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gstack/CLAUDE.md
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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

27 KiB

gstack development

Commands

bun install          # install dependencies
bun test             # run free tests (browse + snapshot + skill validation)
bun run test:evals   # run paid evals: LLM judge + E2E (diff-based, ~$4/run max)
bun run test:evals:all  # run ALL paid evals regardless of diff
bun run test:gate    # run gate-tier tests only (CI default, blocks merge)
bun run test:periodic  # run periodic-tier tests only (weekly cron / manual)
bun run test:e2e     # run E2E tests only (diff-based, ~$3.85/run max)
bun run test:e2e:all # run ALL E2E tests regardless of diff
bun run eval:select  # show which tests would run based on current diff
bun run dev <cmd>    # run CLI in dev mode, e.g. bun run dev goto https://example.com
bun run build        # gen docs + compile binaries
bun run gen:skill-docs  # regenerate SKILL.md files from templates
bun run skill:check  # health dashboard for all skills
bun run dev:skill    # watch mode: auto-regen + validate on change
bun run eval:list    # list all eval runs from ~/.gstack-dev/evals/
bun run eval:compare # compare two eval runs (auto-picks most recent)
bun run eval:summary # aggregate stats across all eval runs
bun run slop          # full slop-scan report (all files)
bun run slop:diff     # slop findings in files changed on this branch only

test:evals requires ANTHROPIC_API_KEY. Codex E2E tests (test/codex-e2e.test.ts) use Codex's own auth from ~/.codex/ config — no OPENAI_API_KEY env var needed. E2E tests stream progress in real-time (tool-by-tool via --output-format stream-json --verbose). Results are persisted to ~/.gstack-dev/evals/ with auto-comparison against the previous run.

Diff-based test selection: test:evals and test:e2e auto-select tests based on git diff against the base branch. Each test declares its file dependencies in test/helpers/touchfiles.ts. Changes to global touchfiles (session-runner, eval-store, touchfiles.ts itself) trigger all tests. Use EVALS_ALL=1 or the :all script variants to force all tests. Run eval:select to preview which tests would run.

Two-tier system: Tests are classified as gate or periodic in E2E_TIERS (in test/helpers/touchfiles.ts). CI runs only gate tests (EVALS_TIER=gate); periodic tests run weekly via cron or manually. Use EVALS_TIER=gate or EVALS_TIER=periodic to filter. When adding new E2E tests, classify them:

  1. Safety guardrail or deterministic functional test? -> gate
  2. Quality benchmark, Opus model test, or non-deterministic? -> periodic
  3. Requires external service (Codex, Gemini)? -> periodic

Testing

bun test             # run before every commit — free, <2s
bun run test:evals   # run before shipping — paid, diff-based (~$4/run max)

bun test runs skill validation, gen-skill-docs quality checks, and browse integration tests. bun run test:evals runs LLM-judge quality evals and E2E tests via claude -p. Both must pass before creating a PR.

