stvlynn/dingtalk-wukong-skills/skill-creator

技能创建助手

This skill provides guidance for creating effective skills.

About Skills

Skills are modular, self-contained packages that extend Claude's capabilities by providing specialized knowledge, workflows, and tools. Think of them as "onboarding guides" for specific domains or tasks—they transform Claude from a general-purpose agent into a specialized agent equipped with procedural knowledge that no model can fully possess.

What Skills Provide

1. Specialized workflows - Multi-step procedures for specific domains
2. Tool integrations - Instructions for working with specific file formats or APIs
3. Domain expertise - Company-specific knowledge, schemas, business logic
4. Bundled resources - Scripts, references, and assets for complex and repetitive tasks

Core Principles

Concise is Key

The context window is a public good. Skills share the context window with everything else Claude needs: system prompt, conversation history, other Skills' metadata, and the actual user request.

Default assumption: Claude is already very smart. Only add context Claude doesn't already have. Challenge each piece of information: "Does Claude really need this explanation?" and "Does this paragraph justify its token cost?"

Prefer concise examples over verbose explanations.

Set Appropriate Degrees of Freedom

Match the level of specificity to the task's fragility and variability:

High freedom (text-based instructions): Use when multiple approaches are valid, decisions depend on context, or heuristics guide the approach.

Medium freedom (pseudocode or scripts with parameters): Use when a preferred pattern exists, some variation is acceptable, or configuration affects behavior.

Low freedom (specific scripts, few parameters): Use when operations are fragile and error-prone, consistency is critical, or a specific sequence must be followed.

Think of Claude as exploring a path: a narrow bridge with cliffs needs specific guardrails (low freedom), while an open field allows many routes (high freedom).

Anatomy of a Skill

Every skill consists of a required SKILL.md file and optional bundled resources:

skill-name/
├── SKILL.md (required)
│   ├── YAML frontmatter metadata (required)
│   │   ├── name: (required)
│   │   ├── description: (required)
│   │   └── compatibility: (optional, rarely needed)
│   └── Markdown instructions (required)
└── Bundled Resources (optional)
    ├── scripts/          - Executable code (Python/Bash/etc.)
    ├── references/       - Documentation intended to be loaded into context as needed
    └── assets/           - Files used in output (templates, icons, fonts, etc.)

SKILL.md (required)

Every SKILL.md consists of:

• Frontmatter (YAML): Contains name and description fields (required), plus optional fields like license, metadata, and compatibility. Only name and description are read by Claude to determine when the skill triggers, so be clear and comprehensive about what the skill is and when it should be used. The compatibility field is for noting environment requirements (target product, system packages, etc.) but most skills don't need it.
• Body (Markdown): Instructions and guidance for using the skill. Only loaded AFTER the skill triggers (if at all).

Bundled Resources (optional)

Scripts (scripts/)

Executable code (Python/Bash/etc.) for tasks that require deterministic reliability or are repeatedly rewritten.

• When to include: When the same code is being rewritten repeatedly or deterministic reliability is needed
• Example: scripts/rotate_pdf.py for PDF rotation tasks
• Benefits: Token efficient, deterministic, may be executed without loading into context
• Note: Scripts may still need to be read by Claude for patching or environment-specific adjustments

References (references/)

Documentation and reference material intended to be loaded as needed into context to inform Claude's process and thinking.

• When to include: For documentation that Claude should reference while working
• Examples: references/finance.md for financial schemas, references/mnda.md for company NDA template, references/policies.md for company policies, references/api_docs.md for API specifications
• Use cases: Database schemas, API documentation, domain knowledge, company policies, detailed workflow guides
• Benefits: Keeps SKILL.md lean, loaded only when Claude determines it's needed
• Best practice: If files are large (>10k words), include grep search patterns in SKILL.md
• Avoid duplication: Information should live in either SKILL.md or references files, not both. Prefer references files for detailed information unless it's truly core to the skill—this keeps SKILL.md lean while making information discoverable without hogging the context window. Keep only essential procedural instructions and workflow guidance in SKILL.md; move detailed reference material, schemas, and examples to references files.

Assets (assets/)

Files not intended to be loaded into context, but rather used within the output Claude produces.

• When to include: When the skill needs files that will be used in the final output
• Examples: assets/logo.png for brand assets, assets/slides.pptx for PowerPoint templates, assets/frontend-template/ for HTML/React boilerplate, assets/font.ttf for typography
• Use cases: Templates, images, icons, boilerplate code, fonts, sample documents that get copied or modified
• Benefits: Separates output resources from documentation, enables Claude to use files without loading them into context

What to Not Include in a Skill

A skill should only contain essential files that directly support its functionality. Do NOT create extraneous documentation or auxiliary files, including:

• README.md
• INSTALLATION_GUIDE.md
• QUICK_REFERENCE.md
• CHANGELOG.md
• etc.

The skill should only contain the information needed for an AI agent to do the job at hand. It should not contain auxilary context about the process that went into creating it, setup and testing procedures, user-facing documentation, etc. Creating additional documentation files just adds clutter and confusion.

