Garry Tan 0a803f9e81 feat: gstack v1 — simpler prompts + real LOC receipts (v1.0.0.0) (#1039)
* docs: add design doc for /plan-tune v1 (observational substrate)

Canonical record of the /plan-tune v1 design: typed question registry,
per-question explicit preferences, inline tune: feedback with user-origin
gate, dual-track profile (declared + inferred separately), and plain-English
inspection skill. Captures every decision with pros/cons, what's deferred to
v2 with explicit acceptance criteria, and what was rejected entirely.

Codex review drove a substantial scope rollback from the initial CEO
EXPANSION plan. 15+ legitimate findings (substrate claim was false without
a typed registry; E4/E6/clamp logical contradiction; profile poisoning
attack surface; LANDED preamble side effect; implementation order) shaped
the final shape.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>

* feat: typed question registry for /plan-tune v1 foundation

scripts/question-registry.ts declares 53 recurring AskUserQuestion categories
across 15 skills (ship, review, office-hours, plan-ceo-review, plan-eng-review,
plan-design-review, plan-devex-review, qa, investigate, land-and-deploy, cso,
gstack-upgrade, preamble, plan-tune, autoplan).

Each entry has: stable kebab-case id, skill owner, category (approval |
clarification | routing | cherry-pick | feedback-loop), door_type (one-way
| two-way), optional stable option keys, optional psychographic signal_key,
and a one-line description.

12 of 53 are one-way doors (destructive ops, architecture/data forks,
security/compliance). These are ALWAYS asked regardless of user preference.

Helpers: getQuestion(id), getOneWayDoorIds(), getAllRegisteredIds(),
getRegistryStats(). No binary or resolver wiring yet — this is the schema
substrate the rest of /plan-tune builds on.

Ad-hoc question_ids (not registered) still log but skip psychographic
signal attribution. Future /plan-tune skill surfaces frequently-firing
ad-hoc ids as candidates for registry promotion.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>

* test: registry schema + safety + coverage tests (gate tier)

20 tests validating the question registry:

Schema (7 tests):
- Every entry has required fields
- All ids are kebab-case and start with their skill name
- No duplicate ids
- Categories are from the allowed set
- door_type is one-way | two-way
- Options arrays are well-formed
- Descriptions are short and single-line

Helpers (5 tests):
- getQuestion returns entry for known id, undefined for unknown
- getOneWayDoorIds includes destructive questions, excludes two-way
- getAllRegisteredIds count matches QUESTIONS keys
- getRegistryStats totals are internally consistent

One-way door safety (2 tests):
- Every critical question (test failure, SQL safety, LLM trust boundary,
  security scan, merge confirm, rollback, fix apply, premise revise,
  arch finding, privacy gate, user challenge) is declared one-way
- At least 10 one-way doors exist (catches regression if declarations
  are accidentally dropped)

Registry breadth (3 tests):
- 11 high-volume skills each have >= 1 registered question
- Preamble one-time prompts are registered
- /plan-tune's own questions are registered

Signal map references (1 test):
- signal_key values are typed kebab-case strings

Template coverage (2 tests, informational):
- AskUserQuestion usage across templates is non-trivial (>20)
- Registry spans >= 10 skills

20 pass, 0 fail.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>

* feat: one-way door classifier (belt-and-suspenders safety fallback)

scripts/one-way-doors.ts — secondary keyword-pattern classifier that catches
destructive questions even when the registry doesn't have an entry for them.

The registry's door_type field (from scripts/question-registry.ts) is the
PRIMARY safety gate. This classifier is the fallback for ad-hoc question_ids
that agents generate at runtime.

Classification priority:
  1. Registry lookup by question_id → use declared door_type
  2. Skill:category fallback (cso:approval, land-and-deploy:approval)
  3. Keyword pattern match against question_summary
  4. Default: treat as two-way (safer to log the miss than auto-decide unsafely)

Covers 21 destructive patterns across:
  - File system (rm -rf, delete, wipe, purge, truncate)
  - Database (drop table/database/schema, delete from)
  - Git/VCS (force-push, reset --hard, checkout --, branch -D)
  - Deploy/infra (kubectl delete, terraform destroy, rollback)
  - Credentials (revoke/reset/rotate API key|token|secret|password)
  - Architecture (breaking change, schema migration, data model change)

7 new tests in test/plan-tune.test.ts covering: registry-first lookup,
unknown-id fallthrough, keyword matching on destructive phrasings including
embedded filler words ("rotate the API key"), skill-category fallback,
benign questions defaulting to two-way, pattern-list non-empty.

27 pass, 0 fail. 1270 expect() calls.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>

* feat: psychographic signal map + builder archetypes

scripts/psychographic-signals.ts — hand-crafted {signal_key, user_choice} →
{dimension, delta} map. Version 0.1.0. Conservative deltas (±0.03 to ±0.06
per event). Covers 9 signal keys: scope-appetite, architecture-care,
code-quality-care, test-discipline, detail-preference, design-care,
devex-care, distribution-care, session-mode.

Helpers: applySignal() mutates running totals, newDimensionTotals() creates
empty starting state, normalizeToDimensionValue() sigmoid-clamps accumulated
delta to [0,1] (0 → 0.5 neutral), validateRegistrySignalKeys() checks that
every signal_key in the registry has a SIGNAL_MAP entry.