Project structure

gstack/
├── browse/          # Headless browser CLI (Playwright)
│   ├── src/         # CLI + server + commands
│   │   ├── commands.ts  # Command registry (single source of truth)
│   │   └── snapshot.ts  # SNAPSHOT_FLAGS metadata array
│   ├── test/        # Integration tests + fixtures
│   └── dist/        # Compiled binary
├── hosts/           # Typed host configs (one per AI agent)
│   ├── claude.ts    # Primary host config
│   ├── codex.ts, factory.ts, kiro.ts  # Existing hosts
│   ├── opencode.ts, slate.ts, cursor.ts, openclaw.ts  # IDE hosts
│   ├── hermes.ts, gbrain.ts  # Agent runtime hosts
│   └── index.ts     # Registry: exports all, derives Host type
├── scripts/         # Build + DX tooling
│   ├── gen-skill-docs.ts  # Template → SKILL.md generator (config-driven)
│   ├── host-config.ts     # HostConfig interface + validator
│   ├── host-config-export.ts  # Shell bridge for setup script
│   ├── host-adapters/     # Host-specific adapters (OpenClaw tool mapping)
│   ├── resolvers/   # Template resolver modules (preamble, design, review, gbrain, etc.)
│   ├── skill-check.ts     # Health dashboard
│   └── dev-skill.ts       # Watch mode
├── test/            # Skill validation + eval tests
│   ├── helpers/     # skill-parser.ts, session-runner.ts, llm-judge.ts, eval-store.ts
│   ├── fixtures/    # Ground truth JSON, planted-bug fixtures, eval baselines
│   ├── skill-validation.test.ts  # Tier 1: static validation (free, <1s)
│   ├── gen-skill-docs.test.ts    # Tier 1: generator quality (free, <1s)
│   ├── skill-llm-eval.test.ts   # Tier 3: LLM-as-judge (~$0.15/run)
│   └── skill-e2e-*.test.ts       # Tier 2: E2E via claude -p (~$3.85/run, split by category)
├── qa-only/         # /qa-only skill (report-only QA, no fixes)
├── plan-design-review/  # /plan-design-review skill (report-only design audit)
├── design-review/    # /design-review skill (design audit + fix loop)
├── ship/            # Ship workflow skill
├── review/          # PR review skill
├── plan-ceo-review/ # /plan-ceo-review skill
├── plan-eng-review/ # /plan-eng-review skill
├── autoplan/        # /autoplan skill (auto-review pipeline: CEO → design → eng)
├── benchmark/       # /benchmark skill (performance regression detection)
├── canary/          # /canary skill (post-deploy monitoring loop)
├── codex/           # /codex skill (multi-AI second opinion via OpenAI Codex CLI)
├── land-and-deploy/ # /land-and-deploy skill (merge → deploy → canary verify)
├── office-hours/    # /office-hours skill (YC Office Hours — startup diagnostic + builder brainstorm)
├── investigate/     # /investigate skill (systematic root-cause debugging)
├── retro/           # Retrospective skill (includes /retro global cross-project mode)
├── bin/             # CLI utilities (gstack-repo-mode, gstack-slug, gstack-config, etc.)
├── document-release/ # /document-release skill (post-ship doc updates)
├── cso/             # /cso skill (OWASP Top 10 + STRIDE security audit)
├── design-consultation/ # /design-consultation skill (design system from scratch)
├── design-shotgun/  # /design-shotgun skill (visual design exploration)
├── open-gstack-browser/  # /open-gstack-browser skill (launch GStack Browser)
├── connect-chrome/  # symlink → open-gstack-browser (backwards compat)
├── design/          # Design binary CLI (GPT Image API)
│   ├── src/         # CLI + commands (generate, variants, compare, serve, etc.)
│   ├── test/        # Integration tests
│   └── dist/        # Compiled binary
├── extension/       # Chrome extension (side panel + activity feed + CSS inspector)
├── lib/             # Shared libraries (worktree.ts)
├── docs/designs/    # Design documents
├── setup-deploy/    # /setup-deploy skill (one-time deploy config)
├── .github/         # CI workflows + Docker image
│   ├── workflows/   # evals.yml (E2E on Ubicloud), skill-docs.yml, actionlint.yml
│   └── docker/      # Dockerfile.ci (pre-baked toolchain + Playwright/Chromium)
├── contrib/         # Contributor-only tools (never installed for users)
│   └── add-host/    # /gstack-contrib-add-host skill
├── setup            # One-time setup: build binary + symlink skills
├── SKILL.md         # Generated from SKILL.md.tmpl (don't edit directly)
├── SKILL.md.tmpl    # Template: edit this, run gen:skill-docs
├── ETHOS.md         # Builder philosophy (Boil the Lake, Search Before Building)
└── package.json     # Build scripts for browse

SKILL.md workflow

SKILL.md files are generated from .tmpl templates. To update docs:

  1. Edit the .tmpl file (e.g. SKILL.md.tmpl or browse/SKILL.md.tmpl)
  2. Run bun run gen:skill-docs (or bun run build which does it automatically)
  3. Commit both the .tmpl and generated .md files

To add a new browse command: add it to browse/src/commands.ts and rebuild. To add a snapshot flag: add it to SNAPSHOT_FLAGS in browse/src/snapshot.ts and rebuild.

Token ceiling: Generated SKILL.md files must stay under 100KB (~25K tokens). gen-skill-docs warns if any file exceeds this. If a skill template grows past the ceiling, consider extracting optional sections into separate resolvers that only inject when relevant, or making verbose evaluation rubrics more concise.

