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From hyrex-sparc
Run the SPARC Refinement and Completion phases — review code, improve test coverage, validate against specification, and generate documentation
npx claudepluginhub akhilyad/deployy --plugin hyrex-sparcHow this skill is triggered — by the user, by Claude, or both
Slash command
/hyrex-sparc:sparc-refineThis skill is limited to the following tools:
The summary Claude sees in its skill listing — used to decide when to auto-load this skill
Run Phases 4 and 5 of the SPARC methodology: iteratively improve through code review and testing, then finalize with validation, documentation, and deployment readiness.
Provides UI/UX resources: 50+ styles, color palettes, font pairings, guidelines, charts for web/mobile across React, Next.js, Vue, Svelte, Tailwind, React Native, Flutter. Aids planning, building, reviewing interfaces.
Fetches up-to-date documentation from Context7 for libraries and frameworks like React, Next.js, Prisma. Use for setup questions, API references, and code examples.
Explores codebases via GitNexus: discover repos, query execution flows, trace processes, inspect symbol callers/callees, and review architecture.
Share bugs, ideas, or general feedback.
Run Phases 4 and 5 of the SPARC methodology: iteratively improve through code review and testing, then finalize with validation, documentation, and deployment readiness.
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.
Retrieve all prior artifacts — call mcp__hyrex__memory_search with namespace sparc-phases and query for the feature slug. Load spec (acceptance criteria), pseudocode, and architecture.
Retrieve phase state — call mcp__hyrex__memory_search with namespace sparc-state to confirm we are in Phase 4.
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
Test coverage analysis: a. Run existing tests and measure coverage b. Identify uncovered acceptance criteria c. Write missing tests:
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
Iterate — repeat steps 3-5 until:
Store refinement artifact — call mcp__hyrex__memory_store with namespace sparc-phases, key refine-{feature-slug}, value: { status: "complete", reviewFindings: [...], coveragePercent: N, performanceResults: {...}, iterations: N }
Record trajectory step — call mcp__hyrex__hooks_intelligence_trajectory-step with refinement summary
Full regression — run the complete test suite to verify no regressions from refinement changes
Traceability matrix — build a matrix mapping every acceptance criterion to:
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
Deployment readiness checklist:
Store completion artifact — call mcp__hyrex__memory_store with namespace sparc-phases, key complete-{feature-slug}, value: { status: "complete", traceabilityMatrix: [...], documentationFiles: [...], deploymentChecklist: {...}, regressionResult: "pass" }
End trajectory — call mcp__hyrex__hooks_intelligence_trajectory-end with the full SPARC cycle summary
Train neural patterns — call mcp__hyrex__neural_train with the successful SPARC cycle data to improve future predictions
Store learned pattern — call mcp__hyrex__memory_store with namespace patterns, key sparc-{feature-slug}, value summarizing what worked, phase durations, and common blockers encountered
Present completion report — display the traceability matrix, deployment checklist, and final status. Suggest running /sparc advance to pass the final gate, or /sparc report for the full methodology report.
# 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 `/sparc report` for the full methodology report.