mirror of
https://github.com/garrytan/gstack.git
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* feat: lib/gstack-memory-helpers shared module for V1 memory ingest pipeline Lane 0 foundation per plan §"Eng review additions". 5 public functions imported by the V1 helpers (Lanes A/B/C): canonicalizeRemote(url) — normalize git remote → host/org/repo secretScanFile(path) — gitleaks wrapper with discriminated return detectEngineTier() — cached 60s in ~/.gstack/.gbrain-engine-cache.json parseSkillManifest(path) — extract gbrain.context_queries: from frontmatter withErrorContext(op,fn,caller) — async-aware error logging 22 unit tests, all passing. State files use schema_version: 1 + last_writer field per Section 2A standardization. Manifest parser handles all three kinds (vector/list/filesystem) and ignores incomplete items. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> * feat: bin/gstack-memory-ingest — V1 unified memory ingest helper Lane A. Walks coding-agent transcripts (Claude Code + Codex; Cursor V1.0.1 follow-up) AND ~/.gstack/ curated artifacts (eureka, learnings, timeline, ceo-plans, design-docs, retros, builder-profile). Calls gbrain put_page with type-tagged frontmatter. Uses gstack-memory-helpers (Lane 0): - Modes: --probe / --incremental (default, mtime fast-path) / --bulk - Default 90-day window; --all-history opts into full archive - --sources subset filter; --include-unattributed opt-in for no-remote sessions - --limit N for smoke testing; --benchmark for throughput reporting - Tolerant JSONL parser handles truncated last lines (D10 partial-flag) - State file at ~/.gstack/.transcript-ingest-state.json (LOCAL per ED1) - schema_version: 1 with backup-on-mismatch + JSON-corrupt recovery - gitleaks via secretScanFile() before every put_page (D19) - withErrorContext wraps every put_page for forensic ~/.gstack/.gbrain-errors.jsonl 15 unit tests cover --help, --probe (empty, Claude Code, Codex, mixed artifacts), --sources filter, state file lifecycle (create, schema mismatch backup, JSON corrupt backup), truncated-last-line handling, --limit validation. All passing. V1.5 P0 follow-ups noted in the file header: - Cursor SQLite extraction (V1.0.1) - gbrain put_file routing for Supabase Storage tier (cross-repo) Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> * feat: bin/gstack-gbrain-sync — V1 unified sync verb (Lane B) Orchestrates three storage tiers per plan §"Storage tiering": 1. Code (current repo) → gbrain import (Supabase or local PGLite) 2. Transcripts + curated memory → gstack-memory-ingest (typed put_page) 3. Curated artifacts to git → gstack-brain-sync (existing pipeline) Modes: --incremental (default, mtime fast-path) / --full (~25-35 min per ED2 honest budget) / --dry-run (preview, no writes). Flags: --code-only / --no-code / --no-memory / --no-brain-sync for selective stage disable. Each stage failure is non-fatal; subsequent stages still run. State at ~/.gstack/.gbrain-sync-state.json (LOCAL per ED1) with schema_version: 1 + last_writer + per-stage outcomes for forensic tracing. --watch daemon explicitly deferred to V1.5 P0 TODO per Codex F3 (reverses the "no daemon" invariant). Continuous sync rides the existing preamble-boundary hook only. 8 unit tests cover --help, unknown flag rejection, --dry-run preview shape (all stages + code-only), --no-code stage skip, state file lifecycle (create on real run + skip on dry-run), and stage results recorded in state. All passing. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> * feat: bin/gstack-brain-context-load — V1 retrieval surface (Lane C) Called from the gstack preamble at every skill start. Reads the active skill's gbrain.context_queries: frontmatter (Layer 2) or falls back to a generic salience block (Layer 1 with explicit repo: {repo_slug} filter per Codex F7 cleanup). Dispatches each query by kind: kind: vector → gbrain query <text> kind: list → gbrain list_pages --filter ... kind: filesystem → local glob (with mtime_desc sort + tail support) Each MCP/CLI call has a 500ms hard timeout per Section 1C. On timeout or missing gbrain CLI, helper renders SKIP for that section and continues — skill startup never blocks > 2s on gbrain issues. Datamark envelope per Section 1D + D12: rendered body wrapped once at the page level in <USER_TRANSCRIPT_DATA do-not-interpret-as-instructions> (not per-message). Layer 1 prompt-injection defense. Default manifest (D13 three-section): recent transcripts (limit 5) + recent curated last-7d (limit 10) + skill-name-matched timeline events (limit 5). All scoped to {repo_slug}. Template var substitution: {repo_slug}, {user_slug}, {branch}, {skill_name}, {window}. Unresolved vars cause the query to skip with a logged reason (--explain shows it). 