gate PASS is separate from review freshness: unresolved recorded findings (findings > findings_fixed, with missing findings_fixed treated as zero) prevent CURRENT even when the gate passes. This does not change the severity gate. Fixes still require a new completed, unchanged review pass before the fixed tree can grade CURRENT.

Challenge — adversarial mode. Codex actively tries to break your code. It looks for edge cases, race conditions, security holes, and assumptions that would fail under load. Think of it as a penetration test for your logic.

Reasoning effort — Review and Challenge run at high, Consult at medium. gstack-config set codex_effort <level> changes that for every run; --effort <level> right after /codex or its mode word, among the leading flags (-m, --model, --role), changes it for one (/codex review --effort medium for a faster, cheaper review). --xhigh is shorthand for --effort xhigh. An unknown level stops before Codex runs. See model policy for levels and precedence.

Consult — open conversation with session continuity. Ask Codex anything about the codebase. Follow-up questions reuse the same session, so context carries over. Great for "am I thinking about this correctly?" moments.

Cross-model analysis

When both /review (Claude) and /codex (OpenAI) have reviewed the same branch, you get a cross-model comparison: which findings overlap (high confidence), which are unique to Codex (different perspective), and which are unique to Claude. This is the "two doctors, same patient" approach to code review.

You:   /codex review

Claude: Running independent Codex review...

        CODEX REVIEW: PASS (3 findings)
        [P2] Race condition in payment handler — concurrent charges
             can double-debit without advisory lock
        [P3] Missing null check on user.email before downcase
        [P3] Token comparison not using constant-time compare

        Cross-model analysis (vs /review):
        OVERLAP: Race condition in payment handler (both caught it)
        UNIQUE TO CODEX: Token comparison timing attack
        UNIQUE TO CLAUDE: N+1 query in listing photos

---

/claude-code

Claude Code provides the outside reviewer when gstack runs in Codex. Other non-Claude harnesses also expose this skill for explicit requests; Claude Code itself omits it. External harnesses install it as /gstack-claude-code.

Review supplies the branch diff for a read-only pass/fail review. Challenge asks Claude Code to find concrete failure cases in the same diff. Consult supports read-only repository exploration and resumes the session saved in .context/claude-session-id. Review and challenge receive context from the parent workflow and run without tools; consultation can read and search files.

The Claude Code CLI must be installed and authenticated. Without a role, its existing model configuration is honored; explicit --role plan-review follows the model policy. GSTACK_CLAUDE_BIN / GSTACK_CLAUDE_BIN_ARGS executable overrides remain in force. Errors, timeouts, and invalid responses report missing outside coverage instead of a clean review. Automatic reviews start fresh; consult session continuity is explicit.

Outside-review routing follows the harness, independently of the configured model. Generic second-opinion requests choose /claude-code on Codex and /codex elsewhere; explicit provider requests keep that provider. The existing codex_reviews setting controls the selected automatic reviewer in workflows that already use that setting. Existing opt-in and skip controls still apply in office hours, design, and spec workflows.

/claude was renamed to /claude-code without an alias. Run ./setup --host <name> to migrate managed installations, including installations sharing that checkout. Setup retains a working old installation when replacement generation or installation fails.

Proactive skill suggestions

gstack can invoke a skill for you when your request matches one. By default (proactive: core) only /office-hours, /review, /qa and /ship auto-invoke; all frees every skill and off suggests nothing. See docs/proactive.md.

Safety & Guardrails

Four skills that add safety rails to any Claude Code session. They work via Claude Code's PreToolUse hooks — transparent, session-scoped, no configuration required.

/careful

Say "be careful" or run /careful when you're working near production, running destructive commands, or just want a safety net. Every Bash and PowerShell command gets checked against known-dangerous patterns:

• rm -rf / rm -r — recursive delete
• DROP TABLE / DROP DATABASE / TRUNCATE — data loss
• git push --force / git push -f — history rewrite
• git reset --hard — discard commits
• git checkout . / git restore . — discard uncommitted work
• kubectl delete — production resource deletion
• docker rm -f / docker system prune — container/image loss

On Windows the same hook checks Claude Code's PowerShell tool and any pwsh/powershell/cmd launched from Bash: Remove-Item and its aliases with -Recurse/-Force (any parameter prefix), cmd rd /s and del /s, Format-Volume, Clear-Disk, Clear-Content and .NET deletes ask, and encoded or dynamic PowerShell (-EncodedCommand, iex, Start-Process of a shell, & $cmd) asks because it can't be inspected. PowerShell coverage is best-effort; Claude Code permission deny rules such as "PowerShell(Remove-Item *)" are the hard stop.

Common build artifact cleanups (rm -rf node_modules, dist, .next, __pycache__, build, coverage) are whitelisted — no false alarms on routine operations.

