Skill Builder

Skills are organized prompts that get loaded on-demand. All prompting best practices apply, with an emphasis on pure XML structure for consistent parsing and efficient token usage.

See references/skill-structure.md for complete details.

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• <objective> - What the skill does and why it matters
• <quick_start> - Immediate, actionable guidance
• <success_criteria> or <when_successful> - How to know it worked

• <context> - Background/situational information
• <workflow> or <process> - Step-by-step procedures
• <advanced_features> - Deep-dive topics (progressive disclosure)
• <validation> - How to verify outputs
• <examples> - Multi-shot learning
• <anti_patterns> - Common mistakes to avoid
• <security_checklist> - Non-negotiable security patterns
• <testing> - Testing workflows
• <common_patterns> - Code examples and recipes
• <reference_guides> or <detailed_references> - Links to reference files

Example: Text extraction, file format conversion, simple API calls

Example: Document processing with multiple steps, API integration with configuration

Example: Payment processing, authentication systems, multi-step workflows with validation

IF no context provided (user just invoked the skill without describing what to build): → IMMEDIATELY use AskUserQuestion with these exact options:

1. Create a new skill - Build a skill from scratch
2. Update an existing skill - Modify or improve an existing skill
3. Get guidance on skill design - Help me think through what kind of skill I need

DO NOT ask "what would you like to build?" in plain text. USE the AskUserQuestion tool.

Routing after selection:

• "Create new" → proceed to adaptive intake below
• "Update existing" → enumerate existing skills as numbered list (see below), then gather requirements for changes
• "Guidance" → help user clarify needs before building

1. List all skills in chat as numbered list (DO NOT use AskUserQuestion - there may be many skills):

   • Glob for ~/skills/*/SKILL.md
   • Present as numbered list in chat:

     Available skills:
     1. create-agent-skills
     2. generate-natal-chart
     3. manage-stripe
     ...
     

   • Ask: "Which skill would you like to update? (enter number)"

2. After user enters number, read that skill's SKILL.md

3. Ask what they want to change/improve using AskUserQuestion or direct question

4. Proceed with modifications

IF context was provided (user said "build a skill for X"): → Skip this gate. Proceed directly to adaptive intake.

Do NOT ask about things that are obvious from context.

Question generation guidance:

• Scope questions: "What specific operations?" not "What should it do?"
• Complexity questions: "Should this handle [specific edge case]?" based on domain knowledge
• Output questions: "What should the user see/get when successful?"
• Boundary questions: "Should this also handle [related thing] or stay focused?"

Avoid:

• Questions answerable from the initial description
• Generic questions that apply to all skills
• Yes/no questions when options would be more helpful
• Obvious questions like "what should it be called?" when the name is clear

Each question option should include a description explaining the implications of that choice.

Question: "Ready to proceed with building, or would you like me to ask more questions?"

Options:

1. Proceed to building - I have enough context to build the skill
2. Ask more questions - There are more details to clarify
3. Let me add details - I want to provide additional context

If "Ask more questions" selected → loop back to generate_questions with refined focus If "Let me add details" → receive additional context, then re-evaluate If "Proceed" → continue to research_trigger, then step_1

External APIs or web services:

• Keywords: "API", "endpoint", "REST", "GraphQL", "webhook", "HTTP"
• Service names: "Stripe", "AWS", "Firebase", "OpenAI", "Anthropic", etc.

Standard vocabularies and ontologies:

• Keywords: "schema.org", "vocabulary", "ontology", "JSON-LD", "RDF", "microdata"
• Examples: Schema.org types, Dublin Core, FOAF

Protocol specifications:

• Keywords: "specification", "standard", "protocol"
• Examples: "HTTP", "WebSocket", "MQTT", "OAuth", "SAML"

Third-party libraries or frameworks:

• Keywords: "library", "package", "framework", "npm", "pip", "cargo"
• Examples: "React", "Django", "pandas", "TensorFlow"

Data format standards:

• Keywords: "format", "parser", "serialization"
• Examples: "CSV", "Parquet", "Protocol Buffers", "Avro", "XML"

Detection method: Check user's initial description and all collected requirements for these keywords or patterns.

