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sparc-refine — Claude Code skill: what it does, how to install

Runs the Refinement and Completion phases of the SPARC framework. It audits code against specs, raises test coverage to 80%, and verifies release readiness.

Install into Claude Code · Skills CLI (Vercel) All methods and platforms ↓
npx skills add ruvnet/ruflo --skill sparc-refine -a claude-code
Open on GitHub

What sparc-refine does

This skill guides a feature through phases 4 and 5 of the SPARC workflow: Refinement and Completion. During Refinement, the agent audits code against acceptance criteria and architectural boundaries, writes missing unit or integration tests, and targets at least 80% coverage on new code. If performance thresholds are set in the specification, it profiles critical paths.

Gates guard progression between phases. The agent halts on failed tests or unresolved review issues. In the Completion phase, it runs a full regression suite, maps acceptance criteria to test cases in a traceability matrix, generates API documentation, and verifies a deployment readiness checklist.

The skill relies strictly on ruflo-core MCP tools for memory namespaces sparc-phases and sparc-state. Running this skill without Ruflo MCP tools configured will fail at the initial state retrieval step.

What it helps with

  • audit implementation against specification criteria and architecture rules
  • increase test coverage on new code to the 80% threshold
  • build a traceability matrix linking acceptance criteria to test results
  • verify deployment readiness checklist and rollback plan before release

Example prompts for the agent

  • Run sparc-refine for the user-auth feature
  • Execute SPARC Refinement and Completion phases for the current task
  • Review implementation against acceptance criteria and run full regression

How to install sparc-refine

1Skills CLI (Vercel)

npx skills add ruvnet/ruflo --skill sparc-refine -a claude-code

2Manually: put the files in place

~/.claude/skills/sparc-refine/SKILL.md

Copy the whole skill folder; for one project use .claude/skills/sparc-refine/

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Questions about sparc-refine

How to install sparc-refine in Claude Code?

Run npx skills add ruvnet/ruflo --skill sparc-refine -a claude-code. The skill file will be placed at ~/.claude/skills/sparc-refine/SKILL.md.

What does the sparc-refine skill do?

It executes phases 4 and 5 of the SPARC methodology. The skill conducts code reviews against specifications, enforces 80% test coverage, builds a traceability matrix, and validates deployment readiness.

What dependencies does sparc-refine require?

It requires MCP tools provided by ruflo-core for memory management (sparc-phases and sparc-state), plus standard Bash, Read, Write, and Edit tools.

Source text

SKILL.md · MIT
---
name: sparc-refine
description: Run the SPARC Refinement and Completion phases — review code, improve test coverage, validate against specification, and generate documentation
argument-hint: ""
allowed-tools: mcp__plugin_ruflo-core_ruflo__memory_store mcp__plugin_ruflo-core_ruflo__memory_search mcp__plugin_ruflo-core_ruflo__memory_retrieve mcp__plugin_ruflo-core_ruflo__task_create mcp__plugin_ruflo-core_ruflo__task_update mcp__plugin_ruflo-core_ruflo__task_complete mcp__plugin_ruflo-core_ruflo__hooks_intelligence_trajectory-step mcp__plugin_ruflo-core_ruflo__hooks_intelligence_trajectory-end mcp__plugin_ruflo-core_ruflo__neural_train mcp__plugin_ruflo-core_ruflo__neural_predict Bash Read Write Edit
---

# SPARC Refinement + Completion

Run Phases 4 and 5 of the SPARC methodology: iteratively improve through code review and testing, then finalize with validation, documentation, and deployment readiness.

## When to use

After the Architecture phase is complete and its gate has been passed. This skill covers the final two phases that bring a feature from implemented to production-ready.

## Steps

### Phase 4 — Refinement

1. **Retrieve all prior artifacts** — call `mcp__plugin_ruflo-core_ruflo__memory_search` with namespace `sparc-phases` and query for the feature slug. Load spec (acceptance criteria), pseudocode, and architecture.

2. **Retrieve phase state** — call `mcp__plugin_ruflo-core_ruflo__memory_retrieve` with namespace `sparc-state` and exact key `current-phase-{feature-slug}` to confirm we are in Phase 4 (or Phase 5 when resuming completion). If `status === "complete"`, report the existing completion and do not write again; stop on missing/malformed state.

3. **Code review** — review the implementation against:
   a. **Specification compliance**: does every acceptance criterion have a corresponding code path?
   b. **Architecture adherence**: do modules follow the defined boundaries and dependency rules?
   c. **Pseudocode fidelity**: does the implementation match the designed algorithms?
   d. **Code quality**: naming conventions, single responsibility, error handling, no dead code
   e. Document findings as review comments

4. **Test coverage analysis**:
   a. Run existing tests and measure coverage
   b. Identify uncovered acceptance criteria
   c. Write missing tests:
      - Unit tests for each public function
      - Integration tests for cross-module interactions
      - Edge case tests for each identified edge case from the spec
   d. Target coverage >= 80% on new code

5. **Performance validation** — if the spec includes performance constraints:
   a. Profile critical paths identified in the pseudocode
   b. Compare measured performance against constraint thresholds
   c. Optimize if thresholds are not met

6. **Iterate** — repeat steps 3-5 until:
   - All acceptance criteria have passing tests
   - Code review has no critical or high-severity issues
   - Coverage meets the threshold
   - Performance constraints are satisfied

7. **Store refinement artifact** — call `mcp__plugin_ruflo-core_ruflo__memory_store` with namespace `sparc-phases`, key `refine-{feature-slug}`, value: `{ status: "complete", reviewFindings: [...], coveragePercent: N, performanceResults: {...}, iterations: N }`

   Before moving to Phase 5, evaluate the Phase 4 gate (passing acceptance tests, approved review, coverage >= 80%) and store its evidence in `sparc-gates`. On failure preserve phase, increment gateAttempts, refresh `updatedAt` with the current ISO timestamp at the exact current-phase key, report blockers and stop. On pass preserve existing state fields, set phase 5, phaseName "Completion", status "active", and `updatedAt` to the current ISO timestamp at the same key in `sparc-state`. When resuming Phase 5, do not repeat the Phase 4 transition.