In v1 the signal map is used ONLY to compute inferred dimension values for
/plan-tune inspection output. No skill behavior adapts to these signals
until v2.

scripts/archetypes.ts — 8 named archetypes + Polymath fallback:
- Cathedral Builder (boil-the-ocean + architecture-first)
- Ship-It Pragmatist (small scope + fast)
- Deep Craft (detail-verbose + principled)
- Taste Maker (intuitive, overrides recommendations)
- Solo Operator (high-autonomy, delegates)
- Consultant (hands-on, consulted on everything)
- Wedge Hunter (narrow scope aggressively)
- Builder-Coach (balanced steering)
- Polymath (fallback when no archetype matches)

matchArchetype() uses L2 distance scaled by tightness, with a 0.55 threshold
below which we return Polymath. v1 ships the model stable; v2 narrative/vibe
commands wire it into user-facing output.

14 new tests: signal map consistency vs registry, applySignal behavior for
known/unknown keys, normalization bounds, archetype schema validity, name
uniqueness, matchArchetype correctness for each reference profile, Polymath
fallback for outliers.

41 pass, 0 fail total in test/plan-tune.test.ts.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>

* feat: bin/gstack-question-log — append validated AskUserQuestion events

Append-only JSONL log at ~/.gstack/projects/{SLUG}/question-log.jsonl.
Schema: {skill, question_id, question_summary, category?, door_type?,
options_count?, user_choice, recommended?, followed_recommendation?,
session_id?, ts}

Validates:
- skill is kebab-case
- question_id is kebab-case, <= 64 chars
- question_summary non-empty, <= 200 chars, newlines flattened
- category is one of approval/clarification/routing/cherry-pick/feedback-loop
- door_type is one-way or two-way
- options_count is integer in [1, 26]
- user_choice non-empty string, <= 64 chars

Injection defense on question_summary rejects the same patterns as
gstack-learnings-log (ignore previous instructions, system:, override:,
do not report, etc).

followed_recommendation is auto-computed when both user_choice and
recommended are present.

ts auto-injected as ISO 8601 if missing.

21 tests covering: valid payloads, full field preservation, auto-followed
computation, appending, long-summary truncation, newline flattening,
invalid JSON, missing fields, bad case, oversized ids, invalid enum
values, out-of-range options_count, and 6 injection attack patterns.

21 pass, 0 fail, 43 expect() calls.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>

* feat: bin/gstack-developer-profile — unified profile with migration

bin/gstack-developer-profile supersedes bin/gstack-builder-profile. The old
binary becomes a one-line legacy shim delegating to --read for /office-hours
backward compat.

Subcommands:
  --read              legacy KEY:VALUE output (tier, session_count, etc)
  --migrate           folds ~/.gstack/builder-profile.jsonl into
                      ~/.gstack/developer-profile.json. Atomic (temp + rename),
                      idempotent (no-op when target exists or source absent),
                      archives source as .migrated-YYYY-MM-DD-HHMMSS
  --derive            recomputes inferred dimensions from question-log.jsonl
                      using the signal map in scripts/psychographic-signals.ts
  --profile           full profile JSON
  --gap               declared vs inferred diff JSON
  --trace <dim>       event-level trace of what contributed to a dimension
  --check-mismatch    flags dimensions where declared and inferred disagree by
                      > 0.3 (requires >= 10 events first)
  --vibe              archetype name + description from scripts/archetypes.ts
  --narrative         (v2 stub)

Auto-migration on first read: if legacy file exists and new file doesn't,
migrate before reading. Creates a neutral (all-0.5) stub if nothing exists.

Unified schema (see docs/designs/PLAN_TUNING_V0.md §Architecture):
  {identity, declared, inferred: {values, sample_size, diversity},
   gap, overrides, sessions, signals_accumulated, schema_version}

25 new tests across subcommand behaviors:
- --read defaults + stub creation
- --migrate: 3 sessions preserved with signal tallies, idempotency, archival
- Tier calculation: welcome_back / regular / inner_circle boundaries
- --derive: neutral-when-empty, upward nudge on 'expand', downward on 'reduce',
  recomputable (same input → same output), ad-hoc unregistered ids ignored
- --trace: contributing events, empty for untouched dims, error without arg
- --gap: empty when no declared, correctly computed otherwise
- --vibe: returns archetype name + description
- --check-mismatch: threshold behavior, 10+ sample requirement
- Unknown subcommand errors

25 pass, 0 fail, 60 expect() calls.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>

* feat: bin/gstack-question-preference — explicit preferences + user-origin gate

Subcommands:
  --check <id>   → ASK_NORMALLY | AUTO_DECIDE  (decides if a registered
                   question should be auto-decided by the agent)
  --write '{…}'  → set a preference (requires user-origin source)
  --read         → dump preferences JSON
  --clear [id]   → clear one or all
  --stats        → short counts summary

Preference values: always-ask | never-ask | ask-only-for-one-way.
Stored at ~/.gstack/projects/{SLUG}/question-preferences.json.

