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."