Garry Tan cab774cced v1.56.0.0 Token-reduction Phase B + AUQ paranoid safety net (#1849)
* refactor(plan-ceo-review): carve review body into on-demand section

Carve the largest skill (138,838 B) into a skeleton + one on-demand
section, the documented next Phase B target after /ship (v2_PLAN.md:216).

- sections/review-sections.md(.tmpl): the 11-section deep review, codex/
  outside-voice rules, how-to-ask, Required Outputs, registries, Completion
  Summary, Review Log, REVIEW_DASHBOARD, PLAN_FILE_REVIEW_REPORT, Next Steps,
  docs/designs promotion, Formatting Rules, and the Mode Quick Reference.
- sections/manifest.json: passive registry (CM2), one entry.
- SKILL.md.tmpl: {{SECTION_INDEX}} after the system audit, a single
  {{SECTION:review-sections}} STOP-Read after Step 0 mode selection, and a
  Section self-check. All of Step 0 (the scope/mode conversation) stays in
  the always-loaded skeleton; only EXIT_PLAN_MODE_GATE follows the section.

Measured: always-loaded skeleton 138,838 -> 80,731 B (-42%, ~14.4K tokens
off every invocation). Union (skeleton + section) 139,110 B, behavior held.

Boundary honors Codex P1: nothing review-governing (formatting rules, mode
reference, how-to-ask, required outputs) sits in the skeleton below the
STOP. Housekeeping resolvers ride in the section, matching the ship
precedent (adversarial.md carries LEARNINGS_LOG + GBRAIN_SAVE_RESULTS).

Tests (atomic with the carve — skill-docs.yml gates gen:skill-docs
freshness on every push, so source + regen + tests must land together):
- parity-harness: plan-ceo flipped to sectioned, maxSkeletonBytes 90_000
  (measured 80,731 + headroom); content/minBytes run against the union.
- skill-size-budget: plan-ceo-review added to SECTIONS_EXTRACTED.
- section-manifest-consistency: generalized to discover every carved skill,
  vars computed per-skill-case (Codex P2).
- skill-ceo-section-ordering (new, gate): per-PR static guard — STOP after
  Step 0, review body absent from skeleton, report writer in the section,
  nothing review-governing below the STOP.
- skill-e2e-plan-ceo-review-section-loading (new, periodic): refreshes the
  installed skill first (Codex P1), drives full Step 0, asserts the section
  is Read before the report.
- gen-skill-docs + skill-validation: read the skeleton+sections union for
  carved skills so relocated prose still counts.
- touchfiles: plan-ceo-section-loading registered (periodic).

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>

* chore: bump VERSION + CHANGELOG for plan-ceo-review carve (v1.56.0.0)

MINOR: carves the largest skill into skeleton + on-demand section,
dropping plan-ceo-review's always-loaded cost 42% (138,838 -> 80,731 B,
~14.4K tokens off every invocation). User-facing release notes lead with
the measured token win.

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>

* docs(todos): file P3 follow-up — carve the shared {{PREAMBLE}} reference blocks

Surfaced by /plan-eng-review on the plan-ceo-review carve: per-skill section
carves stay modest because the ~40-50KB shared preamble dominates the
always-loaded surface. A single preamble-reference carve would help every
tier->=2 skill at once. Records the why, the cold-vs-hot split to measure,
and the guards it needs. Not implemented this PR.

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>

* test(auq): Layer 0 — guarantee AUQ format spec is always-loaded

Deterministic, free, per-PR keystone for the token-reduction era. For every
interactive (tier>=2) skill, asserts the full AskUserQuestion decision-brief
format (ELI10/Recommendation/Pros-cons/checks/Net/(recommended)/Stakes/
self-check) lives in the always-loaded SKILL.md skeleton, NOT only in an
on-demand section. Plus a roster guard (a carve can't silently drop the block)
and per-skill rule survival in the skeleton+sections union. 51 cases + a
negative control. Fails the instant a future carve strands AUQ-governing text
where it won't be loaded when a question fires.

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>

* test(auq): SDK capture engine + verbose-vs-carved no-degradation A/B

Adds the reusable SDK $OUT_FILE capture engine (auq-sdk-capture.ts): drives a
skill to its AUQ and captures the verbatim text the model GENERATES, cleanly
(real-PTY mangles plan-mode AUQs via cursor escapes). Pins the skill to an
absolute path with Read/Write-only tools so the agent can't wander to the
global install. gradeAuqRecommendation normalizes a non-"because" connective
before grading so substantive reasons aren't false-flagged (without touching
the pinned shared judge).

The A/B drives the same prompt through the carved 80KB skeleton and the
pre-carve 137KB monolith and fails if carved scores worse. Result: both 7/7
format, substance 5 — proven no degradation, transcript-verified each side read
its own planted SKILL.md. Periodic tier.

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>

* test(auq): consistency — same trigger N runs, stable format + substance

Drives the carved /plan-ceo-review AUQ N=3 times and fails if any format
element appears in one run but not another, or substance craters. Targets the
"fine one run, broken the next" failure class a single snapshot can't see.
Result: 3/3 stable, 7/7 + substance 5 every run. Periodic tier.

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>

* test(auq): behavioral matrix across AUQ-heavy skills

Data-driven test that drives each AUQ-heavy skill (plan-eng/design/devex,
office-hours, cso, spec, design-consultation) to its first AskUserQuestion and
grades it to the plan-ceo bar: 7/7 decision-brief format + recommendation
substance >=4. One case per skill (isolated failures), env-subsettable via
AUQ_MATRIX_ONLY. Browser/design-binary skills are intentionally excluded
(comparison boards, not format-AUQs; Layer 0 covers their spec). All targeted
skills pass 7/7 with substance 4-5. Periodic tier.

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>

* test(codex): live recommendation-substance grade for /codex

Closes the gap where /codex's synthesis recommendation was only checked
statically (template grep) and via fixtures. Drives the real /codex skill over
a flawed diff and grades the emitted "Recommendation: ... because ..." line
with judgeRecommendation (present/commits/has_because/substance>=4). The named
weak spot holds up: substance 5. Periodic tier.

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>

* test(auq): deterministic trigger for format-compliance gate

A bare /plan-ceo-review against a repo whose work is already implemented makes
the model improvise an off-script "what should I review?" scope question that
skips the decision-brief format, which the gate test then times out waiting for.
Hand it a concrete plan to review (FORCING_FLOOR_CEO) so it reaches the real
Step 0 mode-selection AUQ that is the intended format check.