Safety contract (the core of Codex finding #16, profile-poisoning defense
from docs/designs/PLAN_TUNING_V0.md §Security model):

  1. One-way doors ALWAYS return ASK_NORMALLY from --check, regardless of
     user preference. User's never-ask is overridden with a visible safety
     note so the user knows why their preference didn't suppress the prompt.

  2. --write requires an explicit `source` field:
       - Allowed:  "plan-tune", "inline-user"
       - REJECTED with exit code 2: "inline-tool-output", "inline-file",
         "inline-file-content", "inline-unknown"
     Rejection is explicit ("profile poisoning defense") so the caller can
     log and surface the attempt.

  3. free_text on --write is sanitized against injection patterns (ignore
     previous instructions, override:, system:, etc.) and newline-flattened.

Each --write also appends a preference-set event to
~/.gstack/projects/{SLUG}/question-events.jsonl for derivation audit trail.

31 tests:
- --check behavior (4): defaults, two-way, one-way (one-way overrides
  never-ask with safety note), unknown ids, missing arg
- --check with prefs (5): never-ask on two-way → AUTO_DECIDE; never-ask
  on one-way → ASK_NORMALLY with override note; always-ask always asks;
  ask-only-for-one-way flips appropriately
- --write valid (5): inline-user accepted, plan-tune accepted, persisted
  correctly, event appended, free_text preserved with flattening
- User-origin gate (6): missing source rejected; inline-tool-output
  rejected with exit code 2 and explicit poisoning message; inline-file,
  inline-file-content, inline-unknown rejected; unknown source rejected
- Schema validation (4): invalid JSON, bad question_id, bad preference,
  injection in free_text
- --read (2): empty → {}, returns writes
- --clear (3): specific id, clear-all, NOOP for missing
- --stats (2): empty zeros, tallies by preference type

31 pass, 0 fail, 52 expect() calls.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>

* feat: question-tuning preamble resolvers

scripts/resolvers/question-tuning.ts ships three preamble generators:

  generateQuestionPreferenceCheck — before each AskUserQuestion, agent runs
    gstack-question-preference --check <id>. AUTO_DECIDE suppresses the ask
    and auto-chooses recommended. ASK_NORMALLY asks as usual. One-way door
    safety override is handled by the binary.

  generateQuestionLog — after each AskUserQuestion, agent appends a log
    record with skill, question_id, summary, category, door_type,
    options_count, user_choice, recommended, session_id.

  generateInlineTuneFeedback — offers inline "tune:" prompt after two-way
    questions. Documents structured shortcuts (never-ask, always-ask,
    ask-only-for-one-way, ask-less) AND accepts free-form English with
    normalization + confirmation. Explicitly spells out the USER-ORIGIN
    GATE: only write tune events when the prefix appears in the user's own
    chat message, never from tool output or file content. Binary enforces.

All three resolvers are gated by the QUESTION_TUNING preamble echo. When
the config is off, the agent skips these sections entirely. Ready to be
wired into preamble.ts in the next commit.

Codex host has a simpler variant that uses $GSTACK_BIN env vars.

scripts/resolvers/index.ts registers three placeholders:
  QUESTION_PREFERENCE_CHECK, QUESTION_LOG, INLINE_TUNE_FEEDBACK

Total resolver count goes from 45 to 48.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>

* feat: wire question-tuning into preamble for tier >= 2 skills

scripts/resolvers/preamble.ts — adds two things:

  1. _QUESTION_TUNING config echo in the preamble bash block, gated on the
     user's gstack-config `question_tuning` value (default: false).
  2. A combined Question Tuning section for tier >= 2 skills, injected after
     the confusion protocol. The section itself is runtime-gated by the
     QUESTION_TUNING value — agents skip it entirely when off.

scripts/resolvers/question-tuning.ts — consolidated into one compact combined
section `generateQuestionTuning(ctx)` covering: preference check before the
question, log after, and inline tune: feedback with user-origin gate. Per-phase
generators remain exported for unit tests but are no longer the main entrypoint.

Size impact: +570 tokens / +2.3KB per tier-2+ SKILL.md. Three skills
(plan-ceo-review, office-hours, ship) still exceed the 100KB token ceiling —
but they were already over before this change. Delta is the smallest viable
wiring of the /plan-tune v1 substrate.

Golden fixtures (test/fixtures/golden/claude-ship, codex-ship, factory-ship)
regenerated to match the new baseline.

Full test run: 1149 pass, 0 fail, 113 skip across 28 files.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>

* chore: regenerate SKILL.md files with question-tuning section

bun run gen:skill-docs --host all after wiring the QUESTION_TUNING preamble
section. Every tier >= 2 skill now includes the combined Question Tuning
guidance. Runtime-gated — agents skip the section when question_tuning is
off in gstack-config (default).