"This skill involves [detected technology/standard]. Would you like me to research current [technology] documentation and patterns before building?"

Options:

1. Yes, research first - Fetch 2024-2025 documentation for accurate, up-to-date implementation
2. No, proceed with general patterns - Use knowledge cutoff data (January 2025)
3. I'll provide the documentation - User will supply relevant documentation or links

If option 1 selected:

• For web APIs: Use WebSearch for "[technology] API documentation 2024 2025"
• For libraries: Use Context7 MCP if available, otherwise WebSearch
• For standards/vocabularies: Use WebSearch for "[standard] specification latest"
• Focus on: current versions, recent changes, migration guides, common patterns
• Summarize findings in internal notes for use in skill generation

If option 3 selected:

• Wait for user to provide documentation
• Read provided links or files
• Summarize key information for skill generation

Note findings in skill generation process:

Research findings for [technology]:
- Current version: [version]
- Key changes from knowledge cutoff: [summary]
- Recommended patterns: [list]
- Documentation links: [urls]

1. Primary indicators (strong project context):

   • CLAUDE.md file exists
   • .claude/ directory exists
   • Git repository root (.git/ directory)

2. Secondary indicators (language-specific projects):

   • package.json (Node.js)
   • pyproject.toml or setup.py (Python)
   • Cargo.toml (Rust)
   • pom.xml or build.gradle (Java)
   • go.mod (Go)

3. Path determination:

   # Use Bash to check project context:
   if [ -f "CLAUDE.md" ] || [ -d ".claude" ]; then
     PROJECT_CONTEXT=true
     PROJECT_ROOT=$(pwd)
   elif git rev-parse --git-dir > /dev/null 2>&1; then
     PROJECT_CONTEXT=true
     PROJECT_ROOT=$(git rev-parse --show-toplevel)
   else
     PROJECT_CONTEXT=false
   fi
   

4. Set paths based on context:

   • If PROJECT_CONTEXT=true:
     • SKILLS_PATH="$PROJECT_ROOT/skills/"
     • COMMANDS_PATH="$PROJECT_ROOT/commands/"
   • If PROJECT_CONTEXT=false:
     • SKILLS_PATH="$HOME/skills/"
     • COMMANDS_PATH="$HOME/commands/"

"Detected project context at: [project_root]

Where should this skill be created?"

Options:

1. Project-specific (skills/) - Tracked in git, shared with team, specific to this codebase
2. Global (~/skills/) - Personal use across all projects, general-purpose skill

Provide recommendation based on skill purpose:

• If skill mentions project-specific terms (file paths, module names, codebase concepts) → Recommend project-specific
• If skill is general-purpose (works with any codebase) → Recommend global
• If user explicitly mentioned "for this project" → Recommend project-specific
• Default recommendation: Project-specific (safer, can be moved to global later)

• Step 0.5: Create directory at $SKILLS_PATH/[skill-name]/
• Step 3-5: Write SKILL.md to $SKILLS_PATH/[skill-name]/SKILL.md
• Step 5: Create references at $SKILLS_PATH/[skill-name]/references/
• Step 8: Create slash command at $COMMANDS_PATH/[skill-name].md
• Step 8.5 (if applicable): Create README at $SKILLS_PATH/[skill-name]/README.md

All subsequent file operations MUST use these paths, not hardcoded paths.

1. File Structure Checks:

# Check SKILL.md exists
[ -f "$SKILLS_PATH/$SKILL_NAME/SKILL.md" ] && echo "✅ SKILL.md exists" || echo "❌ SKILL.md missing"

# Check directory name matches YAML name
YAML_NAME=$(head -20 "$SKILLS_PATH/$SKILL_NAME/SKILL.md" | grep "^name:" | cut -d: -f2 | tr -d ' ')
[ "$YAML_NAME" = "$SKILL_NAME" ] && echo "✅ Name matches directory" || echo "⚠️  Name mismatch"

