sparc-refine
Run the SPARC Refinement and Completion phases — review code, improve test coverage, validate against specification, and generate documentation
Best for Post-architecture feature c…Works with GitHub
⌘source
- author
@ruvnet- repo
- ruvnet/ruflo
- language
- TypeScript
★46kstars
5.1kforks
May 5, 2026
✦overview.md
Key Features
- ·Runs SPARC Phases 4 and 5
- ·Reviews code against specification
- ·Improves test coverage
- ·Validates against acceptance criteria
- ·Generates documentation
- ·Finalizes deployment readiness
Use Cases
- →After architecture phase, refine and complete a feature
- →Bring implementation to production-ready state
- →Ensure full test coverage and spec compliance
- →Generate missing documentation for a completed feature
Best for
- ✓Post-architecture feature completion
- ✓Production readiness
- ✓Spec-driven development teams
Not ideal for
- !Early design or ideation phases
- !One-off or throwaway code
FAQs
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__claude-flow__memory_store mcp__claude-flow__memory_search mcp__claude-flow__memory_retrieve mcp__claude-flow__task_create mcp__claude-flow__task_update mcp__claude-flow__task_complete mcp__claude-flow__hooks_intelligence_trajectory-step mcp__claude-flow__hooks_intelligence_trajectory-end mcp__claude-flow__neural_train mcp__claude-flow__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
-
Retrieve all prior artifacts — call
mcp__claude-flow__memory_searchwith namespacesparc-phasesand query for the feature slug. Load spec (acceptance criteria), pseudocode, and architecture. -
Retrieve phase state — call
mcp__claude-flow__memory_searchwith namespacesparc-stateto 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
$install
1-click copynpx skills add ruvnet/ruflo --skill sparc-refineSafety assessment
★
Clarity score
How clear and easy to understand the SKILL.md instructions are, rated from 1 to 5.
4/ 5
very goodClear and well structured, with only minor parts that might need a second read.
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Actionability score
How directly an agent can act on the SKILL.md instructions, rated from 1 to 5.
4/ 5
highMostly actionable with clear steps; only a few small gaps remain.