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 onlytest: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:
- Safety guardrail or deterministic functional test? ->
gate - Quality benchmark, Opus model test, or non-deterministic? ->
periodic - Requires external service (Codex, Gemini)? ->
periodic
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.
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 files are generated from .tmpl templates. To update docs:
- Edit the
.tmplfile (e.g.SKILL.md.tmplorbrowse/SKILL.md.tmpl) - Run
bun run gen:skill-docs(orbun run buildwhich does it automatically) - Commit both the
.tmpland generated.mdfiles
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 trip a warning above 160KB (~40K tokens).
This is a "watch for feature bloat" guardrail, not a hard gate. Modern flagship
models have 200K-1M context windows, so 40K is 4-20% of window, and prompt caching
makes the marginal cost of larger skills small. The ceiling exists to catch runaway
preamble/resolver growth, not to force compression on carefully-tuned big skills
(ship, plan-ceo-review, office-hours legitimately pack 25-35K tokens of
behavior). If you blow past 40K, the right fix is usually: (1) look at WHAT grew,
(2) if one resolver added 10K+ in a single PR, question whether it belongs inline
or as a reference doc, (3) only compress carefully-tuned prose as a last resort —
cuts to the coverage audit, review army, or voice directive have real quality cost.
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.
Skills must NEVER hardcode framework-specific commands, file patterns, or directory structures. Instead:
- Read CLAUDE.md for project-specific config (test commands, eval commands, etc.)
- If missing, AskUserQuestion — let the user tell you or let gstack search the repo
- 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.
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 viagh pr vieworgh 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/elsein bash, write numbered decision steps: "1. If X, do Y. 2. Otherwise, do Z."
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.
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.
Transport-layer security (v1.6.0.0+). When pair-agent starts an ngrok tunnel,
the daemon binds two HTTP listeners: a local listener (127.0.0.1, full command
surface, never forwarded) and a tunnel listener (locked allowlist: /connect,
/command with a scoped token + 17-command browser-driving allowlist,
/sidebar-chat). ngrok forwards only the tunnel port. Root tokens over the tunnel
return 403. SSE endpoints use a 30-minute HttpOnly gstack_sse cookie minted via
POST /sse-session (never valid against /command). Tunnel-surface rejections go
to ~/.gstack/security/attempts.jsonl via tunnel-denial-log.ts. Before editing
server.ts, sse-session-cookie.ts, or tunnel-denial-log.ts, read
ARCHITECTURE.md —
the module boundary (no imports from token-registry.ts into sse-session-cookie.ts)
is load-bearing for scope isolation.
Sidebar security stack (layered defense against prompt injection):
| Layer | Module | Lives in |
|---|---|---|
| L1-L3 | content-security.ts |
both server and agent — datamarking, hidden element strip, ARIA regex, URL blocklist, envelope wrapping |
| L4 | security-classifier.ts (TestSavantAI ONNX) |
sidebar-agent only |
| L4b | security-classifier.ts (Claude Haiku transcript) |
sidebar-agent only |
| L5 | security.ts (canary) |
both — inject in compiled, check in agent |
| L6 | security.ts (combineVerdict ensemble) |
both |
Critical constraint: security-classifier.ts CANNOT be imported from the
compiled browse binary. @huggingface/transformers v4 requires onnxruntime-node
which fails to dlopen from Bun compile's temp extract dir. Only security.ts
(pure-string operations — canary, verdict combiner, attack log, status) is safe
for server.ts. See ~/.gstack/projects/garrytan-gstack/ceo-plans/2026-04-19-prompt-injection-guard.md
§"Pre-Impl Gate 1 Outcome" for full architectural decision.
Thresholds (in security.ts):
BLOCK: 0.85— single-layer score that would cause BLOCK if cross-confirmedWARN: 0.60— cross-confirm threshold. When L4 AND L4b both >= 0.60 → BLOCKLOG_ONLY: 0.40— gates transcript classifier (skip Haiku when all layers < 0.40)
Ensemble rule: BLOCK only when the ML content classifier AND the transcript classifier both report >= WARN. Single-layer high confidence degrades to WARN — this is the Stack Overflow instruction-writing FP mitigation. Canary leak always BLOCKs (deterministic).
Env knobs:
GSTACK_SECURITY_OFF=1— emergency kill switch. Classifier stays off even if warmed. Canary is still injected; just the ML scan is skipped.GSTACK_SECURITY_ENSEMBLE=deberta— opt-in DeBERTa-v3 ensemble. Adds ProtectAI DeBERTa-v3-base-injection-onnx as L4c classifier for cross-model agreement. 721MB first-run download. With ensemble enabled, BLOCK requires 2-of-3 ML classifiers agreeing at >= WARN (testsavant, deberta, transcript). Without ensemble (default), BLOCK requires testsavant + transcript at >= WARN.- Classifier model cache:
~/.gstack/models/testsavant-small/(112MB, first run only) plus~/.gstack/models/deberta-v3-injection/(721MB, only when ensemble enabled) - Attack log:
~/.gstack/security/attempts.jsonl(salted sha256 + domain only, rotates at 10MB, 5 generations) - Per-device salt:
~/.gstack/security/device-salt(0600) - Session state:
~/.gstack/security/session-state.json(cross-process, atomic)
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-docsimmediately 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 --teaminstead. 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.