2. YAML Frontmatter Validation:

# Extract and validate YAML
head -20 "$SKILLS_PATH/$SKILL_NAME/SKILL.md" | python3 -c "
import yaml, sys
try:
    doc = yaml.safe_load(sys.stdin)
    print('✅ YAML syntax valid')

    # Check required fields
    if 'name' in doc:
        print(f'✅ Name field present: {doc[\"name\"]}')
        if len(doc['name']) <= 64:
            print(f'✅ Name length OK: {len(doc[\"name\"])} chars')
        else:
            print(f'⚠️  Name too long: {len(doc[\"name\"])} chars (max 64)')
    else:
        print('❌ Name field missing')

    if 'description' in doc:
        print(f'✅ Description field present: {len(doc[\"description\"])} chars')
        if len(doc['description']) <= 1024:
            print(f'✅ Description length OK')
        else:
            print(f'⚠️  Description too long: {len(doc[\"description\"])} chars (max 1024)')
    else:
        print('❌ Description field missing')

except yaml.YAMLError as e:
    print(f'❌ YAML parse error: {e}')
"

3. Line Count Check:

LINE_COUNT=$(wc -l < "$SKILLS_PATH/$SKILL_NAME/SKILL.md")
echo "SKILL.md line count: $LINE_COUNT"
if [ $LINE_COUNT -lt 500 ]; then
    echo "✅ Line count under 500 limit ($LINE_COUNT lines, $(( (500 - LINE_COUNT) )) remaining)"
else
    echo "⚠️  Line count exceeds 500 limit ($LINE_COUNT lines, $(( (LINE_COUNT - 500) )) over)"
fi

4. XML Structure Checks:

# Check for markdown headings
HEADING_COUNT=$(grep -c '^#' "$SKILLS_PATH/$SKILL_NAME/SKILL.md" || echo 0)
if [ $HEADING_COUNT -eq 0 ]; then
    echo "✅ No markdown headings found"
else
    echo "⚠️  Found $HEADING_COUNT markdown headings - should use XML tags instead"
    grep -n '^#' "$SKILLS_PATH/$SKILL_NAME/SKILL.md"
fi

# Check required tags
for TAG in "objective" "quick_start" "success_criteria"; do
    if grep -q "<$TAG>" "$SKILLS_PATH/$SKILL_NAME/SKILL.md"; then
        echo "✅ Required tag <$TAG> present"
    else
        if [ "$TAG" = "success_criteria" ]; then
            if grep -q "<when_successful>" "$SKILLS_PATH/$SKILL_NAME/SKILL.md"; then
                echo "✅ Alternative tag <when_successful> present"
            else
                echo "❌ Missing required tag: <$TAG> or <when_successful>"
            fi
        else
            echo "❌ Missing required tag: <$TAG>"
        fi
    fi
done

# List all XML tags found
echo "XML tags found:"
grep -oE '<[a-z_]+>' "$SKILLS_PATH/$SKILL_NAME/SKILL.md" | sort | uniq -c | sort -rn

5. Progressive Disclosure Check:

if [ $LINE_COUNT -gt 300 ]; then
    if [ -d "$SKILLS_PATH/$SKILL_NAME/references" ]; then
        REF_COUNT=$(find "$SKILLS_PATH/$SKILL_NAME/references" -name "*.md" | wc -l)
        echo "✅ Progressive disclosure: $REF_COUNT reference files created"
    else
        echo "⚠️  SKILL.md is $LINE_COUNT lines but no reference files found - consider splitting"
    fi
fi

6. Reference Link Validation:

# Check all reference links exist
grep -oE '\[.*\]\([^)]+\.md\)' "$SKILLS_PATH/$SKILL_NAME/SKILL.md" | while read link; do
    FILE=$(echo "$link" | sed 's/.*(\(.*\))/\1/')
    if [ -f "$SKILLS_PATH/$SKILL_NAME/$FILE" ]; then
        echo "✅ Reference link valid: $FILE"
    else
        echo "⚠️  Broken reference link: $FILE"
    fi
done