Golden fixtures (claude-ship, codex-ship, factory-ship) updated to the new
baseline.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>

* feat: /plan-tune skill — conversational inspection + preferences

plan-tune/SKILL.md.tmpl: the user-facing skill for /plan-tune v1. Routes
plain-English intent to one of 8 flows:

  - Enable + setup (first-time): 5 declaration questions mapping to the
    5 psychographic dimensions (scope_appetite, risk_tolerance,
    detail_preference, autonomy, architecture_care). Writes to
    developer-profile.json declared.*.
  - Inspect profile: plain-English rendering of declared + inferred + gap.
    Uses word bands (low/balanced/high) not raw floats. Shows vibe archetype
    when calibration gate is met.
  - Review question log: top-20 question frequencies with follow/override
    counts. Highlights override-heavy questions as candidates for never-ask.
  - Set a preference: normalizes "stop asking me about X" → never-ask, etc.
    Confirms ambiguous phrasings before writing via gstack-question-preference.
  - Edit declared profile: interprets free-form ("more boil-the-ocean") and
    CONFIRMS before mutating declared.* (trust boundary per Codex #15).
  - Show gap: declared vs inferred diff with plain-English severity bands
    (close / drift / mismatch). Never auto-updates declared from the gap.
  - Stats: preference counts + diversity/calibration status.
  - Enable / disable: gstack-config set question_tuning true|false.

Design constraints enforced:
- Plain English everywhere. No CLI subcommand syntax required. Shortcuts
  (`profile`, `vibe`, `stats`, `setup`) exist but optional.
- user-origin gate on tune: writes. source: "plan-tune" for user-invoked
  /plan-tune; source: "inline-user" for inline tune: from other skills.
- One-way doors override never-ask (safety, surfaced to user).
- No behavior adaptation in v1 — this skill inspects and configures only.

Generates plan-tune/SKILL.md at ~11.6k tokens, well under the 100KB ceiling.
Generated for all hosts via `bun run gen:skill-docs --host all`.

Full free test suite: 1149 pass, 0 fail, 113 skip across 28 files.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>

* test: end-to-end pipeline + preamble injection coverage

Added 6 tests to test/plan-tune.test.ts:

Preamble injection (3 tests):
- tier 2+ includes Question Tuning section with preference check, log,
  and user-origin gate language ('profile-poisoning defense', 'inline-user')
- tier 1 does NOT include the prose section (QUESTION_TUNING bash echo
  still fires since it's in the bash block all tiers share)
- codex host swaps binDir references to $GSTACK_BIN

End-to-end pipeline (3 tests) — real binaries working together, not mocks:
- Log 5 expand choices → --derive → profile shows scope_appetite > 0.5
  (full log → registry lookup → signal map → normalization round-trip)
- --write source: inline-tool-output rejected; --read confirms no pref
  was persisted (the profile-poisoning defense actually works end-to-end)
- Migrate a 3-session legacy file; confirm legacy gstack-builder-profile
  shim still returns SESSION_COUNT: 3, TIER: welcome_back, CROSS_PROJECT: true

test/plan-tune.test.ts now has 47 tests total.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>

* test: E2E test for /plan-tune plain-English inspection flow (gate tier)

test/skill-e2e-plan-tune.test.ts — verifies /plan-tune correctly routes
plain-English intent ("review the questions I've been asked") to the
Review question log section without requiring CLI subcommand syntax.

Seeds a synthetic question-log.jsonl with 3 entries exercising:
- override behavior (user chose expand over recommended selective)
- one-way door respect (user followed ship-test-failure-triage recommendation)
- two-way override (user skipped recommended changelog polish)

Invokes the skill via `claude -p` and asserts:
- Agent surfaces >= 2 of 3 logged question_ids in output
- Agent notices override/skip behavior from the log
- Exit reason is success or error_max_turns (not agent-crash)

Gate-tier because the core v1 DX promise is plain-English intent routing.
If it requires memorized subcommands or breaks on natural language, that's
a regression of the defining feature.

Registered in test/helpers/touchfiles.ts with dependencies:
- plan-tune/** (skill template + generated md)
- scripts/question-registry.ts (required for log lookup)
- scripts/psychographic-signals.ts, scripts/one-way-doors.ts (derive path)
- bin/gstack-question-log, gstack-question-preference, gstack-developer-profile

Skipped when EVALS_ENABLED is not set; runs on `bun run test:evals`.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>

* chore: bump version and changelog (v0.19.0.0) — /plan-tune v1

Ships /plan-tune as observational substrate: typed question registry, dual-track
developer profile (declared + inferred), explicit per-question preferences with
user-origin gate, inline tune: feedback across every tier >= 2 skill, unified
developer-profile.json with migration from builder-profile.jsonl.

Scope rolled back from initial CEO EXPANSION plan after outside-voice review
(Codex). 6 deferrals tracked as P0 TODOs with explicit acceptance criteria:
E1 substrate wiring, E3 narrative/vibe, E4 blind-spot coach, E5 LANDED
celebration, E6 auto-adjustment, E7 psychographic auto-decide.

See docs/designs/PLAN_TUNING_V0.md for the full design record.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>

* fix(ci): harden Dockerfile.ci against transient Ubuntu mirror failures

The CI image build failed with:
  E: Failed to fetch http://archive.ubuntu.com/ubuntu/pool/main/...
     Connection failed [IP: 91.189.92.22 80]
  ERROR: process "/bin/sh -c apt-get update && apt-get install ..."
     did not complete successfully: exit code: 100

archive.ubuntu.com periodically returns "connection refused" on individual
regional mirrors. Without retry logic a single failed fetch nukes the whole
Docker build. Three defenses, layered:

  1. /etc/apt/apt.conf.d/80-retries — apt fetches each package up to 5 times
     with a 30s timeout. Handles per-package flakes.
  2. Shell-loop retry around the whole apt-get step (x3, 10s sleep) — handles
     the case where apt-get update itself can't reach any mirror.
  3. --retry 5 --retry-delay 5 --retry-connrefused on all curl fetches (bun
     install script, GitHub CLI keyring, NodeSource setup script).