Progressive Disclosure Design Principle

Skills use a three-level loading system to manage context efficiently:

1. Metadata (name + description) - Always in context (~100 words)
2. SKILL.md body - When skill triggers (<5k words)
3. Bundled resources - As needed by Claude (Unlimited because scripts can be executed without reading into context window)

Progressive Disclosure Patterns

Keep SKILL.md body to the essentials and under 500 lines to minimize context bloat. Split content into separate files when approaching this limit. When splitting out content into other files, it is very important to reference them from SKILL.md and describe clearly when to read them, to ensure the reader of the skill knows they exist and when to use them.

Key principle: When a skill supports multiple variations, frameworks, or options, keep only the core workflow and selection guidance in SKILL.md. Move variant-specific details (patterns, examples, configuration) into separate reference files.

Pattern 1: High-level guide with references

# PDF Processing
 
## Quick start
 
Extract text with pdfplumber:
[code example]
 
## Advanced features
 
-**Form filling**: See [FORMS.md](FORMS.md) for complete guide
-**API reference**: See [REFERENCE.md](REFERENCE.md) for all methods
-**Examples**: See [EXAMPLES.md](EXAMPLES.md) for common patterns

Claude loads FORMS.md, REFERENCE.md, or EXAMPLES.md only when needed.

Pattern 2: Domain-specific organization

For Skills with multiple domains, organize content by domain to avoid loading irrelevant context:

bigquery-skill/
├── SKILL.md (overview and navigation)
└── reference/
    ├── finance.md (revenue, billing metrics)
    ├── sales.md (opportunities, pipeline)
    ├── product.md (API usage, features)
    └── marketing.md (campaigns, attribution)

When a user asks about sales metrics, Claude only reads sales.md.

Similarly, for skills supporting multiple frameworks or variants, organize by variant:

cloud-deploy/
├── SKILL.md (workflow + provider selection)
└── references/
    ├── aws.md (AWS deployment patterns)
    ├── gcp.md (GCP deployment patterns)
    └── azure.md (Azure deployment patterns)

When the user chooses AWS, Claude only reads aws.md.

Pattern 3: Conditional details

Show basic content, link to advanced content:

# DOCX Processing
 
## Creating documents
 
Use docx-js for new documents. See [DOCX-JS.md](DOCX-JS.md).
 
## Editing documents
 
For simple edits, modify the XML directly.
 
**For tracked changes**: See [REDLINING.md](REDLINING.md)
**For OOXML details**: See [OOXML.md](OOXML.md)

Claude reads REDLINING.md or OOXML.md only when the user needs those features.

Important guidelines:

• Avoid deeply nested references - Keep references one level deep from SKILL.md. All reference files should link directly from SKILL.md.
• Structure longer reference files - For files longer than 100 lines, include a table of contents at the top so Claude can see the full scope when previewing.

Skill Creation Process

Skill creation involves these steps:

1. Understand user intent from task history and confirm understanding
2. Create a plan-with-files TODO list and use it as the single execution tracker
3. Understand the skill with concrete examples
4. Plan reusable skill contents (scripts, references, assets)
5. Initialize the skill (run init_skill.py)
6. Edit the skill (implement resources and write SKILL.md)
7. Package the skill (run package_skill.py)
8. Iterate based on real usage

Follow these steps in order, skipping only if there is a clear reason why they are not applicable.

Step 0 (Required): Understand User Intent From Task History

This step is mandatory. Do not initialize or edit a skill before completing it.

When the user asks to create/update a skill, the request is usually based on recent task history. You must first reconstruct intent from:

• Recent task messages and outcomes (success/failure and what was corrected)
• Currently enabled skills and what they did or failed to cover
• Repeated user preferences/constraints (tone, audience, structure, boundaries)

Before moving on, provide a natural-language understanding recap to the user and ask for confirmation.

User-facing communication requirements (mandatory):

• Use natural conversational Chinese in 3-6 sentences.
• Do NOT use rigid form output, bilingual headings, or labels like "理解结果 / Understanding Summary".
• Focus on what the user really wants to reuse:
• What goal they want to turn into a repeatable capability
• Which methods/preferences from the just-finished task are worth preserving
• What skill granularity is recommended and why (capability-level, not one-off topic)
• In the first confirmation message, avoid dumping technical naming details. If needed, mention only one simple direction name.
• End with one confirmation question and wait for the user's reply.

Internal completeness checklist (for your reasoning, not a rigid user-facing template):

1. User goal
2. Context and audience
3. Reusable successful methods from task history
4. User preferences and hard constraints
5. Recommended skill granularity
6. Proposed skill direction/name

Recommended tone example:

我理解你是想把这次任务里“如何写好一类通知”的经验沉淀成可复用能力，而不是只复用这一次的具体内容。
从刚才的过程看，可复用的关键是：受众定位、语气控制、信息结构和人文关怀表达。
所以更合适的沉淀粒度是“编写通知”这类能力型技能，后续可覆盖放假通知、制度通知等相近场景。
我这样理解对吗？如果对，我们就按这个方向进入生成步骤。

You must wait for explicit user confirmation before continuing.

Step 1 (Required): Create and Maintain a Plan-With-Files TODO

This step is mandatory and happens immediately after Step 0 confirmation.

Create a TODO tracker file at:

./output/skill-creation.todo.md

Use template: