Spec
Open registry of community-contributed AI coding skills (SKILL.md files) — daily-synced to skills-hub.ai. Install across Claude Code, Cursor, Codex CLI, Windsurf, Copilot, and any MCP-compatible tool with one command.
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What its author says it does
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Chains /mvp → /backend-spec — analyzes an app from video/screenshots/description, then generates implementation stories from the analysis.
SKILL.md
4.5 KB, 907 tokens by cl100k_base, as published. Nobody here has run it
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.mdin 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
/mvpand/backend-specapply to their respective phases.
NEXT STEPS:
- "Run
/review-implementto review and implement a story in one pass." - "Run
/arch-reviewto review a story's architecture before implementing." - "Run
/iterateto implement a story with autonomous refinement."
What ships with it
Read from the repository
Just SKILL.md. No reference files, no scripts.