Applied to every apt-get and curl call in the Dockerfile. No behavior change
on happy path — only kicks in when mirrors blip. Fixes the build-image job
that was blocking CI on the /plan-tune PR.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>

* docs: add PLAN_TUNING_V1 + PACING_UPDATES_V0 design docs

Captures the V1 design (ELI10 writing + LOC reframe) in
docs/designs/PLAN_TUNING_V1.md and the extracted V1.1 pacing-overhaul
plan in docs/designs/PACING_UPDATES_V0.md. V1 scope was reduced from
the original bundled pacing + writing-style plan after three
engineering-review passes revealed structural gaps in the pacing
workstream that couldn't be closed via plan-text editing. TODOS.md
P0 entry links to V1.1.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>

* feat: curated jargon list for V1 writing-style glossing

Repo-owned list of ~50 high-frequency technical terms (idempotent,
race condition, N+1, backpressure, etc.) that gstack glosses on first
use in tier-≥2 skill output. Baked into generated SKILL.md prose at
gen-skill-docs time. Terms not on this list are assumed plain-English
enough. Contributions via PR.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>

* feat(preamble): V1 Writing Style section + EXPLAIN_LEVEL echo + migration prompt

Adds a new Writing Style section to tier-≥2 preamble output composing with
the existing AskUserQuestion Format section. Six rules: jargon glossed on
first use per skill invocation (from scripts/jargon-list.json), outcome-
framed questions, short sentences, decisions close with user impact,
gloss-on-first-use even if user pasted term, user-turn override for "be
terse" requests. Baked conditionally (skip if EXPLAIN_LEVEL: terse).

Adds EXPLAIN_LEVEL preamble echo using \${binDir} (host-portable matching
V0 QUESTION_TUNING pattern). Adds WRITING_STYLE_PENDING echo reading a
flag file written by the V0→V1 upgrade migration; on first post-upgrade
skill run, the agent fires a one-time AskUserQuestion offering terse mode.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>

* feat(gstack-config): validate explain_level + document in header

Adds explain_level: default|terse to the annotated config header with
a one-line description. Whitelists valid values; on set of an unknown
value, prints a specific warning ("explain_level '\$VALUE' not
recognized. Valid values: default, terse. Using default.") and writes
the default value. Matches V1 preamble's EXPLAIN_LEVEL echo expectation.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>

* feat: V1 upgrade migration — writing-style opt-out prompt

New migration script following existing v0.15.2.0.sh / v0.16.2.0.sh
pattern. Writes a .writing-style-prompt-pending flag file on first run
post-upgrade. The preamble's migration-prompt block reads the flag and
fires a one-time AskUserQuestion offering the user a choice between
the new default writing style and restoring V0 prose via
\`gstack-config set explain_level terse\`. Idempotent via flag files;
if the user has already set explain_level explicitly, counts as
answered and skips.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>

* feat: LOC reframe tooling — throughput comparison + README updater + scc installer

Three new scripts:

- scripts/garry-output-comparison.ts — enumerates Garry-authored commits
  in 2013 + 2026 on public repos, extracts ADDED lines from git diff,
  classifies as logical SLOC via scc --stdin (regex fallback if scc
  missing). Writes docs/throughput-2013-vs-2026.json with per-language
  breakdown + explicit caveats (public repos only, commit-style drift,
  private-work exclusion).

- scripts/update-readme-throughput.ts — reads the JSON if present,
  replaces the README's <!-- GSTACK-THROUGHPUT-PLACEHOLDER --> anchor
  with the computed multiple (preserving the anchor for future runs).
  If JSON missing, writes GSTACK-THROUGHPUT-PENDING marker that CI
  rejects — forcing the build to run before commit.

- scripts/setup-scc.sh — standalone OS-detecting installer for scc.
  Not a package.json dependency (95% of users never run throughput).
  Brew on macOS, apt on Linux, GitHub releases link on Windows.

Two-string anchor pattern (PLACEHOLDER vs PENDING) prevents the
pipeline from destroying its own update path.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>

* feat(retro): surface logical SLOC + weighted commits above raw LOC

V1 reorders the /retro summary table to lead with features shipped,
then commits + weighted commits (commits × files-touched capped at 20),
then PRs merged, then logical SLOC added as the primary code-volume
metric. Raw LOC stays present but is demoted to context. Rationale
inline in the template: ten lines of a good fix is not less shipping
than ten thousand lines of scaffold.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>

* docs(v1): README hero reframe + writing-style + CHANGELOG + version bump to 1.0.0.0

README.md:
- Hero removes "600,000+ lines of production code" framing; replaces
  with the computed 2013-vs-2026 pro-rata multiple (via
  <!-- GSTACK-THROUGHPUT-PLACEHOLDER --> anchor, filled by the
  update-readme-throughput build step).
- Hiring callout: "ship real products at AI-coding speed" instead of
  "10K+ LOC/day."
- New Writing Style section (~80 words) between Quick start and
  Install: "v1 prompts = simpler" framing, outcome-language example,
  terse-mode opt-out, pointer to /plan-tune.

