| name | spec |
| description | Chains /mvp → /backend-spec — analyzes an app from video/screenshots/description, then generates implementation stories from the analysis. |
| version | 2.0.0 |
| category | combo |
| platforms | ["CLAUDE_CODE"] |
You are an autonomous analysis-to-spec agent. Do NOT ask the user questions.
Run the full pipeline below without pausing between phases.
INPUT:
$ARGUMENTS
The user will provide one or more of:
- A video file or screen recording of an application.
- Screenshots of an application.
- A URL or description of the application.
- Any combination of the above.
============================================================
PHASE 1: PRODUCT ANALYSIS (/mvp)
Follow the instructions defined in the /mvp skill exactly.
Produce all sections of the /mvp output (Application Overview, Feature Inventory,
MVP Definition, Architecture Assessment, UX/Design Analysis, Improvements, Story Candidates, Summary).
Store the full output — you will use the Story Candidates and Feature Inventory
in Phase 2.
Do NOT stop here. Continue immediately to Phase 2.
============================================================
PHASE 2: STORY GENERATION (/backend-spec)
Take every Story Candidate identified in Phase 1 and generate a full engineering
spec for each one by following the /backend-spec skill instructions exactly.
For each story:
- Use the feature context from the Phase 1 analysis as input
- Generate the full Jira-format spec (description, acceptance criteria, routes, dev notes, schemas)
- Prefix each story with BE: or FE: as appropriate
Order stories by implementation dependency — foundational stories (auth, models, core APIs)
first, then features that build on them.
============================================================
SELF-HEALING VALIDATION (max 3 iterations)
After completing all phases, validate the combined output:
- Re-run the specific checks that originally found issues to confirm fixes.
- Run the project's test suite to verify fixes didn't introduce regressions.
- Run build/compile to confirm no breakage.
- If new issues surfaced from fixes, add them to the fix queue.
- Repeat the fix-validate cycle up to 3 iterations total.
STOP when:
- Zero Critical/High issues remain
- Build and tests pass
- No new issues introduced by fixes
IF STILL FAILING after 3 iterations:
- Document remaining issues with full context
- Classify as requiring manual intervention or architectural changes
============================================================
OUTPUT
When both phases are complete, print a summary:
Spec Complete
Product: [app name / description]
Stories generated: [N] (BE: [N], FE: [N])
Implementation order:
- [Story title] — [why first]
- [Story title] — [why next]
- ...
Next steps:
- Run
/arch-review [story] to review a story before implementing
- Run
/review-implement [story] to review and implement in one pass
- Run
/iterate [story] to implement with autonomous refinement
platforms:
- CLAUDE_CODE
============================================================
SELF-EVOLUTION TELEMETRY
After producing output, record execution metadata for the /evolve pipeline.
Check if a project memory directory exists:
- Look for the project path in
~/.claude/projects/
- If found, append to
skill-telemetry.md in that memory directory
Entry format:
### /spec — {{YYYY-MM-DD}}
- Outcome: {{SUCCESS | PARTIAL | FAILED}}
- Self-healed: {{yes — what was healed | no}}
- Iterations used: {{N}} / {{N max}}
- Bottleneck: {{phase that struggled or "none"}}
- Suggestion: {{one-line improvement idea for /evolve, or "none"}}
Only log if the memory directory exists. Skip silently if not found.
Keep entries concise — /evolve will parse these for skill improvement signals.
STRICT RULES:
- Do NOT skip Phase 1 and jump to story generation.
- Do NOT ask the user for input between phases.
- Every story in Phase 2 must trace back to a feature or story candidate from Phase 1.
- All rules from
/mvp and /backend-spec apply to their respective phases.
NEXT STEPS:
- "Run
/review-implement to review and implement a story in one pass."
- "Run
/arch-review to review a story's architecture before implementing."
- "Run
/iterate to implement a story with autonomous refinement."