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>

* refactor(office-hours): carve Phase 5+6 into on-demand section

Third Phase B carve (v2_PLAN.md:216, after ship and plan-ceo-review). Moves
Phase 5 (Design Doc templates) + Phase 6 (tiered relationship handoff) — the
session's output + closing tail, only reached after the conversation and
alternatives are done — into sections/design-and-handoff.md, behind a single
STOP-Read after Phase 4.5. The live conversation (Phases 1-4.5) and the
always-run Important Rules stay in the always-loaded skeleton.

Measured: always-loaded skeleton 118,280 -> 88,975 B (-24.8%). Union preserved.
The carved AUQ is identical to pre-carve (matrix: 7/7 format, substance 5),
and Layer 0 confirms the AUQ format spec stays in the skeleton — the AUQ
paranoid suite de-risked this carve end to end.

Atomic with tests + regen (skill-docs.yml gates gen:skill-docs freshness on
every push, so source + regen + tests land together; --host all regenerates
the inlined non-Claude variants):
- sections/manifest.json: passive registry, one entry.
- parity-harness: office-hours flipped to sectioned, maxSkeletonBytes 96_000
  (measured 88,975 + headroom); content/minBytes run against the union.
- skill-size-budget: office-hours added to SECTIONS_EXTRACTED.
- gen-skill-docs + skill-validation: read the skeleton+sections union for
  office-hours so relocated Phase 5/6 prose still counts.

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>

* chore: bump VERSION + CHANGELOG for office-hours carve + AUQ suite (v1.57.0.0)

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>

* refactor(preamble): carve CJK-escaping manual to on-demand doc

The AskUserQuestion format block is inlined into every interactive skill (~33).
It carried the full multi-paragraph non-ASCII/CJK escaping manual inline, but
that rationale only matters when a question contains CJK text and the operative
rule already lives in the always-loaded self-check. Moved the justification to
docs/askuserquestion-cjk.md (read on demand); kept the rule + a pointer.

Corpus: Claude-host SKILL.md total 3,087,499 -> 3,057,975 B (-29,524 B, ~900 B
x ~33 skills). Layer 0 still passes — the core decision-brief format stays
always-loaded; only the rare CJK rationale moved. Atomic with the all-host
regen (skill-docs.yml freshness gate). VERSION + package.json -> 1.58.0.0.

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>

* refactor(plan-eng-review): carve review body into on-demand section

Fourth Phase B carve (v2_PLAN.md:220). Moves the 4-section review (Architecture,
Code Quality, Tests, Performance), outside voice, required outputs, and review
report — everything after Step 0 scope — into sections/review-sections.md behind
a single STOP-Read. Step 0 (scope challenge) and EXIT_PLAN_MODE_GATE stay in the
always-loaded skeleton.

Measured: skeleton 106,984 -> 54,892 B (-48.7%). Union preserved. Atomic with
tests + all-host regen (freshness gate): parity flipped to sectioned
(maxSkeletonBytes 62K), plan-eng-review added to SECTIONS_EXTRACTED, gen-skill-docs
reads the union for relocated review/TEST_COVERAGE/dashboard prose. Layer 0 green.

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>

* refactor(plan-design-review): carve review body into on-demand section

Fifth Phase B carve (v2_PLAN.md:220, bundled with plan-eng). Moves the 7 design
passes, required outputs, and review report — everything after Step 0 scope and
the mockup/rating phase — into sections/review-sections.md behind a STOP-Read.
Step 0, Step 0.5 mockups, the rating method, and EXIT_PLAN_MODE_GATE stay in the
always-loaded skeleton.

Measured: skeleton 112,057 -> 76,024 B (-32.2%). Union preserved. Atomic with
tests + all-host regen: parity sectioned (maxSkeletonBytes 82K), added to
SECTIONS_EXTRACTED, gen-skill-docs reads the union. Layer 0 green.

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>

* refactor(plan-devex-review): carve review body into on-demand section

Sixth Phase B carve. Moves the 8 DX passes, required outputs, and review report
— everything after the Step 0 DX investigation — into sections/review-sections.md
behind a STOP-Read. All of Step 0 (persona, empathy, benchmark, journey trace,
roleplay) + the rating method + EXIT_PLAN_MODE_GATE stay always-loaded.

Measured: skeleton 110,621 -> 69,658 B (-37%). Union preserved. Atomic with
tests + all-host regen: added to SECTIONS_EXTRACTED, gen-skill-docs reads the
union. Layer 0 green. (No parity invariant entry for plan-devex-review.)

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>

* chore: bump VERSION + CHANGELOG for plan-* family carves (v1.59.0.0)

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>

* test: refresh ship golden baselines + gbrain-detection union after carves

Two follow-ups the carve commits should have carried (caught by the full suite,
missed by targeted subsets):
- ship golden baselines (claude/codex/factory) regenerated: the preamble CJK
  trim (v1.58) changed ship's always-loaded AskUserQuestion block.
- gbrain-detection-override probes the office-hours skeleton+section union:
  GBRAIN_SAVE_RESULTS moved into sections/design-and-handoff.md when office-hours
  was carved, so the detection assertions now check both files.

Full `bun test` green.

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>

* test(auq): grade format-compliance gate from SDK capture, not the TUI

The real-PTY version grepped the stripAnsi'd interactive AUQ picker. Verified
directly that this cannot work: plan-mode AUQs render as a cursor picker whose
cursor-positioning escapes stripAnsi can't flatten — the picker renders fine for
a human (cursorSeen=45) but the flattened text drops ELI10:/(recommended) and
parseNumberedOptions returns 0. The test was grading a lossy projection and
failed by construction.

Rewritten to drive /plan-ceo-review via the SDK $OUT_FILE capture (the agent
writes the verbatim question it would have shown — clean text, no rendering
loss) and grade 7/7 format + kind-note + recommendation substance >=4. Same
property, reliable, environment-independent; shares the engine with the periodic
A/B and matrix evals. Result: 7/7 format, substance 5. Touchfiles key renamed
ask-user-question-format-pty -> auq-format-gate (no longer a PTY test).

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>

* test: fix carve-broken CI evals (union reads + section fixtures)

Two CI eval jobs failed on the carved plan-* skills because they read content
that moved into sections/:

- llm-judge (skill-llm-eval): runWorkflowJudge sliced SKILL.md between markers
  like "## Review Sections" / "## CRITICAL RULE" that now live in
  sections/review-sections.md. The markers vanished from the skeleton, so the
  judge scored empty/wrong content. Fix: read the skeleton+sections union.
  Verified: plan-ceo modes / plan-eng sections / plan-design passes all PASS
  (25/25).

- e2e-plan (skill-e2e-plan): setupPlanDir copied only <skill>/SKILL.md into the
  fixture, not sections/. The carved skill's STOP pointed at a section file that
  was absent, so the model improvised a compressed report table instead of the
  canonical "| Review | Trigger | Why | Runs | Status | Findings |". Fix: copy
  sections/ alongside SKILL.md in all 6 setup sites. Verified: report test PASS,
  canonical table emitted.