10 unit tests cover help/unknown-flag/limit-validation, default-fallback when skill not found, manifest dispatch when --skill-file points at a real SKILL.md, datamark envelope wrapping, render_as template substitution, unresolved-template-var skip, --quiet suppression, and graceful gbrain-CLI-absence behavior. All passing. V1.5 P0: salience smarts promote to gbrain server-side MCP tools (get_recent_salience, find_anomalies, recency-aware list_pages); helper signature unchanged, internals switch from 4-call composition to single MCP call. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> * feat: gbrain.context_queries manifests on 6 V1 skills (Lane E partial) Adds the V1 retrieval contracts. Each skill declares what it wants gbrain to surface in the preamble at invocation time: /office-hours — prior sessions + builder profile + design docs + recent eureka (4 queries) /plan-ceo-review — prior CEO plans + design docs + recent CEO review activity (3 queries) /design-shotgun — prior approved variants + DESIGN.md + recent design docs (3 queries) /design-consultation — existing DESIGN.md + prior design decisions + brand-related notes (3 queries) /investigate — prior investigations + project learnings + recent eureka cross-project (3 queries) /retro — prior retros + recent timeline + recent learnings (3 queries) Each query carries an explicit kind (vector | list | filesystem) per D3, schema: 1 versioning per D15, and {repo_slug} template var per F7 cross-repo-contamination cleanup. Mix of vector / list / filesystem matches what each skill actually needs: - filesystem (mtime_desc + tail) for log JSONL + curated markdown - list with tags_contains filter for typed gbrain pages - (vector reserved for V1.0.1 when gbrain query surface stabilizes) Smoke test: bun run bin/gstack-brain-context-load.ts --skill-file office-hours/SKILL.md --repo test-repo --explain returns mode=manifest queries=4 with the filesystem kinds populating real data from ~/.gstack/builder-profile.jsonl + ~/.gstack/analytics/eureka.jsonl on this Mac. End-to-end retrieval flow confirmed. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> * feat: setup-gbrain Step 7.5 ingest gate + Step 10 verdict + memory.md ref doc (Lane E partial) Step 7.5: Transcript & memory ingest gate. After Step 7 wires brain-sync but before Step 8's CLAUDE.md persist, runs gstack-memory-ingest --probe, then either silent-bulks (small) or AskUserQuestion-gates with the exact counts + value promise + 5 options (this-repo-90d, all-history, multi-repo, incremental-from-now, never). Decision persists to gstack-config set transcript_ingest_mode <choice>. Step 10: GREEN/YELLOW/RED verdict block. Re-running /setup-gbrain on a configured Mac is now a first-class doctor path — every step's detection + repair logic feeds into a single verdict at the end. Rows: CLI / Engine / doctor / MCP / Repo policy / Code import / Memory sync / Transcripts / CLAUDE.md / Smoke. Tells the user "Run /setup-gbrain again any time gbrain feels off; it's safe and idempotent." setup-gbrain/memory.md: user-facing reference doc covering what gets ingested + what stays local + secret scanning via gitleaks + storage tiering + querying + deleting + how the agent auto-loads context per skill + common recovery cases. Linked from Step 8's CLAUDE.md persist. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> * test: V1 E2E pipeline + --no-write flag for ingest helper (Lane F) E2E pipeline test exercises the full Lane A → B → C value loop: 1. Set up fake $HOME with all 8 memory source types as fixtures 2. gstack-memory-ingest --probe verifies counts match disk 3. gstack-memory-ingest --incremental writes state with schema_version: 1 4. Idempotency: re-run reports 0 changes 5. --probe distinguishes new vs unchanged after first incremental 6. gstack-gbrain-sync --dry-run previews 3 stages 7. --no-code --no-brain-sync --quiet writes sync state with 1 stage entry 8. office-hours/SKILL.md V1 manifest dispatches 4 queries (mode=manifest) 9. Datamark envelope wraps every loaded section (Section 1D + D12) 10. Layer 1 fallback when no skill specified — default 3-section manifest 11. plan-ceo-review/SKILL.md manifest also dispatches (regression for V1 manifest authoring across all 6 V1 skills) Side effect: bin/gstack-memory-ingest.ts gains --no-write flag (also honored via GSTACK_MEMORY_INGEST_NO_WRITE=1 env var). Skips gbrain put_page calls while still updating the state file. Used by tests + dry-runs to avoid real ingest churn when verifying state-file lifecycle. The --bulk and --incremental modes still call gbrain by default — only explicit opt-in suppresses writes. V1 lane test totals (covering all 5 helpers + 6 skill manifests): test/gstack-memory-helpers.test.ts 22 tests test/gstack-memory-ingest.test.ts 15 tests test/gstack-gbrain-sync.test.ts 8 tests test/gstack-brain-context-load.test.ts 10 tests test/skill-e2e-memory-pipeline.test.ts 10 tests ────────────────────────────────────── ───────── TOTAL 65 passing Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> * chore: bump version and changelog (v1.26.0.0) V1 of memory ingest + retrieval surface. Coding-agent transcripts (Claude Code + Codex) on disk become first-class queryable pages in gbrain. Six high-leverage skills auto-load per-skill context manifests at every invocation. Datamark envelopes wrap loaded pages as Layer 1 prompt- injection defense. Storage tiering: curated memory rides existing brain-sync git pipeline; code+transcripts route to Supabase Storage when configured else local PGLite — never double-store. Net branch size vs main: +4174/-849 across 39 files. 