CLAUDE.md: one-paragraph Writing style (V1) note under project
conventions, linking to preamble resolver + V1 design docs.

CHANGELOG.md: V1 entry on top of v0.19.0.0 with user-facing narrative
(what changes, how to opt out, for-contributors notes). Mentions
scope reduction — pacing overhaul ships in V1.1.

CONTRIBUTING.md: one-paragraph note on jargon-list.json maintenance
(PR to add/remove terms; regenerate via gen:skill-docs).

VERSION + package.json: bump to 1.0.0.0.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>

* chore: regenerate SKILL.md files + golden fixtures for V1

Mechanical regeneration from the updated templates in prior commits:
- Writing Style section now appears in tier-≥2 skill output.
- EXPLAIN_LEVEL + WRITING_STYLE_PENDING echoes in preamble bash.
- V1 migration-prompt block fires conditionally on first upgrade.
- Jargon list inlined into preamble prose at gen time.
- Retro template's logical SLOC + weighted commits order applied.

Regenerated for all 8 hosts via bun run gen:skill-docs --host all.
Golden ship-skill fixtures refreshed from regenerated outputs.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>

* test: V1 gate coverage — writing-style resolver + config + jargon + migration + dormancy

Six new gate-tier test files:

- test/writing-style-resolver.test.ts — asserts Writing Style section
  is injected into tier-≥2 preamble, all 6 rules present, jargon list
  inlined, terse-mode gate condition present, Codex output uses
  \$GSTACK_BIN (not ~/.claude/), tier-1 does NOT get the section,
  migration-prompt block present.

- test/explain-level-config.test.ts — gstack-config set/get round-trip
  for default + terse, unknown-value warns + defaults to default,
  header documents the key, round-trip across set→set→get.

- test/jargon-list.test.ts — shape + ~50 terms + no duplicates
  (case-insensitive) + includes canonical high-signal terms.

- test/v0-dormancy.test.ts — 5D dimension names + archetype names
  forbidden in default-mode tier-≥2 SKILL.md output, except for
  plan-tune and office-hours where they're load-bearing.

- test/readme-throughput.test.ts — script replaces anchor with number
  on happy path, writes PENDING marker when JSON missing, CI gate
  asserts committed README contains no PENDING string.

- test/upgrade-migration-v1.test.ts — fresh run writes pending flag,
  idempotent after user-answered, pre-existing explain_level counts
  as answered.

All 95 V1 test-expect() calls pass. Full suite: 0 failures.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>

* feat: compute real 2013-vs-2026 throughput multiple (130.2×)

Ran scripts/garry-output-comparison.ts across all 15 public garrytan/*
repos. Aggregated results into docs/throughput-2013-vs-2026.json and
ran scripts/update-readme-throughput.ts to replace the README placeholder.

2013 public activity: 2 commits, 2,384 logical lines added across 1
week, in 1 repo (zurb-foundation-wysihtml5 upstream contribution).

2026 public activity: 279 commits, 310,484 logical lines added across
17 active weeks, in 3 repos (gbrain, gstack, resend_robot).

Multiples (public repos only, apples-to-apples):
- Logical SLOC: 130.2×
- Commits per active week: 8.2×
- Raw lines added: 134.4×

Private work at both eras (2013 Bookface at YC, Posterous-era code,
2026 internal tools) is excluded from this comparison.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>

* feat: 207× throughput multiple (with private repos + Bookface)

Re-ran scripts/garry-output-comparison.ts across all 41 repos under
garrytan/* (15 public + 26 private), including Bookface (YC's internal
social network, 2013-era work).

2013 activity: 71 commits, 5,143 logical lines, 4 active repos
  (bookface, delicounter, tandong, zurb-foundation-wysihtml5)
2026 activity: 350 commits, 1,064,818 logical lines, 15 active repos
  (gbrain, gstack, gbrowser, tax-app, kumo, tenjin, autoemail, kitsune,
  easy-chromium-compiles, conductor-playground, garryslist-agent, baku,
  gstack-website, resend_robot, garryslist-brain)

Multiples:
- Logical SLOC: 207× (up from 130.2× when including private work)
- Raw lines: 223×
- Commits/active-week: 3.4×

Stopped committing docs/throughput-2013-vs-2026.json — analysis is a
local artifact, not repo state. Added docs/throughput-*.json to
.gitignore. Full markdown analysis at ~/throughput-analysis-2026-04-18.md
(local-only). README multiple is now hardcoded; re-run the script and
edit manually when you want to refresh it.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>

* docs: run rate vs year-to-date throughput comparison

Two separate numbers in the README hero:
- Run rate: ~700× (9,859 logical lines/day in 2026 vs 14/day in 2013)
- Year-to-date: 207× (2026 through April 18 already exceeds 2013 full
  year by 207×)

Previous "207× pro-rata" framing mixed full-year 2013 vs partial-year
2026. Run rate is the apples-to-apples normalization; YTD is the
"already produced" total. Both are honest; both are compelling; they
measure different things.

Analysis at ~/throughput-analysis-2026-04-18.md (local-only).