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>

* test: copy carved sections into all e2e fixtures (prevent more carve-blind CI fails)

Proactive sweep beyond the two CI logs: every e2e test that copies a carved
skill's SKILL.md into a temp fixture must also copy its sections/, or the
model hits a STOP pointing at a missing section file and improvises/degrades.

- skill-e2e.test.ts: plan-ceo/plan-eng/plan-design/office-hours copies across
  planDir/reviewDir/ohDir/benefitsDir dests now copy sections/.
- skill-e2e-plan.test.ts: the office-hours copy + the 4-skill codex-offering
  loop now copy sections/.
- skill-e2e-design.test.ts: plan-design-review copy now copies sections/.
- skill-e2e-office-hours.test.ts: both office-hours copies now copy sections/.
- skill-e2e-office-hours-brain-writeback.test.ts: GBRAIN_SAVE_RESULTS moved into
  the section, so check the regenerated skeleton+section UNION for the gbrain put
  block, ship both into the workdir, and restore both (the section regen was also
  leaking into the working tree — finally now restores it).

ship copies (single-file Step-0 slices) and review/retro (not carved) untouched.

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>

* test: migrate section-loading E2E to lossless SDK tool-stream detection

The /ship and /plan-ceo-review section-loading tests drove a real PTY and
scraped the ANSI screen buffer for sections/<file>.md paths. That silently
saw nothing in a Conductor PTY (cursor-positioned tool renders and an
unanswered Step 0 question loop both defeat the regex), so both reported
read: [] even when the agent did the work.

They now run the skill through claude -p (the same SDK path the AUQ matrix
uses) and detect section reads from the tool-use stream — Read calls whose
file_path contains sections/<file>.md — with no rendering layer to mangle.
The run is also hermetic: the freshly-generated worktree skeleton + sections
are copied into a throwaway fixture with the absolute path pinned, so the
test validates this branch's carve without mutating the user's ~/.claude
install.

Validated EVALS_TIER=periodic: both pass (plan-ceo Reads review-sections.md;
ship Reads review-army.md + changelog.md), ~6.5 min for both vs ~23 min
combined on the old PTY path where both were failing.

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>

* chore: consolidate branch to v1.56.0.0 (single MINOR above main)

The branch bumped VERSION several times during development (1.56 → 1.57 →
1.58 → 1.59), but none of those landed on main (main is at 1.55.1.0). Per
the "never orphan branch-internal versions" discipline, collapse all four
into a single 1.56.0.0 entry — one MINOR release covering the whole branch:
five skills carved (plan-ceo, office-hours, plan-eng, plan-design,
plan-devex), the shared AskUserQuestion preamble CJK trim, and the paranoid
AUQ no-degradation test suite + lossless section-loading tests.

VERSION and package.json set to 1.56.0.0; main's 1.55.1.0 entry preserved
below the consolidated entry. No SKILL.md drift (VERSION is not embedded in
generated bodies).

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>

---------

Co-authored-by: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
2026-06-04 11:14:43 -07:00
2026-03-12 01:32:16 -07:00

gstack

"I don't think I've typed like a line of code probably since December, basically, which is an extremely large change." — Andrej Karpathy, No Priors podcast, March 2026

When I heard Karpathy say this, I wanted to find out how. How does one person ship like a team of twenty? Peter Steinberger built OpenClaw — 247K GitHub stars — essentially solo with AI agents. The revolution is here. A single builder with the right tooling can move faster than a traditional team.

I'm Garry Tan, President & CEO of Y Combinator. I've worked with thousands of startups — Coinbase, Instacart, Rippling — when they were one or two people in a garage. Before YC, I was one of the first eng/PM/designers at Palantir, cofounded Posterous (sold to Twitter), and built Bookface, YC's internal social network.

gstack is my answer. I've been building products for twenty years, and right now I'm shipping more products than I ever have. In the last 60 days: 3 production services, 40+ shipped features, part-time, while running YC full-time. On logical code change — not raw LOC, which AI inflates — my 2026 run rate is ~810× my 2013 pace (11,417 vs 14 logical lines/day). Year-to-date (through April 18), 2026 has already produced 240× the entire 2013 year. Measured across 40 public + private garrytan/* repos including Bookface, after excluding one demo repo. AI wrote most of it. The point isn't who typed it, it's what shipped.

The LOC critics aren't wrong that raw line counts inflate with AI. They are wrong that normalized-for-inflation, I'm less productive. I'm more productive, by a lot. Full methodology, caveats, and reproduction script: On the LOC Controversy.

2026 — 1,237 contributions and counting:

GitHub contributions 2026 — 1,237 contributions, massive acceleration in Jan-Mar

2013 — when I built Bookface at YC (772 contributions):

GitHub contributions 2013 — 772 contributions building Bookface at YC

Same person. Different era. The difference is the tooling.

gstack is how I do it. It turns Claude Code into a virtual engineering team — a CEO who rethinks the product, an eng manager who locks architecture, a designer who catches AI slop, a reviewer who finds production bugs, a QA lead who opens a real browser, a security officer who runs OWASP + STRIDE audits, and a release engineer who ships the PR. Twenty-three specialists and eight power tools, all slash commands, all Markdown, all free, MIT license.

This is my open source software factory. I use it every day. I'm sharing it because these tools should be available to everyone.

Fork it. Improve it. Make it yours. And if you want to hate on free open source software — you're welcome to, but I'd rather you just try it first.

Who this is for:

  • Founders and CEOs — especially technical ones who still want to ship
  • First-time Claude Code users — structured roles instead of a blank prompt
  • Tech leads and staff engineers — rigorous review, QA, and release automation on every PR

Quick start

  1. Install gstack (30 seconds — see below)
  2. Run /office-hours — describe what you're building
  3. Run /plan-ceo-review on any feature idea
  4. Run /review on any branch with changes
  5. Run /qa on your staging URL
  6. Stop there. You'll know if this is for you.

Install — 30 seconds

Requirements: Claude Code, Git, Bun v1.0+, Node.js (Windows only)

Step 1: Install on your machine

Open Claude Code and paste this. Claude does the rest.

Install gstack: run git clone --single-branch --depth 1 https://github.com/garrytan/gstack.git ~/.claude/skills/gstack && cd ~/.claude/skills/gstack && ./setup then add a "gstack" section to CLAUDE.md that says to use the /browse skill from gstack for all web browsing, never use mcp__claude-in-chrome__* tools, and lists the available skills: /office-hours, /plan-ceo-review, /plan-eng-review, /plan-design-review, /design-consultation, /design-shotgun, /design-html, /review, /ship, /land-and-deploy, /canary, /benchmark, /browse, /connect-chrome, /qa, /qa-only, /design-review, /setup-browser-cookies, /setup-deploy, /setup-gbrain, /retro, /investigate, /document-release, /document-generate, /codex, /cso, /autoplan, /plan-devex-review, /devex-review, /careful, /freeze, /guard, /unfreeze, /gstack-upgrade, /learn. Then ask the user if they also want to add gstack to the current project so teammates get it.