65 V1 tests, all green. Goldilocks scope per CEO D18; V1.5 P0 follow-ups documented in the plan's V1.5 TODOs section. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> --------- Co-authored-by: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
345 lines
13 KiB
Cheetah
345 lines
13 KiB
Cheetah
---
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name: design-shotgun
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preamble-tier: 2
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version: 1.0.0
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description: |
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Design shotgun: generate multiple AI design variants, open a comparison board,
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collect structured feedback, and iterate. Standalone design exploration you can
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run anytime. Use when: "explore designs", "show me options", "design variants",
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"visual brainstorm", or "I don't like how this looks".
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Proactively suggest when the user describes a UI feature but hasn't seen
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what it could look like. (gstack)
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triggers:
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- explore design variants
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- show me design options
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- visual design brainstorm
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allowed-tools:
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- Bash
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- Read
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- Glob
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- Grep
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- Agent
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- AskUserQuestion
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gbrain:
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schema: 1
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context_queries:
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- id: prior-approved-variants
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kind: filesystem
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glob: "~/.gstack/projects/{repo_slug}/designs/*/approved.json"
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sort: mtime_desc
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limit: 5
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render_as: "## Prior approved design variants for this project"
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- id: design-md
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kind: filesystem
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glob: "DESIGN.md"
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tail: 1
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render_as: "## DESIGN.md (project design system)"
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- id: recent-design-docs
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kind: filesystem
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glob: "~/.gstack/projects/{repo_slug}/*-design-*.md"
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sort: mtime_desc
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limit: 3
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render_as: "## Recent design docs"
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---
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{{PREAMBLE}}
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# /design-shotgun: Visual Design Exploration
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You are a design brainstorming partner. Generate multiple AI design variants, open them
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side-by-side in the user's browser, and iterate until they approve a direction. This is
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visual brainstorming, not a review process.