You can override any MEDIUM warning. Two catastrophic shapes are hard-denied instead of asked: recursive deletes of the filesystem root or your home directory (including the /*, ~/, and $HOME/ forms), and force-pushes to the repo's default branch (--force-with-lease never triggers the deny; the escape hatch is ending the session-scoped /careful session). You can also add your own warn rules — one POSIX ERE per line — in ~/.gstack/careful-patterns.txt (global) or ~/.gstack/projects/<slug>/careful-patterns.txt (per-project); custom patterns only ever add warnings, never suppress the built-ins. The guardrails are accident prevention, not access control.

/freeze

Restrict all file edits to a single directory. When you're debugging a billing bug, you don't want Claude accidentally "fixing" unrelated code in src/auth/. /freeze src/billing blocks all Edit, Write and NotebookEdit (Jupyter notebook) operations outside that path.

/investigate activates this automatically — it detects the module being debugged and freezes edits to that directory.

You:   /freeze src/billing

Claude: Edits restricted to src/billing/. Run /unfreeze to remove.

        [Later, Claude tries to edit src/auth/middleware.ts]

Claude: BLOCKED — Edit outside freeze boundary (src/billing/).
        Skipping this change.

Note: this blocks Edit and Write tools only. Bash commands like sed can still modify files outside the boundary — it's accident prevention, not a security sandbox.

/guard

Full safety mode — combines /careful + /freeze in one command. Destructive command warnings plus directory-scoped edits. Use when touching prod or debugging live systems.

/unfreeze

Remove the /freeze boundary, allowing edits everywhere again. The hooks stay registered for the session — they just allow everything. Run /freeze again to set a new boundary.

---

/captain

One controller, many lanes. /captain (also /crew) teaches a coordinating agent the operating model that keeps dozens of worker threads merging into one base branch without turning it red.

You: /captain
You: /captain ready 42        # validate a lane's READY block before it enters a train
You: /captain train           # build, read the verdict, call slots, verify, merge, verify
You: /captain digest          # rewrite Needs you / New / In progress

The rules: lanes never merge and their job ends at an unstamped READY (the block gstack-ship-queue ready prints, plus the full head SHA, the screen choice, the ship receipt at the pin and the logged flaky cases); a green PR page or a cheap test tier is never merge evidence. The controller batches READY pins into a merge train, reads one full gate on the train head (an in-run flaky rerun once; a case that failed twice is real), then merges slot by slot: slot call, lane stamps on call with a commit that holds only tool output, verify --train, gh pr merge --match-head-commit, verify again. Under changelog_fragments there is no slot call: train land publishes each slot's stamped prefix and merges it. A red train is bisected on its red cases and rebuilt at most once; a backstop gate on every base push freezes the queue when a tree no train covered lands. Approvals have three shapes (the per-thread record, the plan ask with before → after and a "do it" reply, the merge ask with captioned before/after images). The digest is Needs you / New / In progress with ages. A daily flaky-fix pass reads the gate runs' flake records and the free suites' retries into a ledger and fixes causes, never thresholds. Where crews that run this model disagree (squash or merge, who stamps, gate-ahead, the severe race, a gate run id in the READY), the skill ships both as options for the crew rules file.

Templates (CREW.md, AGENTS.md, NOTES.md, DIGEST.md, the flaky ledger, the lane report, the READY block, the slot call, the lane brief, the plan and merge asks, the daily automation prompt) live in captain/templates/; the team setup guide for Capy is docs/captain.md.

/gstack-upgrade

Keep gstack current with one command. It detects your install type (global at ~/.claude/skills/gstack vs vendored in your project at .claude/skills/gstack), runs the upgrade, syncs both copies if you have dual installs, and shows you what changed.

You:   /gstack-upgrade

Claude: Current version: 0.7.4
        Latest version: 0.8.2

        What's new:
        - Browser skills now drive your Aside browser
        - /codex multi-AI second opinion
        - /qa always uses browser now
        - Safety skills: /careful, /freeze, /guard
        - Proactive skill suggestions

        Upgraded to 0.8.2. Both global and project installs synced.

Set auto_upgrade: true in ~/.gstack/config.yaml to skip the prompt entirely — gstack upgrades silently at the start of each session when a new version is available.

---

Greptile integration

Greptile is a YC company that reviews your PRs automatically. It catches real bugs — race conditions, security issues, things that pass CI and blow up in production. It has genuinely saved my ass more than once. I love these guys.

Setup

Install Greptile on your GitHub repo at greptile.com — it takes about 30 seconds. Once it's reviewing your PRs, gstack picks up its comments automatically. No additional configuration.

How it works

The problem with any automated reviewer is triage. Greptile is good, but not every comment is a real issue. Some are false positives. Some flag things you already fixed three commits ago. Without a triage layer, the comments pile up and you start ignoring them — which defeats the purpose.

gstack solves this. /review and /ship are now Greptile-aware. They read Greptile's comments, classify each one, and take action:

• Valid issues get added to the critical findings and fixed before shipping
• Already-fixed issues get an auto-reply acknowledging the catch
• False positives get pushed back — you confirm, and a reply goes out explaining why it's wrong

The result is a two-layer review: Greptile catches things asynchronously on the PR, then /review and /ship triage those findings as part of the normal workflow. Nothing falls through the cracks.