7. Naming Convention Check:

# Check verb-noun pattern
SKILL_FIRST_WORD=$(echo "$SKILL_NAME" | cut -d- -f1)
COMMON_VERBS="create manage setup generate analyze process coordinate build handle configure deploy execute extract transform validate parse render compile"

if echo "$COMMON_VERBS" | grep -qw "$SKILL_FIRST_WORD"; then
    echo "✅ Naming convention: '$SKILL_FIRST_WORD' follows verb-noun pattern"
else
    echo "⚠️  Naming: '$SKILL_FIRST_WORD' is not a common verb - verify it's action-oriented"
fi

━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
Skill Validation Report: [skill-name]
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━

File Structure:     [✅/❌] [details]
YAML Frontmatter:   [✅/❌] [details]
Line Count:         [✅/⚠️]  [X lines / 500 limit]
Required Tags:      [✅/❌] [3/3 present]
No MD Headings:     [✅/⚠️]  [X found]
XML Structure:      [✅/❌] [tags properly nested]
Progressive Disc:   [✅/⚠️]  [X ref files]
Reference Links:    [✅/⚠️]  [all valid / X broken]
Naming Convention:  [✅/⚠️]  [verb-noun pattern]
Slash Command:      [✅/❌] [exists at correct path]

Overall Status: [PASS ✅ / NEEDS FIXES ⚠️  / FAIL ❌]

[If issues found, list them with suggested fixes]
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━

1. Stop immediately - Do not proceed to Step 7
2. Report failures clearly with specific line numbers or details
3. Attempt automatic fixes where possible:
   • Remove markdown headings → convert to XML tags
   • Fix YAML syntax errors if obvious
   • Rename files to match conventions
4. If cannot auto-fix, ask user:

   Validation failed. How should I proceed?
   
   Options:
   1. Let me try to fix automatically
   2. Show me the issues and I'll fix manually
   3. Proceed anyway (not recommended)
   

5. Re-run validation after fixes applied
6. Only proceed to Step 7 when all critical checks pass

Warning-level issues (⚠️) can proceed but should be noted:

• Line count 400-500: "Approaching limit, future edits may need reference split"
• Uncommon verb in name: "Ensure name is clear and action-oriented"
• No reference files when >300 lines: "Consider splitting for better progressive disclosure"

"Run full validation checks or quick validation?"

Quick validation only checks:

• YAML frontmatter valid
• Required tags present
• No markdown headings
• Line count < 500

Full validation runs all 7 check categories above.

"The [skill-name] skill has been created and validated. How would you like to proceed?"

Options:

1. Test it now - I'll provide a sample scenario to test the skill guidance
2. Skip testing - Test it later during actual usage
3. You provide test scenario - I'll use your scenario to test the skill

Recommendation: Option 1 (testing now catches issues before delivery)

For different skill types:

• API integration skills (e.g., manage-stripe):

  Scenario: You need to create a new subscription for a customer.
  Let's invoke the skill and see what guidance it provides.
  

• Code processing skills (e.g., coordinate-subagents):

  Scenario: You need to find all files handling user authentication.
  Let's use the skill to craft an efficient subagent prompt.
  

• Data transformation skills (e.g., process-csv):

  Scenario: You have a CSV file with 10,000 rows and need to filter
  and transform specific columns. Let's test the skill's guidance.
  

• Setup/configuration skills (e.g., setup-testing):

  Scenario: You need to add testing to a new TypeScript project.
  Let's see what the skill recommends.
  

Generate scenario that exercises the skill's primary workflow.

1. Invoke the skill using the Skill tool:

   Skill: [skill-name]
   Context: [generated scenario]
   

2. Observe the response:

   • Is the guidance clear and actionable?
   • Are the steps in logical order?
   • Are examples helpful and realistic?
   • Is any critical information missing?
   • Are there any confusing or ambiguous instructions?

3. Document observations:

   Test Observations:
   ✅ Clear: [what worked well]
   ⚠️  Unclear: [what was confusing]
   ❌ Missing: [what information was needed but not provided]
   💡 Suggestions: [potential improvements]
   

"Based on the test, the skill guidance seems [assessment]. Would you like to iterate?"