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{{DESIGN_SETUP}}
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{{UX_PRINCIPLES}}
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## Step 0: Session Detection
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Check for prior design exploration sessions for this project:
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```bash
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eval "$(~/.claude/skills/gstack/bin/gstack-slug 2>/dev/null)"
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setopt +o nomatch 2>/dev/null || true
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_PREV=$(find ~/.gstack/projects/$SLUG/designs/ -name "approved.json" -maxdepth 2 2>/dev/null | sort -r | head -5)
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[ -n "$_PREV" ] && echo "PREVIOUS_SESSIONS_FOUND" || echo "NO_PREVIOUS_SESSIONS"
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echo "$_PREV"
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```
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**If `PREVIOUS_SESSIONS_FOUND`:** Read each `approved.json`, display a summary, then
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AskUserQuestion:
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> "Previous design explorations for this project:
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> - [date]: [screen] — chose variant [X], feedback: '[summary]'
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>
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> A) Revisit — reopen the comparison board to adjust your choices
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> B) New exploration — start fresh with new or updated instructions
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> C) Something else"
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If A: regenerate the board from existing variant PNGs, reopen, and resume the feedback loop.
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If B: proceed to Step 1.
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**If `NO_PREVIOUS_SESSIONS`:** Show the first-time message:
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"This is /design-shotgun — your visual brainstorming tool. I'll generate multiple AI
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design directions, open them side-by-side in your browser, and you pick your favorite.
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You can run /design-shotgun anytime during development to explore design directions for
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any part of your product. Let's start."
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## Step 1: Context Gathering
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When design-shotgun is invoked from plan-design-review, design-consultation, or another
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skill, the calling skill has already gathered context. Check for `$_DESIGN_BRIEF` — if
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it's set, skip to Step 2.
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When run standalone, gather context to build a proper design brief.
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**Required context (5 dimensions):**
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1. **Who** — who is the design for? (persona, audience, expertise level)
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2. **Job to be done** — what is the user trying to accomplish on this screen/page?
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3. **What exists** — what's already in the codebase? (existing components, pages, patterns)
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4. **User flow** — how do users arrive at this screen and where do they go next?
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5. **Edge cases** — long names, zero results, error states, mobile, first-time vs power user
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**Auto-gather first:**
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```bash
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cat DESIGN.md 2>/dev/null | head -80 || echo "NO_DESIGN_MD"
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```
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```bash
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ls src/ app/ pages/ components/ 2>/dev/null | head -30
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```
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```bash
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setopt +o nomatch 2>/dev/null || true
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ls ~/.gstack/projects/$SLUG/*office-hours* 2>/dev/null | head -5
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```
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If DESIGN.md exists, tell the user: "I'll follow your design system in DESIGN.md by
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default. If you want to go off the reservation on visual direction, just say so —
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design-shotgun will follow your lead, but won't diverge by default."
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**Check for a live site to screenshot** (for the "I don't like THIS" use case):
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```bash
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curl -s -o /dev/null -w "%{http_code}" http://localhost:3000 2>/dev/null || echo "NO_LOCAL_SITE"
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```
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If a local site is running AND the user referenced a URL or said something like "I don't
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like how this looks," screenshot the current page and use `$D evolve` instead of
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`$D variants` to generate improvement variants from the existing design.
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**AskUserQuestion with pre-filled context:** Pre-fill what you inferred from the codebase,
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DESIGN.md, and office-hours output. Then ask for what's missing. Frame as ONE question
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covering all gaps:
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> "Here's what I know: [pre-filled context]. I'm missing [gaps].
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> Tell me: [specific questions about the gaps].
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> How many variants? (default 3, up to 8 for important screens)"
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Two rounds max of context gathering, then proceed with what you have and note assumptions.
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## Step 2: Taste Memory
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Read both the persistent taste profile (cross-session) AND the per-session approved
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designs to bias generation toward the user's demonstrated taste.