Merge conflicts on SKILL.md files: NEVER resolve conflicts on generated SKILL.md files by accepting either side. Instead: (1) resolve conflicts on the .tmpl templates and scripts/gen-skill-docs.ts (the sources of truth), (2) run bun run gen:skill-docs to regenerate all SKILL.md files, (3) stage the regenerated files. Accepting one side's generated output silently drops the other side's template changes.

Platform-agnostic design

Skills must NEVER hardcode framework-specific commands, file patterns, or directory structures. Instead:

  1. Read CLAUDE.md for project-specific config (test commands, eval commands, etc.)
  2. If missing, AskUserQuestion — let the user tell you or let gstack search the repo
  3. Persist the answer to CLAUDE.md so we never have to ask again

This applies to test commands, eval commands, deploy commands, and any other project-specific behavior. The project owns its config; gstack reads it.

Writing SKILL templates

SKILL.md.tmpl files are prompt templates read by Claude, not bash scripts. Each bash code block runs in a separate shell — variables do not persist between blocks.

Rules:

  • Use natural language for logic and state. Don't use shell variables to pass state between code blocks. Instead, tell Claude what to remember and reference it in prose (e.g., "the base branch detected in Step 0").
  • Don't hardcode branch names. Detect main/master/etc dynamically via gh pr view or gh repo view. Use {{BASE_BRANCH_DETECT}} for PR-targeting skills. Use "the base branch" in prose, <base> in code block placeholders.
  • Keep bash blocks self-contained. Each code block should work independently. If a block needs context from a previous step, restate it in the prose above.
  • Express conditionals as English. Instead of nested if/elif/else in bash, write numbered decision steps: "1. If X, do Y. 2. Otherwise, do Z."

Writing style (V1)

Default output from every tier-≥2 skill follows the Writing Style section in scripts/resolvers/preamble.ts: jargon glossed on first use (curated list in scripts/jargon-list.json, baked at gen-skill-docs time), questions framed in outcome terms ("what breaks for your users if...") not implementation terms, short sentences, decisions close with user impact. Power users who want the tighter V0 prose set gstack-config set explain_level terse (binary switch, no middle mode). See docs/designs/PLAN_TUNING_V1.md for the full design rationale. The review pacing overhaul that originally tried to ride alongside writing-style was extracted to V1.1 — see docs/designs/PACING_UPDATES_V0.md.

Browser interaction

When you need to interact with a browser (QA, dogfooding, cookie setup), use the /browse skill or run the browse binary directly via $B <command>. NEVER use mcp__claude-in-chrome__* tools — they are slow, unreliable, and not what this project uses.

Sidebar architecture: Before modifying sidepanel.js, background.js, content.js, sidebar-agent.ts, or sidebar-related server endpoints, read docs/designs/SIDEBAR_MESSAGE_FLOW.md. It documents the full initialization timeline, message flow, auth token chain, tab concurrency model, and known failure modes. The sidebar spans 5 files across 2 codebases (extension + server) with non-obvious ordering dependencies. The doc exists to prevent the kind of silent failures that come from not understanding the cross-component flow.

When developing gstack, .claude/skills/gstack may be a symlink back to this working directory (gitignored). This means skill changes are live immediately, great for rapid iteration, risky during big refactors where half-written skills could break other Claude Code sessions using gstack concurrently.

Check once per session: Run ls -la .claude/skills/gstack to see if it's a symlink or a real copy. If it's a symlink to your working directory, be aware that:

  • Template changes + bun run gen:skill-docs immediately affect all gstack invocations
  • Breaking changes to SKILL.md.tmpl files can break concurrent gstack sessions
  • During large refactors, remove the symlink (rm .claude/skills/gstack) so the global install at ~/.claude/skills/gstack/ is used instead

Prefix setting: Setup creates real directories (not symlinks) at the top level with a SKILL.md symlink inside (e.g., qa/SKILL.md -> gstack/qa/SKILL.md). This ensures Claude discovers them as top-level skills, not nested under gstack/. Names are either short (qa) or namespaced (gstack-qa), controlled by skill_prefix in ~/.gstack/config.yaml. Pass --no-prefix or --prefix to skip the interactive prompt.