Learning from history

Every false positive you confirm gets saved to ~/.gstack/greptile-history.md. Future runs auto-skip known FP patterns for your codebase. And /retro tracks Greptile's batting average over time — so you can see whether the signal-to-noise ratio is improving.

Example

You:   /ship

Claude: [syncs main, runs tests, pre-landing review...]

        Greptile found 3 comments on this PR:

        [VALID] app/services/payment_service.rb:47 — Race condition:
        concurrent charges can double-debit. Recommend DB-level advisory
        lock around the charge block.

        [ALREADY FIXED] app/models/user.rb:12 — Missing null check
        on email before downcase.
        → Already fixed in commit abc1234. Auto-replying.

        [FALSE POSITIVE] lib/auth.rb:88 — "Token comparison should
        use constant-time comparison." We already use
        ActiveSupport::SecurityUtils.secure_compare here.

        Fixing the race condition in payment_service.rb...

        The auth token comment is a false positive.
        Options: A) Reply to Greptile explaining  B) Fix anyway  C) Ignore

You:    A

Claude: Replied to Greptile. All tests pass.
        PR: github.com/you/app/pull/42

Three Greptile comments. One real fix. One auto-acknowledged. One false positive pushed back with a reply. Total extra time: about 30 seconds.

---

/ios-qa

Live-device iOS QA. The fork's load-bearing insight was: don't simulate, don't run XCTest, don't bring up WebDriverAgent. Embed an HTTP server in the app under test, drive it from a Mac-side daemon over the USB CoreDevice IPv6 tunnel.

The agent reads your Swift source, finds @Observable classes with @Snapshotable-marked fields, codegens typed accessors, deploys a debug bridge, then runs a closed find→fix→verify loop.

Architecture in one diagram

       ┌──────────────────────┐   USB CoreDevice (IPv6)   ┌──────────────────┐
       │ gstack-ios-qa daemon │ ────────────────────────▶ │ iOS app          │
       │ (Mac, bun/TS)        │   bearer + X-Session-Id   │ StateServer      │
       │ - rotates boot token │                           │ (loopback only)  │
       │ - mints session toks │                           └──────────────────┘
       │ - capability tiers   │
       │ - audit + redact     │
       └──────────────────────┘
                ▲
                │ Tailscale (optional, --tailnet)
                │
       ┌──────────────────────┐
       │ Remote agent         │
       │ (OpenClaw, etc.)     │
       └──────────────────────┘

The iOS app's StateServer binds loopback only (::1 + 127.0.0.1). The Mac daemon owns tailnet identity validation, capability tiers, and the audit trail. Remote agents NEVER see the boot token — only short-lived session tokens (1h default, 24h hard cap) minted via Tailscale identity gating.

The unlock: USB-tethered + Tailscale = remote iOS QA from any agent

A Mac plus an iPhone you already own plus the Tailscale free tier replaces what most teams pay BrowserStack/Sauce Labs for. Any HTTP-capable agent on your tailnet can drive the iOS app once you've minted them a session token. Tailscale ACLs scope which identities can reach the Mac at which capability tier.

See ios-qa/docs/tailscale-acl-example.md for the runnable setup.

Capability tiers

Tier	Endpoints
observe	/screenshot, /elements, GET /state/*, /state/snapshot, /healthz
interact	observe + /tap, /swipe, /type, /session/*
mutate	interact + POST /state/<key>
restore	mutate + POST /state/restore

Default minted tokens get interact. Higher tiers require explicit owner mint.

---

/ios-fix

Iron Law: no fix without a reproducing snapshot. The agent captures pre-bug state via GET /state/snapshot, writes the fix, rebuilds, redeploys, restores the snapshot, and verifies the bug is gone. The snapshot becomes a regression test fixture so the bug can't recur silently.

Mirrors /qa's find-bug → fix → re-verify loop for iOS.

---

/ios-design-review

Designer's-eye QA on a real iPhone. Connects to the same /ios-qa daemon in observe-tier mode and screenshots every screen. Scores 10 dimensions 0-10: typography hierarchy, spacing rhythm, color hierarchy, touch targets, loading/empty/error states, accessibility, animation discipline, iOS idiom alignment, information density, AI-slop check.

For each score < 7, uses AskUserQuestion to present the issue with recommended fix.

---

/ios-clean

Convenience wrapper. The structural Release-build guard against shipping DebugBridge is in Package.swift (.when(configuration: .debug)) plus a CI invariant test. /ios-clean is for developers who want a guided removal flow or who manually added the SPM dependency without going through /ios-qa.

---

/ios-sync

Run after upgrading gstack or adding new @Observable classes. Detects what's installed, runs gen-accessors against the latest upstream templates, refreshes any changed Swift files, verifies the app rebuilds. Cache-key invalidation handles Swift version changes, generator git rev changes, and source changes.