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**Persistent taste profile (v1 schema at `~/.gstack/projects/$SLUG/taste-profile.json`):**
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{{TASTE_PROFILE}}
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**Per-session approved.json files (legacy, still supported):**
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```bash
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setopt +o nomatch 2>/dev/null || true
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_TASTE=$(find ~/.gstack/projects/$SLUG/designs/ -name "approved.json" -maxdepth 2 2>/dev/null | sort -r | head -10)
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```
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If prior sessions exist, read each `approved.json` and extract patterns from the
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approved variants. Merge these into the taste-profile.json-derived signal — if the
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profile already says "user prefers Geist font" (from aggregated history), the
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approved.json files add the specific recent approval context.
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Limit to last 10 sessions. Try/catch JSON parse on each (skip corrupted files).
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**Updating taste profile after a design-shotgun session:** When the user picks a
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variant, call `{{BIN_DIR}}/gstack-taste-update approved <variant-path>`. When they
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explicitly reject a variant, call `{{BIN_DIR}}/gstack-taste-update rejected <variant-path>`.
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The CLI handles schema migration from approved.json, decay, and conflict flagging.
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## Step 3: Generate Variants
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Set up the output directory:
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```bash
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eval "$(~/.claude/skills/gstack/bin/gstack-slug 2>/dev/null)"
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_DESIGN_DIR="$HOME/.gstack/projects/$SLUG/designs/<screen-name>-$(date +%Y%m%d)"
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mkdir -p "$_DESIGN_DIR"
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echo "DESIGN_DIR: $_DESIGN_DIR"
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```
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Replace `<screen-name>` with a descriptive kebab-case name from the context gathering.
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### Step 3a: Concept Generation
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Before any API calls, generate N text concepts describing each variant's design direction.
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Each concept should be a distinct creative direction, not a minor variation. Present them
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as a lettered list:
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```
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I'll explore 3 directions:
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A) "Name" — one-line visual description of this direction
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B) "Name" — one-line visual description of this direction
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C) "Name" — one-line visual description of this direction
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```
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Draw on DESIGN.md, taste memory, and the user's request to make each concept distinct.
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**Anti-convergence directive (hard requirement):** Each variant MUST use a different
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font family, color palette, and layout approach. If two variants look like siblings
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— same typographic feel, overlapping color temperature, comparable layout rhythm —
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one of them failed. Regenerate the weaker one with a deliberately different direction.
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Concrete test: if someone could swap the headline text between two variants without
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noticing, they're too similar. Variants should feel like they came from three
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different design teams, not the same team at three different coffee levels.
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### Step 3b: Concept Confirmation
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Use AskUserQuestion to confirm before spending API credits:
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> "These are the {N} directions I'll generate. Each takes ~60s, but I'll run them all
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> in parallel so total time is ~60 seconds regardless of count."
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Options:
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- A) Generate all {N} — looks good
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- B) I want to change some concepts (tell me which)
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- C) Add more variants (I'll suggest additional directions)
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- D) Fewer variants (tell me which to drop)
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If B: incorporate feedback, re-present concepts, re-confirm. Max 2 rounds.
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If C: add concepts, re-present, re-confirm.
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If D: drop specified concepts, re-present, re-confirm.
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### Step 3c: Parallel Generation
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**If evolving from a screenshot** (user said "I don't like THIS"), take ONE screenshot
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first:
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```bash
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$B screenshot "$_DESIGN_DIR/current.png"
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```
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**Launch N Agent subagents in a single message** (parallel execution). Use the Agent
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tool with `subagent_type: "general-purpose"` for each variant. Each agent is independent
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and handles its own generation, quality check, verification, and retry.
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**Important: $D path propagation.** The `$D` variable from DESIGN SETUP is a shell
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variable that agents do NOT inherit. Substitute the resolved absolute path (from the
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`DESIGN_READY: /path/to/design` output in Step 0) into each agent prompt.
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**Agent prompt template** (one per variant, substitute all `{...}` values):
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```
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Generate a design variant and save it.
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Design binary: {absolute path to $D binary}
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Brief: {the full variant-specific brief for this direction}
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Output: /tmp/variant-{letter}.png
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Final location: {_DESIGN_DIR absolute path}/variant-{letter}.png
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Steps:
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1. Run: {$D path} generate --brief "{brief}" --output /tmp/variant-{letter}.png
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2. If the command fails with a rate limit error (429 or "rate limit"), wait 5 seconds
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and retry. Up to 3 retries.