Note: Vendoring gstack into a project's repo is deprecated. Use global install

  • ./setup --team instead. See README.md for team mode instructions.

For plan reviews: When reviewing plans that modify skill templates or the gen-skill-docs pipeline, consider whether the changes should be tested in isolation before going live (especially if the user is actively using gstack in other windows).

Upgrade migrations: When a change modifies on-disk state (directory structure, config format, stale files) in ways that could break existing user installs, add a migration script to gstack-upgrade/migrations/. Read CONTRIBUTING.md's "Upgrade migrations" section for the format and testing requirements. The upgrade skill runs these automatically after ./setup during /gstack-upgrade.

Compiled binaries — NEVER commit browse/dist/ or design/dist/

The browse/dist/ and design/dist/ directories contain compiled Bun binaries (browse, find-browse, design, ~58MB each). These are Mach-O arm64 only — they do NOT work on Linux, Windows, or Intel Macs. The ./setup script already builds from source for every platform, so the checked-in binaries are redundant. They are tracked by git due to a historical mistake and should eventually be removed with git rm --cached.

NEVER stage or commit these files. They show up as modified in git status because they're tracked despite .gitignore — ignore them. When staging files, always use specific filenames (git add file1 file2) — never git add . or git add -A, which will accidentally include the binaries.

Commit style

Always bisect commits. Every commit should be a single logical change. When you've made multiple changes (e.g., a rename + a rewrite + new tests), split them into separate commits before pushing. Each commit should be independently understandable and revertable.

Examples of good bisection:

  • Rename/move separate from behavior changes
  • Test infrastructure (touchfiles, helpers) separate from test implementations
  • Template changes separate from generated file regeneration
  • Mechanical refactors separate from new features

When the user says "bisect commit" or "bisect and push," split staged/unstaged changes into logical commits and push.

Slop-scan: AI code quality, not AI code hiding

We use slop-scan to catch patterns where AI-generated code is genuinely worse than what a human would write. We are NOT trying to pass as human code. We are AI-coded and proud of it. The goal is code quality.

npx slop-scan scan .          # human-readable report
npx slop-scan scan . --json   # machine-readable for diffing

Config: slop-scan.config.json at repo root (currently excludes **/vendor/**).

What to fix (genuine quality improvements)

  • Empty catches around file ops — use safeUnlink() (ignores ENOENT, rethrows EPERM/EIO). A swallowed EPERM in cleanup means silent data loss.
  • Empty catches around process kills — use safeKill() (ignores ESRCH, rethrows EPERM). A swallowed EPERM means you think you killed something you didn't.
  • Redundant return await — remove when there's no enclosing try block. Saves a microtask, signals intent.
  • Typed exception catchescatch (err) { if (!(err instanceof TypeError)) throw err } is genuinely better than catch {} when the try block does URL parsing or DOM work. You know what error you expect, so say so.

What NOT to fix (linter gaming, not quality)

  • String-matching on error messageserr.message.includes('closed') is brittle. Playwright/Chrome can change wording anytime. If a fire-and-forget operation can fail for ANY reason and you don't care, catch {} is the correct pattern.
  • Adding comments to exempt pass-through wrappers — "alias for active session" above a method just to trip slop-scan's exemption rule is noise, not documentation.
  • Converting extension catch-and-log to selective rethrow — Chrome extensions crash entirely on uncaught errors. If the catch logs and continues, that IS the right pattern for extension code. Don't make it throw.
  • Tightening best-effort cleanup paths — shutdown, emergency cleanup, and disconnect code should use safeUnlinkQuiet() (swallows ALL errors). A cleanup path that throws on EPERM means the rest of cleanup doesn't run. That's worse.

Utilities in browse/src/error-handling.ts

Function Use when Behavior
safeUnlink(path) Normal file deletion Ignores ENOENT, rethrows others
safeUnlinkQuiet(path) Shutdown/emergency cleanup Swallows all errors
safeKill(pid, signal) Sending signals Ignores ESRCH, rethrows others
isProcessAlive(pid) Boolean process checks Returns true/false, never throws

Score tracking

Baseline (2026-04-09, before cleanup): 100 findings, 432.8 score, 2.38 score/file. After cleanup: 90 findings, 358.1 score, 1.96 score/file.