From inside your repo, paste this. Switches you to team mode, bootstraps the repo so teammates get gstack automatically, and commits the change:

(cd ~/.claude/skills/gstack && ./setup --team) && ~/.claude/skills/gstack/bin/gstack-team-init required && git add .claude/ CLAUDE.md && git commit -m "require gstack for AI-assisted work"

No vendored files in your repo, no version drift, no manual upgrades. Every Claude Code session starts with a fast auto-update check (throttled to once/hour, network-failure-safe, completely silent).

Swap required for optional if you'd rather nudge teammates than block them.

OpenClaw

OpenClaw spawns Claude Code sessions via ACP, so every gstack skill just works when Claude Code has gstack installed. Paste this to your OpenClaw agent:

Install gstack: run git clone --single-branch --depth 1 https://github.com/garrytan/gstack.git ~/.claude/skills/gstack && cd ~/.claude/skills/gstack && ./setup to install gstack for Claude Code. Then add a "Coding Tasks" section to AGENTS.md that says: when spawning Claude Code sessions for coding work, tell the session to use gstack skills. Include these examples — security audit: "Load gstack. Run /cso", code review: "Load gstack. Run /review", QA test a URL: "Load gstack. Run /qa https://...", build a feature end-to-end: "Load gstack. Run /autoplan, implement the plan, then run /ship", plan before building: "Load gstack. Run /office-hours then /autoplan. Save the plan, don't implement."

After setup, just talk to your OpenClaw agent naturally:

You say What happens
"Fix the typo in README" Simple — Claude Code session, no gstack needed
"Run a security audit on this repo" Spawns Claude Code with Run /cso
"Build me a notifications feature" Spawns Claude Code with /autoplan → implement → /ship
"Help me plan the v2 API redesign" Spawns Claude Code with /office-hours → /autoplan, saves plan

See docs/OPENCLAW.md for advanced dispatch routing and the gstack-lite/gstack-full prompt templates.

Native OpenClaw Skills (via ClawHub)

Four methodology skills that work directly in your OpenClaw agent, no Claude Code session needed. Install from ClawHub:

clawhub install gstack-openclaw-office-hours gstack-openclaw-ceo-review gstack-openclaw-investigate gstack-openclaw-retro
Skill What it does
gstack-openclaw-office-hours Product interrogation with 6 forcing questions
gstack-openclaw-ceo-review Strategic challenge with 4 scope modes
gstack-openclaw-investigate Root cause debugging methodology
gstack-openclaw-retro Weekly engineering retrospective

These are conversational skills. Your OpenClaw agent runs them directly via chat.

Other AI Agents

gstack works on 10 AI coding agents, not just Claude. Setup auto-detects which agents you have installed:

git clone --single-branch --depth 1 https://github.com/garrytan/gstack.git ~/gstack
cd ~/gstack && ./setup

Or target a specific agent with ./setup --host <name>:

Agent Flag Skills install to
OpenAI Codex CLI --host codex ~/.codex/skills/gstack-*/
OpenCode --host opencode ~/.config/opencode/skills/gstack-*/
Cursor --host cursor ~/.cursor/skills/gstack-*/
Factory Droid --host factory ~/.factory/skills/gstack-*/
Slate --host slate ~/.slate/skills/gstack-*/
Kiro --host kiro ~/.kiro/skills/gstack-*/
Hermes --host hermes ~/.hermes/skills/gstack-*/
GBrain (mod) --host gbrain ~/.gbrain/skills/gstack-*/

Want to add support for another agent? See docs/ADDING_A_HOST.md. It's one TypeScript config file, zero code changes.

See it work

You:    I want to build a daily briefing app for my calendar.
You:    /office-hours
Claude: [asks about the pain — specific examples, not hypotheticals]

You:    Multiple Google calendars, events with stale info, wrong locations.
        Prep takes forever and the results aren't good enough...

Claude: I'm going to push back on the framing. You said "daily briefing
        app." But what you actually described is a personal chief of
        staff AI.
        [extracts 5 capabilities you didn't realize you were describing]
        [challenges 4 premises — you agree, disagree, or adjust]
        [generates 3 implementation approaches with effort estimates]
        RECOMMENDATION: Ship the narrowest wedge tomorrow, learn from
        real usage. The full vision is a 3-month project — start with
        the daily briefing that actually works.
        [writes design doc → feeds into downstream skills automatically]

You:    /plan-ceo-review
        [reads the design doc, challenges scope, runs 10-section review]

You:    /plan-eng-review
        [ASCII diagrams for data flow, state machines, error paths]
        [test matrix, failure modes, security concerns]

You:    Approve plan. Exit plan mode.
        [writes 2,400 lines across 11 files. ~8 minutes.]

You:    /review
        [AUTO-FIXED] 2 issues. [ASK] Race condition → you approve fix.

You:    /qa https://staging.myapp.com
        [opens real browser, clicks through flows, finds and fixes a bug]

You:    /ship
        Tests: 42 → 51 (+9 new). PR: github.com/you/app/pull/42

You said "daily briefing app." The agent said "you're building a chief of staff AI" — because it listened to your pain, not your feature request. Eight commands, end to end. That is not a copilot. That is a team.

The sprint

gstack is a process, not a collection of tools. The skills run in the order a sprint runs:

Think → Plan → Build → Review → Test → Ship → Reflect

Each skill feeds into the next. /office-hours writes a design doc that /plan-ceo-review reads. /plan-eng-review writes a test plan that /qa picks up. /review catches bugs that /ship verifies are fixed. Nothing falls through the cracks because every step knows what came before it.