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.
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.
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 diffingConfig: slop-scan.config.json at repo root (currently excludes **/vendor/**).
- 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 catches —
catch (err) { if (!(err instanceof TypeError)) throw err }is genuinely better thancatch {}when the try block does URL parsing or DOM work. You know what error you expect, so say so.
- String-matching on error messages —
err.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.
| 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 |
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.
When reviewing or merging community PRs, always AskUserQuestion before accepting any commit that:
- Touches ETHOS.md — this file is Garry's personal builder philosophy. No edits from external contributors or AI agents, period.
- 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.
- 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."
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
/shiptime (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:
- What branch am I on? What did THIS branch change?
- Is the base branch version already released? (If yes, bump and create new entry.)
- 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."
Every version entry in CHANGELOG.md MUST start with a release-summary section in
the GStack/Garry voice, one viewport's worth of prose + tables that lands like a
verdict, not marketing. The itemized changelog (subsections, bullets, files) goes
BELOW that summary, separated by a ### Itemized changes header.
The release-summary section gets read by humans, by the auto-update agent, and by anyone deciding whether to upgrade. The itemized list is for agents that need to know exactly what changed.
Structure for the top of every ## [X.Y.Z] entry:
- Two-line bold headline (10-14 words total). Should land like a verdict, not marketing. Sound like someone who shipped today and cares whether it works.
- Lead paragraph (3-5 sentences). What shipped, what changed for the user. Specific, concrete, no AI vocabulary, no em dashes, no hype.
- A "The X numbers that matter" section with:
- One short setup paragraph naming the source of the numbers (real production deployment OR a reproducible benchmark, name the file/command to run).
- A table of 3-6 key metrics with BEFORE / AFTER / Δ columns.
- A second optional table for per-category breakdown if relevant.
- 1-2 sentences interpreting the most striking number in concrete user terms.
- A "What this means for [audience]" closing paragraph (2-4 sentences) tying the metrics to a real workflow shift. End with what to do.
Voice rules for the release summary:
- No em dashes (use commas, periods, "...").
- No AI vocabulary (delve, robust, comprehensive, nuanced, fundamental, etc.) or banned phrases ("here's the kicker", "the bottom line", etc.).
- Real numbers, real file names, real commands. Not "fast" but "~30s on 30K pages."
- Short paragraphs, mix one-sentence punches with 2-3 sentence runs.
- Connect to user outcomes: "the agent does ~3x less reading" beats "improved precision."
- Be direct about quality. "Well-designed" or "this is a mess." No dancing.
Source material:
- CHANGELOG previous entry for prior context.
- Benchmark files or
/retrooutput for headline numbers. - Recent commits (
git log <prev-version>..HEAD --oneline) for what shipped. - Don't make up numbers. If a metric isn't in a benchmark or production data, don't include it. Say "no measurement yet" if asked.
Target length: ~250-350 words for the summary. Should render as one viewport.
Write ### Itemized changes and continue with the detailed subsections (Added,
Changed, Fixed, For contributors). Same rules as the user-facing voice guidance
above, plus:
- Always credit community contributions. When an entry includes work from a
community PR, name the contributor with
Contributed by @username. Contributors did real work. Thank them publicly every time, no exceptions.
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.
Before designing any solution that involves concurrency, unfamiliar patterns, infrastructure, or anything where the runtime/framework might have a built-in:
- Search for "{runtime} {thing} built-in"
- Search for "{thing} best practice {current year}"
- 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.
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.
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":
- Run the same eval on main (or base branch) and show it fails there too
- If it passes on main but fails on the branch — it IS your change. Trace the blame.
- 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.
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.
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&andtee - Never
pkillrunning eval processes and restart — you lose results and waste money - One clean run beats three killed-and-restarted runs
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.
The active skill lives at ~/.claude/skills/gstack/. After making changes:
- Push your branch
- Fetch and reset in the skill directory:
cd ~/.claude/skills/gstack && git fetch origin && git reset --hard origin/main - Rebuild:
cd ~/.claude/skills/gstack && bun run build
Or copy the binaries directly:
cp browse/dist/browse ~/.claude/skills/gstack/browse/dist/browsecp design/dist/design ~/.claude/skills/gstack/design/dist/design