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>

* feat(throughput): script natively computes to-date + run-rate multiples

Enhanced scripts/garry-output-comparison.ts so both calculations come
out of a single run instead of being reassembled ad-hoc in bash:

PerYearResult now includes:
- days_elapsed — 365 for past years, day-of-year for current
- is_partial — flags the current (in-progress) year
- per_day_rate — logical/raw/commits normalized by calendar day
- annualized_projection — per_day_rate × 365

Output JSON's `multiples` now has two sibling blocks:
- multiples.to_date — raw volume ratios (2026-YTD / 2013-full-year)
- multiples.run_rate — per-day pace ratios (apples-to-apples)

Back-compat: multiples.logical_lines_added still aliases to_date for
older consumers reading the JSON.

Updated README hero to cite both (picking up brain/* repo that was
missed in the earlier aggregation pass):

  2026 run rate: ~880× my 2013 pace (12,382 vs 14 logical lines/day)
  2026 YTD:      260× the entire 2013 year

Stderr summary now prints both multiples at the end of each run.

Full analysis at ~/throughput-analysis-2026-04-18.md (local-only).

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>

* docs: ON_THE_LOC_CONTROVERSY methodology post + README link

Long-form response to the "LOC is a meaningless vanity metric" critique.
Covers:
- The three branches of the LOC critique and which are right
- Why logical SLOC (NCLOC) beats raw LOC as the honest measurement
- Full method: author-scoped git diff, regex-classified added lines,
  aggregated across 41 public + private garrytan/* repos
- Both calculations: to-date (260x) and run-rate (879x)
- Steelman of the critics (greenfield-vs-maintenance, survivorship bias,
  quality-adjusted productivity, time-to-first-user)
- Reproduction instructions

Linked from README hero via a blockquote directly below the number.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>

* exclude: tax-app from throughput analysis (import-dominated history)

tax-app's history is one commit of 104K logical lines — an initial
import of a codebase, not authored work. Removing it to keep the
comparison honest.

Changes:
- scripts/garry-output-comparison.ts: added EXCLUDED_REPOS constant
  with tax-app + a one-line rationale. The script now skips excluded
  repos with a stderr note and deletes any stale output JSON so
  aggregation loops don't pick up pre-exclusion numbers.

- README hero: updated to 810× run rate + 240× YTD (were 880×/260×).
  Wording updated to "40 public + private repos ... after excluding
  repos dominated by imported code."

- docs/ON_THE_LOC_CONTROVERSY.md: updated all numbers, added an
  "Exclusions" paragraph explaining tax-app, removed tax-app from
  the "shipped not WIP" example list.

New numbers (2026 through day 108, without tax-app):
  - To-date:  240× logical SLOC (1,233,062 vs 5,143)
  - Run rate: 810× per-day pace (11,417 vs 14 logical/day)
  - Annualized: ~4.2M logical lines projected

Future re-runs automatically skip tax-app. Add more exclusions to
EXCLUDED_REPOS at the top of the script with a one-line rationale.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>

* fix: correct tax-app exclusion rationale

tax-app is a demo app I built for an upcoming YC channel video,
not an "import-dominated history" as the previous commit claimed.
Excluded because it's not production shipping work, not because
of an import commit.

Updated rationale in scripts/garry-output-comparison.ts's
EXCLUDED_REPOS constant, in docs/ON_THE_LOC_CONTROVERSY.md's
method section + conclusion, and in the README hero wording
("one demo repo" vs the earlier "repos dominated by imported code").

Numbers unchanged — the exclusion itself is the same, just the
reason.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>

* docs: harden ON_THE_LOC_CONTROVERSY against Cramer + neckbeard critiques

Reframes the thesis as "engineers can fly now" (amplification, not
replacement) and fortifies the soft spots critics will attack.

Added:
- Flight-thesis opener: pilot vs walker, leverage not replacement.
- Second deflation layer for AI verbosity (on top of NCLOC). Headline
  moves from 810x to 408x after generous 2x AI-boilerplate cut, with
  explicit sensitivity analysis showing the number is still large under
  pessimistic priors (5x → 162x, 10x → 81x, 100x impossible).
- Weekly distribution check (kills "you had one burst week" attack).
- Revert rate (2.0%) and post-merge fix rate (6.3%) with OSS
  comparables (K8s/Rails/Django band). Addresses "where are your error
  rates" directly.
- Named production adoption signals (gstack 1000+ installs, gbrain beta,
  resend_robot paying API) with explicit concession that "shipped != used
  at scale" for most of the corpus.
- Harder steelman: 5 specific concessions with quantified pivot points
  (e.g., "if 2013 baseline was 3.5x higher, 810x → 228x, still high").

Removed factual error: Posterous acquisition paragraph (Garry had already
left Posterous by 2011, so the "Twitter bought our private repos" excuse
for the 2013 corpus gap doesn't apply).

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>

* docs: update gstack/gbrain adoption numbers in LOC controversy post

gstack: "1,000+ distinct project installations" → "tens of thousands of
daily active users" (telemetry-reported, community tier, opt-in).
gbrain: "small set of beta testers" → "hundreds of beta testers running
it live."