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.
/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 Rates each design dimension 0-10, explains what a 10 looks like, then edits the plan to get there. AI Slop detection. Interactive — one AskUserQuestion per design choice.
/plan-devex-review Developer Experience Lead Interactive DX review: explores developer personas, benchmarks against competitors' TTHW, designs your magical moment, traces friction points step by step. Three modes: DX EXPANSION, DX POLISH, DX TRIAGE. 20-45 forcing questions.
/design-consultation Design Partner Build a complete design system from scratch. Researches the landscape, proposes creative risks, generates realistic product mockups.
/review Staff Engineer Find the bugs that pass CI but blow up in production. Auto-fixes the obvious ones. Flags completeness gaps.
/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 Same audit as /plan-design-review, then fixes what it finds. Atomic commits, before/after screenshots.
/devex-review DX Tester Live developer experience audit. Actually tests your onboarding: navigates docs, tries the getting started flow, times TTHW, screenshots errors. Compares against /plan-devex-review scores — the boomerang that shows if your plan matched reality.
/design-shotgun Design Explorer "Show me options." Generates 4-6 AI mockup variants, opens a comparison board in your browser, collects your feedback, and iterates. Taste memory learns what you like. Repeat until you love something, then hand it to /design-html.
/design-html Design Engineer Turn a mockup into production HTML that actually works. Pretext computed layout: text reflows, heights adjust, layouts are dynamic. 30KB, zero deps. Detects React/Svelte/Vue. Smart API routing per design type (landing page vs dashboard vs form). The output is shippable, not a demo.
/qa QA Lead Test your app, find bugs, fix them with atomic commits, re-verify. Auto-generates regression tests for every fix.
/qa-only QA Reporter Same methodology as /qa but report only. Pure bug report without code changes.
/pair-agent Multi-Agent Coordinator Share your browser with any AI agent. One command, one paste, connected. Works with OpenClaw, Hermes, Codex, Cursor, or anything that can curl. Each agent gets its own tab. Auto-launches headed mode so you watch everything. Auto-starts ngrok tunnel for remote agents. Scoped tokens, tab isolation, rate limiting, activity attribution.
/cso Chief Security Officer OWASP Top 10 + STRIDE threat model. Zero-noise: 17 false positive exclusions, 8/10+ confidence gate, independent finding verification. Each finding includes a concrete exploit scenario.
/ship Release Engineer Sync main, run tests, audit coverage, push, open PR. Bootstraps test frameworks if you don't have one.
/land-and-deploy Release Engineer Merge the PR, wait for CI and deploy, verify production health. One command from "approved" to "verified in production."
/canary SRE Post-deploy monitoring loop. Watches for console errors, performance regressions, and page failures.
/benchmark Performance Engineer Baseline page load times, Core Web Vitals, and resource sizes. Compare before/after on every PR.
/document-release Technical Writer Update all project docs to match what you just shipped. Catches stale READMEs automatically. Builds a Diataxis coverage map (reference / how-to / tutorial / explanation) so gaps are visible in the PR body.
/document-generate Documentation Author Generate missing docs from scratch using the Diataxis framework. Researches the codebase first, then writes reference / how-to / tutorial / explanation docs that actually match the code. Invokable standalone or chained from /document-release when the coverage map finds gaps. Learn more: tutorialhow-towhy Diataxis.
/retro Eng Manager Team-aware weekly retro. Per-person breakdowns, shipping streaks, test health trends, growth opportunities. /retro global runs across all your projects and AI tools (Claude Code, Codex, Gemini).
/browse QA Engineer Give the agent eyes. Real Chromium browser, real clicks, real screenshots. ~100ms per command. /open-gstack-browser launches GStack Browser with sidebar, anti-bot stealth, and auto model routing.
/setup-browser-cookies Session Manager Import cookies from your real browser (Chrome, Arc, Brave, Edge) into the headless session. Test authenticated pages.
/autoplan Review Pipeline One command, fully reviewed plan. Runs CEO → design → eng review automatically with encoded decision principles. Surfaces only taste decisions for your approval.
/spec Spec Author Turn vague intent into a precise, executable spec in five phases (why, scope, technical with mandatory code-reading, draft, file). Codex quality gate before file (blocks below 7/10), fail-closed secret redaction, dedupe against existing issues, archive to $GSTACK_STATE_ROOT/projects/$SLUG/specs/ for team-corpus recall. --execute spawns claude -p in a fresh worktree; /ship auto-closes the source issue on merge. Plan-mode aware.
/learn Memory Manage what gstack learned across sessions. Review, search, prune, and export project-specific patterns, pitfalls, and preferences. Learnings compound across sessions so gstack gets smarter on your codebase over time.

Which review should I use?

Building for... Plan stage (before code) Live audit (after shipping)
End users (UI, web app, mobile) /plan-design-review /design-review
Developers (API, CLI, SDK, docs) /plan-devex-review /devex-review
Architecture (data flow, perf, tests) /plan-eng-review /review
All of the above /autoplan (runs CEO → design → eng → DX, auto-detects which apply)

Power tools

Skill What it does
/codex Second Opinion — independent code review from OpenAI Codex CLI. Three modes: review (pass/fail gate), adversarial challenge, and open consultation. Cross-model analysis when both /review and /codex have run.
/careful Safety Guardrails — warns before destructive commands (rm -rf, DROP TABLE, force-push). Say "be careful" to activate. Override any warning.
/freeze Edit Lock — restrict file edits to one directory. Prevents accidental changes outside scope while debugging.
/guard Full Safety/careful + /freeze in one command. Maximum safety for prod work.
/unfreeze Unlock — remove the /freeze boundary.
/open-gstack-browser GStack Browser — launch GStack Browser with sidebar, anti-bot stealth, auto model routing (Sonnet for actions, Opus for analysis), one-click cookie import, and Claude Code integration. Clean up pages, take smart screenshots, edit CSS, and pass info back to your terminal.
/setup-deploy Deploy Configurator — one-time setup for /land-and-deploy. Detects your platform, production URL, and deploy commands.
/setup-gbrain GBrain Onboarding — from zero to running gbrain in under 5 minutes. PGLite local, Supabase existing URL, or auto-provision a new Supabase project via Management API. MCP registration for Claude Code + per-repo trust triad (read-write/read-only/deny). Full guide.
/sync-gbrain Keep Brain Current — re-index this repo's code into gbrain via gbrain sources add + gbrain sync --strategy code, refresh the ## GBrain Search Guidance block in CLAUDE.md, and auto-remove guidance when the capability check fails. --incremental (default), --full, --dry-run. Idempotent; safe to re-run.
/gstack-upgrade Self-Updater — upgrade gstack to latest. Detects global vs vendored install, syncs both, shows what changed.
/ios-qa iOS Live-Device QA (v1.43.0.0+) — drive a real iPhone over USB CoreDevice via an embedded StateServer in the app. Read Swift source, codegen typed @Observable accessors, run the agent loop. Optional --tailnet flag exposes the device to OpenClaw or any HTTP-capable agent on your Tailscale tailnet so remote agents can run iOS QA without ever touching the hardware. Capability-tier allowlist (observe/interact/mutate/restore), per-device session lock, audit log.
/ios-fix, /ios-design-review, /ios-clean, /ios-sync iOS bug-fix loop, designer's-eye HIG audit, debug-bridge cleanup, and accessor resync. See docs/skills.md. End-to-end walkthrough: docs/howto-ios-testing-with-gstack.md.

