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    shakefu

    skill-improver

    shakefu/skill-improver
    Research
    1 installs

    About

    SKILL.md

    Install

    Install via Skills CLI

    or add to your agent
    • Claude Code
      Claude Code
    • Codex
      Codex
    • OpenClaw
      OpenClaw
    • Cursor
      Cursor
    • Amp
      Amp
    • GitHub Copilot
      GitHub Copilot
    • Gemini CLI
      Gemini CLI
    • Kilo Code
      Kilo Code
    • Junie
      Junie
    • Replit
      Replit
    • Windsurf
      Windsurf
    • Cline
      Cline
    • Continue
      Continue
    • OpenCode
      OpenCode
    • OpenHands
      OpenHands
    • Roo Code
      Roo Code
    • Augment
      Augment
    • Goose
      Goose
    • Trae
      Trae
    • Zencoder
      Zencoder
    • Antigravity
      Antigravity
    ├─
    ├─
    └─

    About

    Research and improve Claude skills with current best practices...

    SKILL.md

    Skill Improver

    Research current best practices and improve existing Claude skills.

    Process Overview

    1. Identify target skill and its domain
    2. Research current best practices (web search)
    3. Analyze existing skill against best practices
    4. Generate improvement recommendations
    5. Apply improvements (if requested)

    Step 1: Identify Target

    Locate the skill to improve:

    # Find skill location
    ls -la .claude/skills/<skill-name>/
    

    Read SKILL.md and all references to understand current implementation.

    Step 2: Research Best Practices

    Use subagents (Task tool) to parallelize research across multiple topics:

    Spawn parallel research agents for:
    1. "<domain> best practices 2026"
    2. "<domain> common mistakes to avoid"
    3. "Claude AI <domain> techniques" (if applicable)
    

    Each subagent should return:

    • Key findings with sources
    • Actionable recommendations

    Focus areas:

    • Industry standards and conventions
    • Common pitfalls and how to avoid them
    • Performance optimizations
    • Security considerations (if relevant)
    • Token efficiency for LLM skills

    Step 3: Analyze Skill

    Compare existing skill against:

    Aspect Check
    Clarity Instructions unambiguous?
    Completeness All use cases covered?
    Efficiency Minimal tokens for max utility?
    Accuracy Reflects current best practices?
    Triggers Description covers all valid triggers?
    Structure Follows skill-creator guidelines?

    Step 4: Generate Recommendations

    Create improvement report:

    ## Skill Improvement Report: <skill-name>
    
    ### Summary
    - Current state assessment
    - Key findings from research
    
    ### Recommendations
    
    #### High Priority
    1. [Issue]: [Recommended fix]
    
    #### Medium Priority
    1. [Issue]: [Recommended fix]
    
    #### Low Priority / Nice-to-Have
    1. [Suggestion]
    
    ### Best Practices Found
    - [Practice 1]: [Source]
    - [Practice 2]: [Source]
    

    Step 5: Apply Improvements

    If user approves changes:

    1. Edit SKILL.md with improvements
    2. Update/add references if needed
    3. Update scripts if applicable
    4. Validate with scripts/validate_skill.py

    Guidelines

    • Preserve intent - Improvements should enhance, not change skill purpose
    • Cite sources - Link to best practice sources when recommending changes
    • Prioritize impact - Focus on changes that meaningfully improve skill quality
    • Maintain conciseness - Don't bloat skills with unnecessary content
    • Test triggers - Ensure description still triggers appropriately after changes

    See references/research-strategies.md for search query templates and source evaluation guidelines.

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    Repository
    shakefu/contextium
    Files