8. **Record trajectory step** — call `mcp__plugin_ruflo-core_ruflo__hooks_intelligence_trajectory-step` with refinement summary

### Phase 5 — Completion

9. **Full regression** — run the complete test suite to verify no regressions from refinement changes

10. **Traceability matrix** — build a matrix mapping every acceptance criterion to:
    - The test(s) that verify it
    - The code file(s) that implement it
    - The current pass/fail status

11. **Documentation**:
    a. Generate API documentation from code comments and type definitions
    b. Write usage examples for key public interfaces
    c. Update any existing documentation affected by the changes

12. **Deployment readiness checklist**:
    - [ ] All tests passing
    - [ ] Documentation complete
    - [ ] Database migrations prepared (if applicable)
    - [ ] Configuration changes documented
    - [ ] Feature flags configured (if applicable)
    - [ ] Rollback plan defined
    - [ ] Security review complete (no secrets, inputs validated)

13. **Evaluate the final Phase 5 gate** — completion is allowed only when final gate evidence for every criterion passes: full regression actually ran and passed, documentation is complete, deployment checklist is verified, and traceability links every acceptance criterion to passing tests. Store the actual pass/fail evidence at `gate-5-{feature-slug}-{timestamp}` in `sparc-gates`. If evidence is missing, failed, interrupted, or unrun, preserve state and phase, increment gateAttempts, refresh `updatedAt` to the current ISO timestamp at the exact current-phase key, report blockers and stop. Do not store a complete artifact or complete the state, set completedAt, or train a successful cycle on failure.

    **After the final gate passes, store completion artifact** — call `mcp__plugin_ruflo-core_ruflo__memory_store` with namespace `sparc-phases`, key `complete-{feature-slug}`, value: `{ status: "complete", traceabilityMatrix: [...], documentationFiles: [...], deploymentChecklist: {...}, regressionResult: "pass" }`

    **Close the workflow** — retrieve `current-phase-{feature-slug}` exactly from `sparc-state` again and decode it as `state`. If `status === "complete"`, do not write again or change its timestamps. Otherwise require phase 5 and the successful final gate evidence above; stop on missing/malformed or changed state. Preserve all existing state fields and set `now = new Date().toISOString()`. Call `mcp__plugin_ruflo-core_ruflo__memory_store` with namespace `sparc-state` and exact key `current-phase-{feature-slug}`, value `{ ...state, phase: 5, phaseName: "Completion", status: "complete", completedAt: now, updatedAt: now }` once. Keep phase 5, never increment to 6. Report completion only after this write succeeds. A completion artifact alone does not close state; this read/write sequence is not an atomic concurrency guarantee.

14. **End trajectory** — call `mcp__plugin_ruflo-core_ruflo__hooks_intelligence_trajectory-end` with the full SPARC cycle summary

15. **Train neural patterns** — call `mcp__plugin_ruflo-core_ruflo__neural_train` with the successful SPARC cycle data to improve future predictions

16. **Store learned pattern** — call `mcp__plugin_ruflo-core_ruflo__memory_store` with namespace `patterns`, key `sparc-{feature-slug}`, value summarizing what worked, phase durations, and common blockers encountered

17. **Present completion report** — display the traceability matrix, deployment checklist, and final status. After the final gate and state write succeed, suggest `/ruflo-sparc:ruflo-sparc report` for the full methodology report. Otherwise show active status and blockers, never a completion claim.

## Output format

Success example only: use actual evidence and show completion only after the final gate and state write succeed.

```
# Refinement: {Feature Name}

## Code Review Summary
- Critical issues: {N} (must be 0 to pass gate)
- High issues: {N}
- Medium issues: {N}
- Resolved: {N}/{total}

## Test Coverage
- Overall: {N}%
- New code: {N}%
- Acceptance criteria covered: {N}/{total}

## Performance
| Constraint | Target | Measured | Status |
|-----------|--------|----------|--------|
| Response time | <200ms | 145ms | Pass |

---

# Completion: {Feature Name}

## Traceability Matrix
| AC | Test | Code | Status |
|----|------|------|--------|
| AC-1 | test_xxx | service.ts:42 | Pass |
| AC-2 | test_yyy | controller.ts:18 | Pass |
| AC-3 | test_zzz | repository.ts:31 | Pass |

## Deployment Checklist
- [x] All tests passing
- [x] Documentation complete
- [x] Migrations prepared
- [x] Config documented
- [x] Rollback plan defined
- [x] Security reviewed

---
SPARC workflow complete. Run `/ruflo-sparc:ruflo-sparc report` for the full methodology report.
```

© ruvnet · MIT · ruvnet/ruflo

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