New binaries (v0.19)

Beyond the slash-command skills, gstack ships standalone CLIs for workflows that don't belong inside a session:

Command What it does
gstack-model-benchmark Cross-model benchmark — run the same prompt through Claude, GPT (via Codex CLI), and Gemini; compare latency, tokens, cost, and (optionally) LLM-judge quality score. Auth detected per provider, unavailable providers skip cleanly. Output as table, JSON, or markdown. --dry-run validates flags + auth without spending API calls.
gstack-taste-update Design taste learning — writes approvals and rejections from /design-shotgun into a persistent per-project taste profile. Decays 5%/week. Feeds back into future variant generation so the system learns what you actually pick.
gstack-ios-qa-daemon iOS QA daemon — Mac-side broker between an agent and a connected iPhone over USB CoreDevice. Loopback by default; --tailnet opens a Tailscale-facing listener with identity-gated capability tiers. Single-instance via flock on ~/.gstack/ios-qa-daemon.pid. See docs/howto-ios-testing-with-gstack.md.
gstack-ios-qa-mint iOS allowlist manager — owner-grant CLI for the tailnet allowlist. grant/revoke/list against ~/.gstack/ios-qa-allowlist.json (mode 0600). Remote agents never auto-allowlist; this is the explicit-intent path.

Continuous checkpoint mode (opt-in, local by default)

Set gstack-config set checkpoint_mode continuous and skills auto-commit your work as you go with a WIP: prefix plus a structured [gstack-context] body (decisions, remaining work, failed approaches). Survives crashes and context switches. /context-restore reads those commits to reconstruct session state. /ship filter-squashes WIP commits before the PR (preserving non-WIP commits) so bisect stays clean. Push is opt-in via checkpoint_push=true — default is local-only so you don't trigger CI on every WIP commit.

Domain skills + raw CDP escape hatch

Two new browser primitives compound the gstack agent over time:

  • $B domain-skill save — agent saves a per-site note (e.g., "LinkedIn's Apply button lives in an iframe") that fires automatically next time it visits that hostname. Quarantined → active after 3 successful uses → optional cross-project promotion via $B domain-skill promote-to-global. Storage lives alongside /learn's per-project learnings file. Full reference: docs/domain-skills.md.
  • $B cdp <Domain.method> — raw Chrome DevTools Protocol escape hatch for the rare case curated commands miss. Deny-default: methods must be explicitly added to browse/src/cdp-allowlist.ts with a one-line justification. Two-tier mutex serializes browser-scoped CDP calls against per-tab work. Output for data-exfil methods is wrapped in the UNTRUSTED envelope.

Want raw CDP with no rails, no allowlist, no daemon — just thin transport from agent to Chrome? browser-use/browser-harness-js is a different philosophy (agent-authored helpers vs gstack's curated commands) and a good fit if you don't want gstack's security stack. The two can coexist: gstack's $B cdp and harness can both attach to the same Chrome via Playwright's newCDPSession.

Deep dives with examples and philosophy for every skill →

Karpathy's four failure modes? Already covered.

Andrej Karpathy's AI coding rules (17K stars) nail four failure modes: wrong assumptions, overcomplexity, orthogonal edits, imperative over declarative. gstack's workflow skills enforce all four. /office-hours forces assumptions into the open before code is written. The Confusion Protocol stops Claude from guessing on architectural decisions. /review catches unnecessary complexity and drive-by edits. /ship transforms tasks into verifiable goals with test-first execution. If you already use Karpathy-style CLAUDE.md rules, gstack is the workflow enforcement layer that makes them stick across entire sprints, not just single prompts.

Parallel sprints

gstack works well with one sprint. It gets interesting with ten running at once.

Design is at the heart. /design-consultation builds your design system from scratch, researches what's out there, proposes creative risks, and writes DESIGN.md. But the real magic is the shotgun-to-HTML pipeline.

/design-shotgun is how you explore. You describe what you want. It generates 4-6 AI mockup variants using GPT Image. Then it opens a comparison board in your browser with all variants side by side. You pick favorites, leave feedback ("more whitespace", "bolder headline", "lose the gradient"), and it generates a new round. Repeat until you love something. Taste memory kicks in after a few rounds so it starts biasing toward what you actually like. No more describing your vision in words and hoping the AI gets it. You see options, pick the good ones, and iterate visually.

/design-html makes it real. Take that approved mockup (from /design-shotgun, a CEO plan, a design review, or just a description) and turn it into production-quality HTML/CSS. Not the kind of AI HTML that looks fine at one viewport width and breaks everywhere else. This uses Pretext for computed text layout: text actually reflows on resize, heights adjust to content, layouts are dynamic. 30KB overhead, zero dependencies. It detects your framework (React, Svelte, Vue) and outputs the right format. Smart API routing picks different Pretext patterns depending on whether it's a landing page, dashboard, form, or card layout. The output is something you'd actually ship, not a demo.

/qa was a massive unlock. It let me go from 6 to 12 parallel workers. Claude Code saying "I SEE THE ISSUE" and then actually fixing it, generating a regression test, and verifying the fix — that changed how I work. The agent has eyes now.

Smart review routing. Just like at a well-run startup: CEO doesn't have to look at infra bug fixes, design review isn't needed for backend changes. gstack tracks what reviews are run, figures out what's appropriate, and just does the smart thing. The Review Readiness Dashboard tells you where you stand before you ship.

Test everything. /ship bootstraps test frameworks from scratch if your project doesn't have one. Every /ship run produces a coverage audit. Every /qa bug fix generates a regression test. 100% test coverage is the goal — tests make vibe coding safe instead of yolo coding.

/document-release is the engineer you never had. It reads every doc file in your project, cross-references the diff, and updates everything that drifted. README, ARCHITECTURE, CONTRIBUTING, CLAUDE.md, TODOS — all kept current automatically. And now /ship auto-invokes it — docs stay current without an extra command.

Real browser mode. /open-gstack-browser launches GStack Browser, an AI-controlled Chromium with anti-bot stealth, custom branding, and the sidebar extension baked in. Sites like Google and NYTimes work without captchas. The menu bar says "GStack Browser" instead of "Chrome for Testing." Your regular Chrome stays untouched. All existing browse commands work unchanged. $B disconnect returns to headless. The browser stays alive as long as the window is open... no idle timeout killing it while you're working.

Sidebar agent — your AI browser assistant. Type natural language in the Chrome side panel and a child Claude instance executes it. "Navigate to the settings page and screenshot it." "Fill out this form with test data." "Go through every item in this list and extract the prices." The sidebar auto-routes to the right model: Sonnet for fast actions (click, navigate, screenshot) and Opus for reading and analysis. Each task gets up to 5 minutes. The sidebar agent runs in an isolated session, so it won't interfere with your main Claude Code window. One-click cookie import right from the sidebar footer.

