Claude-skill-registry code-refinement

install
source · Clone the upstream repo
git clone https://github.com/majiayu000/claude-skill-registry
Claude Code · Install into ~/.claude/skills/
T=$(mktemp -d) && git clone --depth=1 https://github.com/majiayu000/claude-skill-registry "$T" && mkdir -p ~/.claude/skills && cp -r "$T/skills/data/code-refinement" ~/.claude/skills/majiayu000-claude-skill-registry-code-refinement && rm -rf "$T"
manifest: skills/data/code-refinement/SKILL.md
source content

Table of Contents

Code Refinement Workflow

Analyze and improve living code quality across six dimensions.

Quick Start

/refine-code
/refine-code --level 2 --focus duplication
/refine-code --level 3 --report refinement-plan.md

When to Use

  • After rapid AI-assisted development sprints
  • Before major releases (quality gate)
  • When code "works but smells"
  • Refactoring existing modules for clarity
  • Reducing technical debt in living code

Analysis Dimensions

#DimensionModuleWhat It Catches
1Duplication & Redundancy
duplication-analysis
Near-identical blocks, similar functions, copy-paste
2Algorithmic Efficiency
algorithm-efficiency
O(n^2) where O(n) works, unnecessary iterations
3Clean Code Violations
clean-code-checks
Long methods, deep nesting, poor naming, magic values
4Architectural Fit
architectural-fit
Paradigm mismatches, coupling violations, leaky abstractions
5Anti-Slop Patterns
clean-code-checks
Premature abstraction, enterprise cosplay, hollow patterns
6Error Handling
clean-code-checks
Bare excepts, swallowed errors, happy-path-only

Progressive Loading

Load modules based on refinement focus:

  • modules/duplication-analysis.md
    (~400 tokens): Duplication detection and consolidation
  • modules/algorithm-efficiency.md
    (~400 tokens): Complexity analysis and optimization
  • modules/clean-code-checks.md
    (~450 tokens): Clean code, anti-slop, error handling
  • modules/architectural-fit.md
    (~400 tokens): Paradigm alignment and coupling

Load all for comprehensive refinement. For focused work, load only relevant modules.

Required TodoWrite Items

  1. refine:context-established
    — Scope, language, framework detection
  2. refine:scan-complete
    — Findings across all dimensions
  3. refine:prioritized
    — Findings ranked by impact and effort
  4. refine:plan-generated
    — Concrete refactoring plan with before/after
  5. refine:evidence-captured
    — Evidence appendix per
    imbue:evidence-logging

Workflow

Step 1: Establish Context (
refine:context-established
)

Detect project characteristics:

# Language detection
find . -name "*.py" -o -name "*.ts" -o -name "*.rs" -o -name "*.go" | head -20

# Framework detection
ls package.json pyproject.toml Cargo.toml go.mod 2>/dev/null

# Size assessment
find . -name "*.py" -o -name "*.ts" -o -name "*.rs" | xargs wc -l 2>/dev/null | tail -1

Step 2: Dimensional Scan (
refine:scan-complete
)

Load relevant modules and execute analysis per tier level.

Step 3: Prioritize (
refine:prioritized
)

Rank findings by:

  • Impact: How much quality improves (HIGH/MEDIUM/LOW)
  • Effort: Lines changed, files touched (SMALL/MEDIUM/LARGE)
  • Risk: Likelihood of introducing bugs (LOW/MEDIUM/HIGH)

Priority = HIGH impact + SMALL effort + LOW risk first.

Step 4: Generate Plan (
refine:plan-generated
)

For each finding, produce:

  • File path and line range
  • Current code snippet
  • Proposed improvement
  • Rationale (which principle/dimension)
  • Estimated effort

Step 5: Evidence Capture (
refine:evidence-captured
)

Document with

imbue:evidence-logging
(if available):

  • [E1]
    ,
    [E2]
    references for each finding
  • Metrics before/after where measurable
  • Principle violations cited

Fallback: If

imbue
is not installed, capture evidence inline in the report using the same
[E1]
reference format without TodoWrite integration.

Tiered Analysis

TierTimeScope
1: Quick (default)2-5 minComplexity hotspots, obvious duplication, naming, magic values
2: Targeted10-20 minAlgorithm analysis, full duplication scan, architectural alignment
3: Deep30-60 minAll above + cross-module coupling, paradigm fitness, comprehensive plan

Cross-Plugin Dependencies

DependencyRequired?Fallback
pensive:shared
YesCore review patterns
imbue:evidence-logging
OptionalInline evidence in report
conserve:code-quality-principles
OptionalBuilt-in KISS/YAGNI/SOLID checks
archetypes:architecture-paradigms
OptionalPrinciple-based checks only (no paradigm detection)

When optional plugins are not installed, the skill degrades gracefully:

  • Without
    imbue
    : Evidence captured inline, no TodoWrite proof-of-work
  • Without
    conserve
    : Uses built-in clean code checks (subset)
  • Without
    archetypes
    : Skips paradigm-specific alignment, uses coupling/cohesion principles only