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Spec

Skill tinh2/skills-hub-registry/combo/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.

Install
npx -y skills add tinh2/skills-hub-registry --skill spec

Assembled from the repository path, not quoted from the project. Check it against their README if it does not work.

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What its author says it does

Copied from the file, not written here

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:

  1. A video file or screen recording of an application.
  2. Screenshots of an application.
  3. A URL or description of the application.
  4. 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:

  1. Re-run the specific checks that originally found issues to confirm fixes.
  2. Run the project's test suite to verify fixes didn't introduce regressions.
  3. Run build/compile to confirm no breakage.
  4. If new issues surfaced from fixes, add them to the fix queue.
  5. 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:

  1. [Story title] — [why first]
  2. [Story title] — [why next]
  3. ...

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."

What ships with it

Read from the repository

Just SKILL.md. No reference files, no scripts.

Keep looking

Skills are one crate of 326,984. Ordering is by how many stacks a row turns up in, so the top of any crate is what has actually been picked rather than what has the most stars.