Personal automation. The sidebar agent isn't just for dev workflows. Example: "Browse my kid's school parent portal and add all the other parents' names, phone numbers, and photos to my Google Contacts." Two ways to get authenticated: (1) log in once in the headed browser, your session persists, or (2) click the "cookies" button in the sidebar footer to import cookies from your real Chrome. Once authenticated, Claude navigates the directory, extracts the data, and creates the contacts.

Prompt injection defense. Hostile web pages try to hijack your sidebar agent. gstack ships a layered defense: a 22MB ML classifier bundled with the browser scans every page and tool output locally, a Claude Haiku transcript check votes on the full conversation shape, a random canary token in the system prompt catches session exfil attempts across text, tool args, URLs, and file writes, and a verdict combiner requires two classifiers to agree before blocking (prevents single-model false positives on Stack Overflow-style instruction pages). A shield icon in the sidebar header shows status (green/amber/red). Opt in to a 721MB DeBERTa-v3 ensemble via GSTACK_SECURITY_ENSEMBLE=deberta for 2-of-3 agreement. Emergency kill switch: GSTACK_SECURITY_OFF=1. See ARCHITECTURE.md for the full stack.

Browser handoff when the AI gets stuck. Hit a CAPTCHA, auth wall, or MFA prompt? $B handoff opens a visible Chrome at the exact same page with all your cookies and tabs intact. Solve the problem, tell Claude you're done, $B resume picks up right where it left off. The agent even suggests it automatically after 3 consecutive failures.

/pair-agent is cross-agent coordination. You're in Claude Code. You also have OpenClaw running. Or Hermes. Or Codex. You want them both looking at the same website. Type /pair-agent, pick your agent, and a GStack Browser window opens so you can watch. The skill prints a block of instructions. Paste that block into the other agent's chat. It exchanges a one-time setup key for a session token, creates its own tab, and starts browsing. You see both agents working in the same browser, each in their own tab, neither able to interfere with the other. If ngrok is installed, the tunnel starts automatically so the other agent can be on a completely different machine. Same-machine agents get a zero-friction shortcut that writes credentials directly. This is the first time AI agents from different vendors can coordinate through a shared browser with real security: scoped tokens, tab isolation, rate limiting, domain restrictions, and activity attribution.

Multi-AI second opinion. /codex gets an independent review from OpenAI's Codex CLI — a completely different AI looking at the same diff. Three modes: code review with a pass/fail gate, adversarial challenge that actively tries to break your code, and open consultation with session continuity. When both /review (Claude) and /codex (OpenAI) have reviewed the same branch, you get a cross-model analysis showing which findings overlap and which are unique to each.

Safety guardrails on demand. Say "be careful" and /careful warns before any destructive command — rm -rf, DROP TABLE, force-push, git reset --hard. /freeze locks edits to one directory while debugging so Claude can't accidentally "fix" unrelated code. /guard activates both. /investigate auto-freezes to the module being investigated.

Proactive skill suggestions. gstack notices what stage you're in — brainstorming, reviewing, debugging, testing — and suggests the right skill. Don't like it? Say "stop suggesting" and it remembers across sessions.

10-15 parallel sprints

gstack is powerful with one sprint. It is transformative with ten running at once.

Conductor runs multiple Claude Code sessions in parallel — each in its own isolated workspace. One session running /office-hours on a new idea, another doing /review on a PR, a third implementing a feature, a fourth running /qa on staging, and six more on other branches. All at the same time. I regularly run 10-15 parallel sprints — that's the practical max right now.

The sprint structure is what makes parallelism work. Without a process, ten agents is ten sources of chaos. With a process — think, plan, build, review, test, ship — each agent knows exactly what to do and when to stop. You manage them the way a CEO manages a team: check in on the decisions that matter, let the rest run.

Voice input (AquaVoice, Whisper, etc.)

gstack skills have voice-friendly trigger phrases. Say what you want naturally — "run a security check", "test the website", "do an engineering review" — and the right skill activates. You don't need to remember slash command names or acronyms.

Uninstall

Option 1: Run the uninstall script

If gstack is installed on your machine:

~/.claude/skills/gstack/bin/gstack-uninstall

This handles skills, symlinks, global state (~/.gstack/), project-local state, browse daemons, and temp files. Use --keep-state to preserve config and analytics. Use --force to skip confirmation.

Option 2: Manual removal (no local repo)

If you don't have the repo cloned (e.g. you installed via a Claude Code paste and later deleted the clone):

# 1. Stop browse daemons
pkill -f "gstack.*browse" 2>/dev/null || true

# 2. Remove per-skill directories whose SKILL.md points into gstack/
find ~/.claude/skills -mindepth 1 -maxdepth 1 -type d ! -name gstack 2>/dev/null |
while IFS= read -r dir; do
  link="$dir/SKILL.md"
  [ -L "$link" ] || continue
  target=$(readlink "$link" 2>/dev/null) || continue
  case "$target" in
    gstack/*|*/gstack/*)
      rm -f "$link"
      rmdir "$dir" 2>/dev/null || true
      ;;
  esac
done

# 3. Remove gstack
rm -rf ~/.claude/skills/gstack

# 4. Remove global state
rm -rf ~/.gstack

# 5. Remove integrations (skip any you never installed)
rm -rf ~/.codex/skills/gstack* 2>/dev/null
rm -rf ~/.factory/skills/gstack* 2>/dev/null
rm -rf ~/.kiro/skills/gstack* 2>/dev/null
rm -rf ~/.openclaw/skills/gstack* 2>/dev/null

# 6. Remove temp files
rm -f /tmp/gstack-* 2>/dev/null

# 7. Per-project cleanup (run from each project root)
rm -rf .gstack .gstack-worktrees .claude/skills/gstack 2>/dev/null
rm -rf .agents/skills/gstack* .factory/skills/gstack* 2>/dev/null

Clean up CLAUDE.md

The uninstall script does not edit CLAUDE.md. In each project where gstack was added, remove the ## gstack and ## Skill routing sections.

Playwright

~/Library/Caches/ms-playwright/ (macOS) is left in place because other tools may share it. Remove it if nothing else needs it.


Free, MIT licensed, open source. No premium tier, no waitlist.

I open sourced how I build software. You can fork it and make it your own.

We're hiring. Want to ship real products at AI-coding speed and help harden gstack? Come work at YC — ycombinator.com/software Extremely competitive salary and equity. San Francisco, Dogpatch District.

GBrain — persistent knowledge for your coding agent

GBrain is a persistent knowledge base for AI agents — think of it as the memory your agent actually keeps between sessions. GStack gives you a one-command path from zero to "it's running, my agent can call it."