Don't chase the number. Fix patterns that represent actual code quality problems. Accept findings where the "sloppy" pattern is the correct engineering choice.

Community PR guardrails

When reviewing or merging community PRs, always AskUserQuestion before accepting any commit that:

  1. Touches ETHOS.md — this file is Garry's personal builder philosophy. No edits from external contributors or AI agents, period.
  2. Removes or softens promotional material — YC references, founder perspective, and product voice are intentional. PRs that frame these as "unnecessary" or "too promotional" must be rejected.
  3. Changes Garry's voice — the tone, humor, directness, and perspective in skill templates, CHANGELOG, and docs are not generic. PRs that rewrite voice to be more "neutral" or "professional" must be rejected.

Even if the agent strongly believes a change improves the project, these three categories require explicit user approval via AskUserQuestion. No exceptions. No auto-merging. No "I'll just clean this up."

CHANGELOG + VERSION style

VERSION and CHANGELOG are branch-scoped. Every feature branch that ships gets its own version bump and CHANGELOG entry. The entry describes what THIS branch adds — not what was already on main.

When to write the CHANGELOG entry:

  • At /ship time (Step 13), not during development or mid-branch.
  • The entry covers ALL commits on this branch vs the base branch.
  • Never fold new work into an existing CHANGELOG entry from a prior version that already landed on main. If main has v0.10.0.0 and your branch adds features, bump to v0.10.1.0 with a new entry — don't edit the v0.10.0.0 entry.

Key questions before writing:

  1. What branch am I on? What did THIS branch change?
  2. Is the base branch version already released? (If yes, bump and create new entry.)
  3. Does an existing entry on this branch already cover earlier work? (If yes, replace it with one unified entry for the final version.)

Merging main does NOT mean adopting main's version. When you merge origin/main into a feature branch, main may bring new CHANGELOG entries and a higher VERSION. Your branch still needs its OWN version bump on top. If main is at v0.13.8.0 and your branch adds features, bump to v0.13.9.0 with a new entry. Never jam your changes into an entry that already landed on main. Your entry goes on top because your branch lands next.

After merging main, always check:

  • Does CHANGELOG have your branch's own entry separate from main's entries?
  • Is VERSION higher than main's VERSION?
  • Is your entry the topmost entry in CHANGELOG (above main's latest)? If any answer is no, fix it before continuing.

After any CHANGELOG edit that moves, adds, or removes entries, immediately run grep "^## \[" CHANGELOG.md and verify the full version sequence is contiguous with no gaps or duplicates before committing. If a version is missing, the edit broke something. Fix it before moving on.

CHANGELOG.md is for users, not contributors. Write it like product release notes:

  • Lead with what the user can now do that they couldn't before. Sell the feature.
  • Use plain language, not implementation details. "You can now..." not "Refactored the..."
  • Never mention TODOS.md, internal tracking, eval infrastructure, or contributor-facing details. These are invisible to users and meaningless to them.
  • Put contributor/internal changes in a separate "For contributors" section at the bottom.
  • Every entry should make someone think "oh nice, I want to try that."
  • No jargon: say "every question now tells you which project and branch you're in" not "AskUserQuestion format standardized across skill templates via preamble resolver."

AI effort compression

When estimating or discussing effort, always show both human-team and CC+gstack time:

Task type Human team CC+gstack Compression
Boilerplate / scaffolding 2 days 15 min ~100x
Test writing 1 day 15 min ~50x
Feature implementation 1 week 30 min ~30x
Bug fix + regression test 4 hours 15 min ~20x
Architecture / design 2 days 4 hours ~5x
Research / exploration 1 day 3 hours ~3x

Completeness is cheap. Don't recommend shortcuts when the complete implementation is a "lake" (achievable) not an "ocean" (multi-quarter migration). See the Completeness Principle in the skill preamble for the full philosophy.

Search before building

Before designing any solution that involves concurrency, unfamiliar patterns, infrastructure, or anything where the runtime/framework might have a built-in:

  1. Search for "{runtime} {thing} built-in"
  2. Search for "{thing} best practice {current year}"
  3. Check official runtime/framework docs

Three layers of knowledge: tried-and-true (Layer 1), new-and-popular (Layer 2), first-principles (Layer 3). Prize Layer 3 above all. See ETHOS.md for the full builder philosophy.