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3. If the output file is missing or empty after the command succeeds, retry once.
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4. Copy: cp /tmp/variant-{letter}.png {_DESIGN_DIR}/variant-{letter}.png
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5. Quality check: {$D path} check --image {_DESIGN_DIR}/variant-{letter}.png --brief "{brief}"
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If quality check fails, retry generation once.
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6. Verify: ls -lh {_DESIGN_DIR}/variant-{letter}.png
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7. Report exactly one of:
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VARIANT_{letter}_DONE: {file size}
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VARIANT_{letter}_FAILED: {error description}
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VARIANT_{letter}_RATE_LIMITED: exhausted retries
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```
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For the evolve path, replace step 1 with:
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```
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{$D path} evolve --screenshot {_DESIGN_DIR}/current.png --brief "{brief}" --output /tmp/variant-{letter}.png
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```
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**Why /tmp/ then cp?** In observed sessions, `$D generate --output ~/.gstack/...`
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failed with "The operation was aborted" while `--output /tmp/...` succeeded. This is
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a sandbox restriction. Always generate to `/tmp/` first, then `cp`.
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### Step 3d: Results
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After all agents complete:
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1. Read each generated PNG inline (Read tool) so the user sees all variants at once.
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2. Report status: "All {N} variants generated in ~{actual time}. {successes} succeeded,
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{failures} failed."
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3. For any failures: report explicitly with the error. Do NOT silently skip.
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4. If zero variants succeeded: fall back to sequential generation (one at a time with
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`$D generate`, showing each as it lands). Tell the user: "Parallel generation failed
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(likely rate limiting). Falling back to sequential..."
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5. Proceed to Step 4 (comparison board).
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**Dynamic image list for comparison board:** When proceeding to Step 4, construct the
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image list from whatever variant files actually exist, not a hardcoded A/B/C list:
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```bash
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setopt +o nomatch 2>/dev/null || true # zsh compat
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_IMAGES=$(ls "$_DESIGN_DIR"/variant-*.png 2>/dev/null | tr '\n' ',' | sed 's/,$//')
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```
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Use `$_IMAGES` in the `$D compare --images` command.
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## Step 4: Comparison Board + Feedback Loop
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{{DESIGN_SHOTGUN_LOOP}}
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## Step 5: Feedback Confirmation
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After receiving feedback (via HTTP POST or AskUserQuestion fallback), output a clear
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summary confirming what was understood:
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"Here's what I understood from your feedback:
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PREFERRED: Variant [X]
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RATINGS: A: 4/5, B: 3/5, C: 2/5
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YOUR NOTES: [full text of per-variant and overall comments]
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DIRECTION: [regenerate action if any]
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Is this right?"
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Use AskUserQuestion to confirm before saving.
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## Step 6: Save & Next Steps
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Write `approved.json` to `$_DESIGN_DIR/` (handled by the loop above).
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If invoked from another skill: return the structured feedback for that skill to consume.
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The calling skill reads `approved.json` and the approved variant PNG.
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If standalone, offer next steps via AskUserQuestion:
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> "Design direction locked in. What's next?
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> A) Iterate more — refine the approved variant with specific feedback
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> B) Finalize — generate production Pretext-native HTML/CSS with /design-html
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> C) Save to plan — add this as an approved mockup reference in the current plan
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> D) Done — I'll use this later"
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## Important Rules
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1. **Never save to `.context/`, `docs/designs/`, or `/tmp/`.** All design artifacts go
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to `~/.gstack/projects/$SLUG/designs/`. This is enforced. See DESIGN_SETUP above.
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2. **Show variants inline before opening the board.** The user should see designs
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immediately in their terminal. The browser board is for detailed feedback.
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3. **Confirm feedback before saving.** Always summarize what you understood and verify.
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4. **Taste memory is automatic.** Prior approved designs inform new generations by default.
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5. **Two rounds max on context gathering.** Don't over-interrogate. Proceed with assumptions.
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6. **DESIGN.md is the default constraint.** Unless the user says otherwise.
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