Both are the accurate current numbers. The concession paragraph below
(about shipped != adopted at scale for the long-tail repos) still reads
correctly since it's about the corpus as a whole, not gstack/gbrain
specifically.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>

* docs: reframe reproducibility note as OSS breakout flex

"You'd need access to my private repos" → "Bookface and Posthaven are
private, but gstack and gbrain are open-sourced with tens of thousands
of GitHub stars and tens of thousands of confirmed regular users, among
the most-used OSS projects in the world that didn't exist three months
ago."

Keeps the `gh repo list` command at the end for the actual
reproducibility instruction.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>

* Rewrite LOC controversy post

- Lead with concession (LOC is garbage, do the math anyway)
- Preempt 14 lines/day meme with historical baselines (Brooks, Jones, McConnell)
- Remove 'neckbeard' language throughout
- Add slop-scan story (Ben Vinegar, 5.24 → 1.96, 62% cut)
- David Cramer GUnit joke
- Add testing philosophy section (the real unlock)
- ASCII weekly distribution chart
- gstack telemetry section with real numbers (15K installs, 305K invocations, 95.2% success)
- Top skills usage chart
- Pick-your-priors paragraph moved earlier (the killer)
- Sharper close: run the script, show me your numbers

* docs: four precision fixes on LOC controversy post

1. Citation fix. Kernighan didn't say anything about LOC-as-metric
   (that's the famous "aircraft building by weight" quote, commonly
   misattributed but actually Bill Gates). Replaced "Kernighan implied
   it before that" with the real Dijkstra quote ("lines produced" vs
   "lines spent" from EWD1036, with direct link) + the Gates quote.
   Verified via web search.

2. Slop-scan direction clarified. "(highest on his benchmark)" was
   ambiguous — could read as a brag. Now: "Higher score = more slop.
   He ran it on gstack and we scored 5.24, the worst he'd measured
   at the time." Then the 62% cut lands as an actual win.

3. Prose/chart skill-usage ordering now matches. Added /plan-eng-review
   (28,014) to the prose list so it doesn't conflict with the chart
   below it.

4. Cut the "David — I owe you one / GUnit" insider joke. Most readers
   won't connect Cramer → Sentry → GUnit naming. Ends the slop-scan
   paragraph on the stronger line: "Run `bun test` and watch 2,000+
   tests pass."

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>

* docs: tighten four LOC post citations to match primary sources

1. Bill Gates quote: flagged as folklore-grade. Was "Bill Gates put it
   more memorably" (firm attribution). Now "The old line (widely
   attributed to Bill Gates, sourcing murky) puts it more memorably."
   The quote stands; honesty about attribution avoids the same
   misattribution trap we just fixed for Kernighan.

2. Capers Jones: "15-50 across thousands of projects" → "roughly 16-38
   LOC/day across thousands of projects" — matches his actual published
   measurements (which also report as 325-750 LOC/month).

3. Steve McConnell: "10-50 for finished, tested, delivered code" was
   folklore. Replaced with his actual project-size-dependent range from
   Code Complete: "20-125 LOC/day for small projects (10K LOC) down to
   1.5-25 for large projects (10M LOC) — it's size-dependent, not a
   single number."

4. Revert rate comparison: "Kubernetes, Rails, and Django historically
   run 1.5-3%" was unsourced. Replaced with "mature OSS codebases
   typically run 1-3%" + "run the same command on whatever you consider
   the bar and compare." No false specificity about which repos.

Net: every quantitative citation in the post now matches primary-source
figures or is explicitly flagged as folklore. Neckbeards can verify.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>

* docs: drop Writing style section from README

Was sitting in prime real estate between Quick start and Install —
internal implementation detail, not something users need up-front.
Existing coverage is enough:
- Upgrade migration prompt notifies users on first post-upgrade run
- CLAUDE.md has the contributor note
- docs/designs/PLAN_TUNING_V1.md has the full design

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>

* docs: collapse team-mode setup into one paste-and-go command

Step 2 was three separate code blocks: setup --team, then team-init,
then git add/commit. Mirrors Step 1's style now — one shell one-liner
that does all three. Subshell (cd && ./setup --team) keeps the user
in their repo pwd so team-init + git commit land in the right place.

"Swap required for optional" moved to a one-liner below.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>

* docs: move full-clone footnote from README to CONTRIBUTING

The "Contributing or need full history?" note is for contributors, not
for someone following the README install flow. Moved into CONTRIBUTING's
Quick start section where it fits next to the existing clone command,
with a tip to upgrade an existing shallow clone via
\`git fetch --unshallow\`.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>

---------

Co-authored-by: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
Co-authored-by: root <root@localhost>
2026-04-18 15:05:42 +08:00
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, /retro, /investigate, /document-release, /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.
/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.
/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.
/gstack-upgrade Self-Updater — upgrade gstack to latest. Detects global vs vendored install, syncs both, shows what changed.

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.

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 symlinks pointing into gstack/
find ~/.claude/skills -maxdepth 1 -type l 2>/dev/null | while read -r link; do
  case "$(readlink "$link" 2>/dev/null)" in gstack/*|*/gstack/*) rm -f "$link" ;; 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.

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
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.

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, /retro, /investigate, /document-release, /codex,
/cso, /autoplan, /pair-agent, /careful, /freeze, /guard, /unfreeze, /gstack-upgrade, /learn.

License

MIT. Free forever. Go build something.

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