Local plans

Contributors can store long-range vision docs and design documents in ~/.gstack-dev/plans/. These are local-only (not checked in). When reviewing TODOS.md, check plans/ for candidates that may be ready to promote to TODOs or implement.

E2E eval failure blame protocol

When an E2E eval fails during /ship or any other workflow, never claim "not related to our changes" without proving it. These systems have invisible couplings — a preamble text change affects agent behavior, a new helper changes timing, a regenerated SKILL.md shifts prompt context.

Required before attributing a failure to "pre-existing":

  1. Run the same eval on main (or base branch) and show it fails there too
  2. If it passes on main but fails on the branch — it IS your change. Trace the blame.
  3. If you can't run on main, say "unverified — may or may not be related" and flag it as a risk in the PR body

"Pre-existing" without receipts is a lazy claim. Prove it or don't say it.

Long-running tasks: don't give up

When running evals, E2E tests, or any long-running background task, poll until completion. Use sleep 180 && echo "ready" + TaskOutput in a loop every 3 minutes. Never switch to blocking mode and give up when the poll times out. Never say "I'll be notified when it completes" and stop checking — keep the loop going until the task finishes or the user tells you to stop.

The full E2E suite can take 30-45 minutes. That's 10-15 polling cycles. Do all of them. Report progress at each check (which tests passed, which are running, any failures so far). The user wants to see the run complete, not a promise that you'll check later.

E2E test fixtures: extract, don't copy

NEVER copy a full SKILL.md file into an E2E test fixture. SKILL.md files are 1500-2000 lines. When claude -p reads a file that large, context bloat causes timeouts, flaky turn limits, and tests that take 5-10x longer than necessary.

Instead, extract only the section the test actually needs:

// BAD — agent reads 1900 lines, burns tokens on irrelevant sections
fs.copyFileSync(path.join(ROOT, 'ship', 'SKILL.md'), path.join(dir, 'ship-SKILL.md'));

// GOOD — agent reads ~60 lines, finishes in 38s instead of timing out
const full = fs.readFileSync(path.join(ROOT, 'ship', 'SKILL.md'), 'utf-8');
const start = full.indexOf('## Review Readiness Dashboard');
const end = full.indexOf('\n---\n', start);
fs.writeFileSync(path.join(dir, 'ship-SKILL.md'), full.slice(start, end > start ? end : undefined));

Also when running targeted E2E tests to debug failures:

  • Run in foreground (bun test ...), not background with & and tee
  • Never pkill running eval processes and restart — you lose results and waste money
  • One clean run beats three killed-and-restarted runs

Publishing native OpenClaw skills to ClawHub

Native OpenClaw skills live in openclaw/skills/gstack-openclaw-*/SKILL.md. These are hand-crafted methodology skills (not generated by the pipeline) published to ClawHub so any OpenClaw user can install them.

Publishing: The command is clawhub publish (NOT clawhub skill publish):

clawhub publish openclaw/skills/gstack-openclaw-office-hours \
  --slug gstack-openclaw-office-hours --name "gstack Office Hours" \
  --version 1.0.0 --changelog "description of changes"

Repeat for each skill: gstack-openclaw-ceo-review, gstack-openclaw-investigate, gstack-openclaw-retro. Bump --version on each update.

Auth: clawhub login (opens browser for GitHub auth). clawhub whoami to verify.

Updating: Same clawhub publish command with a higher --version and --changelog.

Verification: clawhub search gstack to confirm they're live.

Deploying to the active skill

The active skill lives at ~/.claude/skills/gstack/. After making changes:

  1. Push your branch
  2. Fetch and reset in the skill directory: cd ~/.claude/skills/gstack && git fetch origin && git reset --hard origin/main
  3. Rebuild: cd ~/.claude/skills/gstack && bun run build

Or copy the binaries directly:

  • cp browse/dist/browse ~/.claude/skills/gstack/browse/dist/browse
  • cp design/dist/design ~/.claude/skills/gstack/design/dist/design