AI Skill Report Card

Generating Claude Skills

Generates complete Claude Code agent skills with proper YAML structure, workflow sections, and examples. Use when asked to "create a skill", "build a skill", or "generate skill".

A-85·Feb 9, 2026·Source: Web

Quick Start

When someone says "請幫我建立skill" or "create a skill for X":

YAML
--- name: [gerund-action] description: [Third-person description]. Use when [trigger phrases]. --- # Quick Start [Immediate actionable example] # Workflow Progress: - [ ] Step 1: [Action] - [ ] Step 2: [Action] # Examples **Example 1:** Input: [specific] Output: [specific] # Best Practices - Guideline 1 - Guideline 2 # Common Pitfalls - Don't do X - Avoid Y

Workflow

Progress:

  • Extract core action from user request
  • Convert to gerund-form kebab-case name
  • Write trigger-focused description
  • Create actionable Quick Start
  • Build step-by-step workflow with checklist
  • Add concrete input/output examples

Step 1: Name Generation Framework

  • Identify verb: "analyze" → "analyzing"
  • Add object: "analyzing-data", "writing-proposals"
  • Check length: max 64 characters
  • Validate kebab-case: lowercase + hyphens only

Step 2: Description Template Format: "[Action verb]s [object] and [outcome]. Use when [trigger phrases]."

  • "Analyzes datasets and generates insights. Use when asked to 'analyze data' or 'examine dataset'."

Step 3: Content Structure Template

  1. Quick Start: Code/steps, no explanation
  2. Workflow: Numbered steps + progress checklist
  3. Examples: Minimum 2 input/output pairs
  4. Best Practices: 3-5 actionable guidelines
  5. Common Pitfalls: What NOT to do

Examples

Example 1: Input: "幫我建立一個分析CSV數據的skill" Output: Complete SKILL.md file:

YAML
--- name: analyzing-csv-data description: Analyzes CSV datasets and generates statistical insights with visualizations. Use when asked to "analyze CSV", "examine data file", or "process spreadsheet". --- # Quick Start ```python import pandas as pd df = pd.read_csv('data.csv') print(df.describe()) df.hist()

Workflow

Progress:

  • Load and validate CSV file
  • Generate descriptive statistics
  • Create visualizations
  • Identify patterns and outliers

Step 1: Load data with error handling Step 2: Check data types and missing values Step 3: Generate summary statistics Step 4: Create relevant plots

Examples

Example 1: Input: sales_data.csv with columns: date, product, revenue Output: Summary stats, time series plot, top products

Best Practices

  • Always check for missing values first
  • Use appropriate plot types for data
  • Include data validation steps

Common Pitfalls

  • Don't assume clean data
  • Don't create too many plots

**Example 2:**
Input: "Create a skill for API documentation"
Output:
```yaml
---
name: documenting-apis
description: Creates comprehensive API documentation with endpoints, examples, and schemas. Use when asked to "document API", "write API docs", or "create API reference".
---

# Quick Start
```markdown

Creates a new user account.

Request:

JSON
{"name": "John", "email": "john@example.com"}

Response:

JSON
{"id": 123, "name": "John", "created_at": "2024-01-01T00:00:00Z"}

Workflow

Progress:

  • List all endpoints
  • Document request/response formats
  • Add authentication requirements
  • Include error codes

Examples

Example 1: Input: REST API with user management Output: Complete OpenAPI spec with examples

Best Practices

  • Include realistic examples
  • Document error responses
  • Show authentication headers

Common Pitfalls

  • Don't skip error documentation
  • Don't use fake/unrealistic data

# Best Practices

- **Name Convention**: Always gerund + object (`processing-images`, not `image-processor`)
- **Trigger Optimization**: Include exact phrases users say ("analyze this", "create docs")
- **Quick Start Rule**: First code block should be copy-pasteable
- **Example Quality**: Use realistic data, show complete workflows
- **Checklist Strategy**: Break complex tasks into trackable steps
- **Length Target**: Aim for 400-600 lines total

# Common Pitfalls

- Don't use abstract examples - show actual file contents
- Don't write "I will" or "you can" - use third person action verbs
- Don't create mega-skills - split complex domains into focused skills
- Don't forget progress checklists for multi-step workflows
- Don't explain basic concepts (what JSON is, how functions work)
- Don't provide multiple options - give the best single approach
0
Grade A-AI Skill Framework
Scorecard
Criteria Breakdown
Quick Start
11/15
Workflow
11/15
Examples
15/20
Completeness
15/20
Format
11/15
Conciseness
11/15