Options:

1. Yes, make improvements - I'll update based on testing observations
2. No, it's good enough - Proceed to Step 8 (slash command creation)
3. Show me the issues first - Let me review before deciding

If option 1 selected:

• List specific improvements to make
• Make edits to SKILL.md or reference files
• Re-run validation (Step 6)
• Offer to test again with same or different scenario

If option 2 or 3 selected:

• Proceed to Step 8

1. Wait for user scenario: "Please describe the scenario you'd like to test with."

2. Acknowledge scenario: "I'll test the skill with: [user scenario]"

3. Invoke skill with user's scenario

4. Follow observation and iteration process as above

1. Note in output: "Testing skipped - recommend testing during first actual use"

2. Provide testing reminder:

   When you first use this skill, observe:
   - Is the guidance immediately actionable?
   - Are there any unclear instructions?
   - Is any critical information missing?
   
   If issues found, you can improve the skill by editing:
   $SKILLS_PATH/[skill-name]/SKILL.md
   

3. Proceed to Step 8

Testing adds 2-5 minutes but can save hours of confusion later.

1. Missing context: Skill assumes knowledge user doesn't have

   • Fix: Add <context> section with background

2. Steps out of order: Workflow jumps around

   • Fix: Reorder steps to follow actual execution sequence

3. Examples too abstract: Code examples don't match real use cases

   • Fix: Use more realistic, specific examples

4. Missing error handling: Doesn't address what to do when things fail

   • Fix: Add <troubleshooting> or error handling guidance

5. Terminology mismatch: Skill uses different terms than user expects

   • Fix: Add <terminology> section or adjust language

6. Too verbose or too terse: Wrong level of detail

   • Fix: Adjust based on complexity (intelligence rules)

Location: $COMMANDS_PATH/{skill-name}.md (determined in Step 0.5)

Template:

---
description: {Brief description of what the skill does}
argument-hint: [{argument description}]
allowed-tools: Skill({skill-name})
---

<objective>
Delegate {task} to the {skill-name} skill for: $ARGUMENTS

This routes to specialized skill containing patterns, best practices, and workflows.
</objective>

<process>
1. Use Skill tool to invoke {skill-name} skill
2. Pass user's request: $ARGUMENTS
3. Let skill handle workflow
</process>

<success_criteria>
- Skill successfully invoked
- Arguments passed correctly to skill
</success_criteria>

The slash command's only job is routing—all expertise lives in the skill.

Core principles: references/core-principles.md

• XML structure (consistency, parseability, Claude performance)
• Conciseness (context window is shared)
• Degrees of freedom (matching specificity to task fragility)
• Model testing (Haiku vs Sonnet vs Opus)

Skill structure: references/skill-structure.md

• XML structure requirements
• Naming conventions
• Writing effective descriptions
• Progressive disclosure patterns
• File organization

Workflows and validation: references/workflows-and-validation.md

• Complex workflows with checklists
• Feedback loops (validate → fix → repeat)
• Plan-validate-execute pattern

Common patterns: references/common-patterns.md

• Template patterns
• Examples patterns
• Consistent terminology
• Anti-patterns to avoid

Executable code: references/executable-code.md

• When to use utility scripts
• Error handling in scripts
• Package dependencies
• MCP tool references

API security: references/api-security.md

• Preventing credentials from appearing in chat
• Using the secure API wrapper
• Adding new services and operations
• Credential storage patterns

Iteration and testing: references/iteration-and-testing.md

• Evaluation-driven development
• Claude A/B development pattern
• Observing how Claude navigates Skills
• XML structure validation during testing

Prompting fundamentals:

• references/clear-and-direct.md
• references/use-xml-tags.md

• Valid YAML frontmatter with descriptive name and comprehensive description
• Pure XML structure with no markdown headings in body
• Required tags: objective, quick_start, success_criteria
• Conditional tags appropriate to complexity level
• Progressive disclosure (SKILL.md < 500 lines, details in reference files)
• Clear, concise instructions that assume Claude is smart
• Real-world testing and iteration based on observed behavior
• Lightweight slash command wrapper for discoverability

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