Back to Skills

refactor-skill-structure

pjt222
Updated 2 days ago
5 views
17
2
17
View on GitHub
Metageneral

About

This skill refactors lengthy or poorly structured SKILL.md files to meet CI line limits and improve readability. It extracts code examples to a separate file, splits complex procedures, and reorganizes content for progressive disclosure. Use it when a skill exceeds 500 lines, is dominated by code blocks, or has procedural steps with multiple unrelated operations.

Quick Install

Claude Code

Recommended
Primary
npx skills add pjt222/agent-almanac -a claude-code
Plugin CommandAlternative
/plugin add https://github.com/pjt222/agent-almanac
Git CloneAlternative
git clone https://github.com/pjt222/agent-almanac.git ~/.claude/skills/refactor-skill-structure

Copy and paste this command in Claude Code to install this skill

Documentation

Refactor Skill Structure

Refactor SKILL.md exceeded 500-line limit or w/ structural problems. Extract code examples to references/EXAMPLES.md, split compound procs into focused sub-procs, add cross-refs for progressive disclosure, verify skill complete + valid after restructure.

Use When

  • Skill > 500-line CI limit
  • Single proc step has multi unrelated ops → should be separate
  • Code blocks > 15 lines dominate → could extract
  • Skill accumulated ad-hoc sections breaking standard 6-section
  • After update pushed over limit
  • Review flagged structural issues beyond content

In

  • Required: Path to SKILL.md
  • Optional: Target line count (default 80% of 500 = ~400)
  • Optional: Create references/EXAMPLES.md? (default yes if extractable)
  • Optional: Split into multi skills? (default no, prefer extract first)

Do

Step 1: Measure + ID Bloat

Read skill + create section line budget → ID bloat.

# Total line count
wc -l < skills/<skill-name>/SKILL.md

# Line count per section (approximate)
grep -n "^## \|^### " skills/<skill-name>/SKILL.md

Classify bloat:

  • Extractable: Code blocks > 15 lines, full configs, multi-variant examples
  • Splittable: Compound proc steps doing 2+ unrelated ops
  • Trimable: Redundant explanations, verbose ctx
  • Structural: Ad-hoc sections not in standard 6

→ Line budget showing oversized sections + bloat category. Largest = primary refactor targets.

If err: skill < 500 lines + no structural issues → skill not needed. Verify request justified.

Step 2: Extract Code → references/EXAMPLES.md

Move code blocks > 15 lines to references/EXAMPLES.md, leave brief inline (3-10 lines) in main.

  1. Create dir:

    mkdir -p skills/<skill-name>/references/
    
  2. For each extractable block:

    • Copy full block to references/EXAMPLES.md w/ descriptive heading
    • Replace block in SKILL.md w/ brief 3-5 line snippet
    • Add cross-ref: See [EXAMPLES.md](references/EXAMPLES.md#heading) for the complete configuration.
  3. Structure references/EXAMPLES.md w/ clear headings:

    # Examples
    
    ## Example 1: Full Configuration
    
    Complete configuration file for [context]:
    
    \```yaml
    # ... full config here ...
    \```
    
    ## Example 2: Multi-Variant Setup
    
    ### Variant A: Development
    \```yaml
    # ... dev config ...
    \```
    
    ### Variant B: Production
    \```yaml
    # ... prod config ...
    \```
    

→ All blocks > 15 lines extracted. Main SKILL.md keeps brief inline. Cross-refs link to extracted. references/EXAMPLES.md well-organized.

If err: extracting doesn't reduce enough (still > 500) → Step 3 splitting. Few code blocks (natural-lang skill) → focus Steps 3 + 4.

Step 3: Split Compound → Focused Steps

ID proc steps doing multi unrelated ops + split.

Signs compound step:

  • Title contains "and" ("Configure Database and Set Up Caching")
  • Step has multi Expected/On failure blocks (or should)
  • Step > 30 lines
  • Could skip or do diff order from sub-parts

For each compound:

  1. ID distinct ops in step
  2. Create new ### Step N: for each
  3. Renumber subsequent
  4. Each new step → own Expected + On failure
  5. Add transition ctx between new steps

→ Each proc step does one thing. No step > 30 lines. Step count may grow but each indep verifiable.

If err: splitting → too granular (20+ total) → group related micro-steps under single step w/ numbered sub. Sweet spot 5-12 steps.

Step 4: Add Cross-Refs

Ensure main SKILL.md maintains readability + discoverability after extract.

For each extraction:

  1. Inline snippet in SKILL.md self-sufficient for common case
  2. Cross-ref explains additional content available
  3. Use relative paths: [EXAMPLES.md](references/EXAMPLES.md#section-anchor)

Patterns:

  • After brief snippet: See [EXAMPLES.md](references/EXAMPLES.md#full-configuration) for the complete configuration with all options.
  • For multi-variant: See [EXAMPLES.md](references/EXAMPLES.md#variants) for development, staging, and production variants.
  • For extended troubleshooting: See [EXAMPLES.md](references/EXAMPLES.md#troubleshooting) for additional error scenarios.

→ Every extraction has cross-ref. Reader follows main for common case, drills into refs for detail.

If err: cross-refs make text awkward → consolidate multi refs into single note at end of step: For extended examples including [X], [Y], and [Z], see [EXAMPLES.md](references/EXAMPLES.md).