/setup-gbrain

Four paths, pick one:

  • Supabase, existing URL — your cloud agent already provisioned a brain; paste the Session Pooler URL, now this laptop uses the same data.
  • Supabase, auto-provision — paste a Supabase Personal Access Token; the skill creates a new project, polls to healthy, fetches the pooler URL, hands it to gbrain init. ~90 seconds end-to-end.
  • PGLite local — zero accounts, zero network, ~30 seconds. Isolated brain on this Mac only. Great for try-first; migrate to Supabase later with /setup-gbrain --switch.
  • Remote gbrain MCP — your brain runs on another machine (Tailscale, ngrok, internal LAN) or a teammate's server; paste an MCP URL and bearer token. Optionally pair with a local PGLite for symbol-aware code search in split-engine mode. Best for cross-machine memory without standing up a local DB.

After init, the skill offers to register gbrain as an MCP server for Claude Code (claude mcp add gbrain -- gbrain serve) so gbrain search, gbrain put, etc. show up as first-class typed tools — not bash shell-outs.

Keeping the brain current. Run /sync-gbrain from any repo to re-index its code into gbrain (incremental by default, --full for a full reindex, --dry-run to preview). The skill registers the cwd as a federated source via gbrain sources add, runs gbrain sync --strategy code, and writes a ## GBrain Search Guidance block to your project's CLAUDE.md so the agent prefers gbrain search/code-def/code-refs over Grep. The block is removed automatically if the capability check fails — no stale guidance pointing at tools that aren't installed.

Per-remote trust policy. Each repo on your machine gets one of three tiers:

  • read-write — agent can search the brain AND write new pages back from this repo
  • read-only — agent can search but never writes (best for multi-client consultants: search the shared brain, don't contaminate it with Client A's work while in Client B's repo)
  • deny — no gbrain interaction at all

The skill asks once per repo. The decision is sticky across worktrees and branches of the same remote.

GStack memory sync (different feature, same private-repo infra). Optionally pushes your gstack state (learnings, CEO plans, design docs, retros, developer profile) to a private git repo so your memory follows you across machines, with a one-time privacy prompt (everything allowlisted / artifacts only / off) and a defense-in-depth secret scanner that blocks AWS keys, tokens, PEM blocks, and JWTs before they leave your machine.

gstack-brain-init

Running gstack in Conductor? Conductor explicitly strips ANTHROPIC_API_KEY and OPENAI_API_KEY from every workspace's process env, so paid evals and gbrain embeddings won't work out of the box. Set GSTACK_ANTHROPIC_API_KEY and GSTACK_OPENAI_API_KEY in Conductor's workspace env config instead — gstack's TS entry points promote them to canonical names at runtime. Full details and the contributor checklist for adding the import to new entry points: Conductor + GSTACK_* env vars.

Full monty — every scenario, every flag, every bin helper, every troubleshooting step: USING_GBRAIN_WITH_GSTACK.md

Other references: docs/gbrain-sync.md (sync-specific guide) • docs/gbrain-sync-errors.md (error index)

Docs

Doc What it covers
Skill Deep Dives Philosophy, examples, and workflow for every skill (includes Greptile integration)
Builder Ethos Builder philosophy: Boil the Lake, Search Before Building, three layers of knowledge
Using GBrain with GStack Every path, flag, bin helper, and troubleshooting step for /setup-gbrain
GBrain Sync Cross-machine memory setup, privacy modes, troubleshooting
Architecture Design decisions and system internals
Browser Reference Full command reference for /browse
Contributing Dev setup, testing, contributor mode, and dev mode
Changelog What's new in every version

Privacy & Telemetry

gstack includes opt-in usage telemetry to help improve the project. Here's exactly what happens:

  • Default is off. Nothing is sent anywhere unless you explicitly say yes.
  • On first run, gstack asks if you want to share anonymous usage data. You can say no.
  • What's sent (if you opt in): skill name, duration, success/fail, gstack version, OS. That's it.
  • What's never sent: code, file paths, repo names, branch names, prompts, or any user-generated content.
  • Change anytime: gstack-config set telemetry off disables everything instantly.

Data is stored in Supabase (open source Firebase alternative). The schema is in supabase/migrations/ — you can verify exactly what's collected. The Supabase publishable key in the repo is a public key (like a Firebase API key) — row-level security policies deny all direct access. Telemetry flows through validated edge functions that enforce schema checks, event type allowlists, and field length limits.

Local analytics are always available. Run gstack-analytics to see your personal usage dashboard from the local JSONL file — no remote data needed.

Troubleshooting

Skill not showing up? cd ~/.claude/skills/gstack && ./setup

/browse fails? cd ~/.claude/skills/gstack && bun install && bun run build

Stale install? Run /gstack-upgrade — or set auto_upgrade: true in ~/.gstack/config.yaml

Want shorter commands? cd ~/.claude/skills/gstack && ./setup --no-prefix — switches from /gstack-qa to /qa. Your choice is remembered for future upgrades.

Want namespaced commands? cd ~/.claude/skills/gstack && ./setup --prefix — switches from /qa to /gstack-qa. Useful if you run other skill packs alongside gstack.

Codex says "Skipped loading skill(s) due to invalid SKILL.md"? Your Codex skill descriptions are stale. Fix: cd ~/.codex/skills/gstack && git pull && ./setup --host codex — or for repo-local installs: cd "$(readlink -f .agents/skills/gstack)" && git pull && ./setup --host codex

Windows users: gstack works on Windows 11 via Git Bash or WSL. Node.js is required in addition to Bun — Bun has a known bug with Playwright's pipe transport on Windows (bun#4253). The browse server automatically falls back to Node.js. Make sure both bun and node are on your PATH.

On Windows without Developer Mode (MSYS2 / Git Bash), setup falls back to file copies instead of symlinks because ln -snf produces frozen copies that don't refresh on git pull. Re-run cd ~/.claude/skills/gstack && ./setup after every git pull so your skill files match the repo. setup prints a one-line note reminding you. Unix and WSL keep symlinks and don't need the re-run.

Claude says it can't see the skills? Make sure your project's CLAUDE.md has a gstack section. Add this:

## gstack
Use /browse from gstack for all web browsing. Never use mcp__claude-in-chrome__* tools.
Available skills: /office-hours, /plan-ceo-review, /plan-eng-review, /plan-design-review,
/design-consultation, /design-shotgun, /design-html, /review, /ship, /land-and-deploy,
/canary, /benchmark, /browse, /open-gstack-browser, /qa, /qa-only, /design-review,
/setup-browser-cookies, /setup-deploy, /setup-gbrain, /sync-gbrain, /retro, /investigate,
/document-release, /document-generate, /codex, /cso, /autoplan, /pair-agent, /careful, /freeze,
/guard, /unfreeze, /gstack-upgrade, /learn.

License

MIT. Free forever. Go build something.

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