Evaluating & Creating Skills

Quick Start

1. Validating: Run skills validate <skill-dir> for structural checks
2. Scoring: Run python scripts/score-skills.py <skill-dir> for spec-grounded LLM evaluation

When to Use This Skill

• User wants to create a new skill
• User asks to review or evaluate an existing skill
• User needs help with skill format or structure
• User asks about skill best practices
• User wants to refactor or improve a skill
• Keywords: "skill", "SKILL.md", "create skill", "evaluate skill", "skill quality"

Authoritative References

The scorer grounds evaluation against these live documents (with vendored snapshot fallback):

• Specification - Field constraints, structure rules
• Best Practices - Quality criteria
• Evaluating Skills - Evaluation methodology

Skill Anatomy

skill-name/                    # Gerund form (verb-ing)
├── SKILL.md                   # Main documentation (<500 lines)
└── references/                # Optional detailed references
    ├── topic-1.md            # One level deep only
    └── topic-2.md

Frontmatter (Required)

---
name: skill-name                    # Gerund, lowercase, hyphens, max 64 chars
description: "Third person description with trigger keywords. Max 1024 chars."
---

Description Rules:

• Third person: "Analyzes data..." not "I help you..."
• Include trigger keywords for agent activation
• Describe what AND when to use

Recommended Section Order

Section	Purpose	Guidelines
Quick Start	Immediate value	2-5 lines, actionable
When to Use	Activation triggers	Bullet points, keywords
Core Concepts	Mental models	Build understanding
Workflow/Procedures	Step-by-step	Progressive complexity
Examples	Concrete patterns	Code blocks, scenarios
Common Pitfalls	Mistakes to avoid	5-10 items
References	Deep dives	Link to references/ with trigger context

Skill Types & Patterns

Exploratory Skills

Explain concepts, provide reference material, build mental models.

• Lead with fundamentals
• Include terminology glossary
• Show common patterns

Procedural Skills

Step-by-step guides for completing tasks.

• Start with quick start
• Show code examples early
• Progress simple → complex

Decision/Framework Skills

Help make choices between options.

• Lead with decision trees (ASCII)
• Provide decision matrices
• Include keyword signals

Analytical Skills

Interpret data or outputs.

• Explain interpretation frameworks
• Pattern recognition guidance
• Good vs bad examples

Evaluation Checklist

Frontmatter

• Name uses gerund form (verb-ing)
• Name is lowercase with hyphens only
• Name matches directory name
• Description is third person
• Description includes trigger keywords
• Description < 1024 characters

Structure

• SKILL.md body < 500 lines
• Total skill < 5000 tokens
• References one level deep only
• Has Quick Start section
• Has When to Use section

Content Quality

• Paragraphs 3-5 lines max
• Uses headers for organization
• Code in fenced blocks with language
• Tables for comparisons
• Concrete examples (not abstract)
• No time-sensitive information
• Consistent terminology

Common Pitfalls

• Includes pitfalls section
• 5-10 specific mistakes
• Explains why they're wrong

Creating a New Skill

Step 1: Choose the Name

Good: analyzing-data, creating-reports, managing-users
Bad:  data-analysis, report-creator, user-management

Use gerund form (verb + -ing). The action should be clear.

Step 2: Write the Description

Template:

"{Verb}s {what} for {purpose}. Use when {trigger conditions}."

Example:

"Analyzes chart visualizations to extract insights. Use when interpreting
dashboards, identifying trends, or explaining data patterns to stakeholders."

Step 3: Structure Content

1. Start with Quick Start (2-5 actionable lines)
2. Add When to Use (bullet list of triggers)
3. Write core content (concepts, workflows, examples)
4. Add Common Pitfalls
5. Move detailed content to references/ with loading triggers (e.g. "Read when implementing X")

Step 4: Validate

Run through the evaluation checklist above.

Using the Scorer

Validate Only (fast, no LLM)

uv run python scripts/score-skills.py <skill-dir> --validate_only

Full Scoring (with spec grounding)

uv run python scripts/score-skills.py <skill-dir>

Batch All Skills

uv run python scripts/score-skills.py . --scan_all

Common Pitfalls

1. First-person descriptions - Use "Analyzes..." not "I analyze..."
2. Missing trigger keywords - Agents can't find the skill
3. Too long SKILL.md - Move details to references/ and add trigger context (e.g. "Read when working with X")
4. Nested reference folders - Only one level allowed
5. Abstract examples - Use concrete, real scenarios
6. Noun-form names - Use "analyzing-data" not "data-analyzer"
7. No Quick Start - Users abandon without immediate value
8. Inconsistent terminology - Pick terms and stick with them
9. Missing pitfalls section - Helps users avoid mistakes
10. Time-sensitive content - Skills should be evergreen

References

• skill-checklist.md - Read when scoring or reviewing a skill to get the full rubric breakdown, anti-patterns, and evaluation template
• examples.md - Read when creating a new skill or refactoring an existing one to see concrete patterns from well-designed skills