Break an epic into implementable story files with acceptance criteria, GDD traceability and ADR guidance. Run after /create-epics.
The English summary is being prepared. Showing the original description.
Run score Not tested
See how to installReview the instructions the agent will receive before you install.
Break an epic into implementable stories — one behavior per story, ~2-4h each, fully traceable to GDD requirement + ADR decision. Run per epic, Foundation first, then Core, etc.
Output: production/epics/[epic-slug]/story-NNN-[slug].md
Resolve review mode: --review arg → production/review-mode.txt → default full. Accept epic-slug or full path. No arg → list available epics via Glob.
Read in full: EPIC.md, its GDD (all 8 sections), all governing ADRs (Decision, Implementation Guidelines, Engine Compatibility, Engine Notes), control-manifest.md (rules + manifest version), tr-registry.yaml.
ADR existence validation: confirm all referenced ADR files exist on disk. Missing → stop immediately, redirect to /architecture-decision.
| Type | Assign when criteria reference... |
|---|---|
| Logic | Formulas, thresholds, state transitions, calculations |
| Integration | Two+ systems interacting, signals crossing boundaries, save/load |
| Visual/Feel | Animation, VFX, timing, audio sync |
| UI | Menus, HUD, buttons, screens, tooltips |
| Config/Data | Balance tuning values, data files only |
Mixed → assign type with highest implementation risk. Type determines test evidence required at /story-done.
For each GDD AC: group related criteria → each group = one story. Order: foundational first, edge cases last, UI last. Per story determine: GDD requirement + TR-ID (from registry), governing ADR (Proposed → story Blocked), story type, engine risk.
Solo/lean → skip. Full → spawn qa-director gate QL-STORY-READY with story list + ACs + types + TR-IDs. Revise until ADEQUATE. Then qa-director produces test case specs per story:
Specs embed into each story's ## QA Test Cases section.
Show full story list (title, type, ADR, TR-IDs covered, test required) before writing. AskUserQuestion: write all / review first.
Each story file includes: header (epic, status, layer, type, manifest version), context (GDD path, TR-ID, ADR + decision summary, engine risk + notes, manifest rules), acceptance criteria (from GDD), implementation notes (from ADR), out of scope, QA test cases (from qa-director), test evidence (required path by type + status), dependencies (depends on / unlocks).
Also update EPIC.md with populated stories table.
Solo/lean → skip. Full → spawn delivery-manager gate PR-EPIC before writing.
AskUserQuestion with context-aware next steps: start implementing (/story-readiness), create stories for next epic, plan sprint, or stop.
No reviews yet. Tell others what you thought.
No login needed. Share how it worked for you, ask a question, or note where it did not run.
No comments yet. Be the first to write one.
Plan, design, and implement A/B tests and experiments with statistical rigor. Covers hypothesis frameworks, sample sizing, metrics, and result analysis.
The English summary is being prepared. Showing the original description.
Web/mobile accessibility decision guide: WCAG 2.2 AA, ARIA, keyboard nav, focus management, contrast, testing. Use for: a11y, accessibility, wcag, aria, screen reader, keyboard, contrast.
The English summary is being prepared. Showing the original description.
Generate, iterate, and scale ad creative for paid advertising across Google, Meta, LinkedIn, and X. Covers platform specs, creative frameworks, and quality validation.
The English summary is being prepared. Showing the original description.
Musica interactiva para juegos: layering vertical, re-secuenciacion horizontal, stingers, reglas de transicion con sync points, y mapeo de estados de gameplay a musica. Usar para: musica adaptativa, sistema de musica dinamica, transiciones musicales, combat music.
The English summary is being prepared. Showing the original description.
Design multi-agent systems, create agent architectures, define communication patterns, and build autonomous agent workflows with structured evaluation frameworks.
The English summary is being prepared. Showing the original description.
Inter-agent communication protocol for C-suite agent teams. Defines invocation syntax, loop prevention, isolation rules, response formats, and quality loops.
The English summary is being prepared. Showing the original description.