Step 5: Verify Line Count

Re-measure SKILL.md after changes.

# Check main SKILL.md
lines=$(wc -l < skills/<skill-name>/SKILL.md)
[ "$lines" -le 500 ] && echo "SKILL.md: OK ($lines lines)" || echo "SKILL.md: STILL OVER ($lines lines)"

# Check references file if created
if [ -f skills/<skill-name>/references/EXAMPLES.md ]; then
  ref_lines=$(wc -l < skills/<skill-name>/references/EXAMPLES.md)
  echo "EXAMPLES.md: $ref_lines lines"
fi

# Total content
echo "Total content: $((lines + ${ref_lines:-0})) lines"

→ SKILL.md < 500. Ideal < 400 → room future growth. references/EXAMPLES.md no limit.

If err: still > 500 after extract + split → skill should decompose into 2 separate skills. Too much ground = scope creep. Use create-skill for second + update Related Skills cross-refs both.

Step 6: Validate All Sections

After refactor, verify skill has all required sections + frontmatter intact.

Run review-skill-format checklist:

  1. YAML frontmatter parses
  2. All 6 required sections (When to Use, Inputs, Procedure, Validation, Common Pitfalls, Related Skills)
  3. Every proc step has Expected + On failure
  4. No orphaned cross-refs (all links resolve)
# Quick section check
for section in "## When to Use" "## Inputs" "## Procedure" "## Common Pitfalls" "## Related Skills"; do
  grep -q "$section" skills/<skill-name>/SKILL.md && echo "$section: OK" || echo "$section: MISSING"
done
grep -qE "## Validation( Checklist)?" skills/<skill-name>/SKILL.md && echo "Validation: OK" || echo "Validation: MISSING"

→ All sections present. No content accidentally deleted during extract. Cross-refs in SKILL.md resolve to actual headings in EXAMPLES.md.

If err: section accidentally removed → restore from git: git diff skills/<skill-name>/SKILL.md. Cross-refs broken → verify heading anchors in EXAMPLES.md match links in SKILL.md (GitHub anchor: lowercase, hyphens for spaces, strip punctuation).

Check

  • SKILL.md line count ≤ 500
  • All code blocks in SKILL.md ≤ 15 lines
  • Extracted in references/EXAMPLES.md w/ descriptive headings
  • Every extraction has cross-ref in main SKILL.md
  • No compound proc steps remain (each step one thing)
  • All 6 required sections present after refactor
  • Every proc step has Expected: + On failure:
  • YAML frontmatter intact + parseable
  • Cross-ref links resolve to actual headings in EXAMPLES.md
  • review-skill-format validation passes

Traps

  • Extract too aggressive: All code → refs makes main unreadable. Keep 3-10 line snippets inline for common case. Only extract > 15 lines or multi-variant.
  • Broken anchors: GitHub markdown anchors case-sensitive some renderers. Lowercase headings in EXAMPLES.md, match exact in cross-refs. Test grep -c "heading-text" references/EXAMPLES.md.
  • Lose Expected/On failure during split: Each new step gets own Expected + On failure. Easy to leave one w/o blocks after split.
  • Too many tiny steps: Splitting → 5-12 steps. End up 15+ → split too aggressive. Merge related micro back to logical groups.
  • Forget update EXAMPLES.md headings: Rename section → all cross-ref anchors in SKILL.md must update. Grep old anchor to catch all refs.

  • review-skill-format — run format validation after refactor → confirm compliant
  • update-skill-content — content updates often trigger structural refactor when push over limit
  • create-skill — reference canonical structure when deciding how to organize extracted
  • evolve-skill — split into 2 separate skills → use evolution to create derivative

GitHub Repository

pjt222/agent-almanac
Path: i18n/caveman-ultra/skills/refactor-skill-structure
0
agentsagentskillsai-assisted-developmentclaude-codeskillsteams

Related Skills

content-collections

Meta

This skill provides a production-tested setup for Content Collections, a TypeScript-first tool that transforms Markdown/MDX files into type-safe data collections with Zod validation. Use it when building blogs, documentation sites, or content-heavy Vite + React applications to ensure type safety and automatic content validation. It covers everything from Vite plugin configuration and MDX compilation to deployment optimization and schema validation.

View skill

polymarket

Meta

This skill enables developers to build applications with the Polymarket prediction markets platform, including API integration for trading and market data. It also provides real-time data streaming via WebSocket to monitor live trades and market activity. Use it for implementing trading strategies or creating tools that process live market updates.

View skill

creating-opencode-plugins

Meta

This skill helps developers create OpenCode plugins that hook into 25+ event types like commands, files, and LSP operations. It provides the plugin structure, event API specifications, and implementation patterns for JavaScript/TypeScript modules. Use it when you need to intercept, monitor, or extend the OpenCode AI assistant's lifecycle with custom event-driven logic.

View skill

sglang

Meta

SGLang is a high-performance LLM serving framework that specializes in fast, structured generation for JSON, regex, and agentic workflows using its RadixAttention prefix caching. It delivers significantly faster inference, especially for tasks with repeated prefixes, making it ideal for complex, structured outputs and multi-turn conversations. Choose SGLang over alternatives like vLLM when you need constrained decoding or are building applications with extensive prefix sharing.

View skill