Generated
Validation
Total
13/16Score
Passed| Criteria | Score |
|---|---|
description_trigger_hint | Description may be missing an explicit 'when to use' trigger hint (e.g., 'Use when...') |
metadata_version | 'metadata' field is not a dictionary |
body_steps | No step-by-step structure detected (no ordered list); consider adding a simple workflow |
Implementation
Suggestions 2
Score
73%Overall Assessment
This skill excels at progressive disclosure and conciseness, providing a clean overview that efficiently points to detailed resources. However, the actionability suffers from incomplete code examples (undefined processWithLLM function), and the workflow for actually building and deploying an agent is not clearly sequenced.
Suggestions
- Replace the Quick Start with a complete, executable example that doesn't reference undefined functions like `processWithLLM`
- Add a brief numbered workflow showing the steps to create, configure, and deploy a basic agent (e.g., 1. Create project, 2. Configure wrangler.toml, 3. Implement agent, 4. Deploy)
| Dimension | Score | Reasoning |
|---|---|---|
Conciseness | 3/3 | The content is lean and efficient, providing only essential information without explaining concepts Claude already knows. No verbose explanations of what agents, tools, or LLMs are. |
Actionability | 2/3 | The Quick Start provides executable TypeScript code, but the `processWithLLM` function is undefined/pseudocode. The Agent Pattern section is also incomplete - it shows structure but not actual implementation. |
Workflow Clarity | 2/3 | For a simple overview skill, the structure is adequate, but there's no clear workflow for building an agent from scratch. No validation steps or sequence for setting up the environment, configuring wrangler, or deploying. |
Progressive Disclosure | 3/3 | Excellent organization with clear one-level-deep references. Resources are well-categorized (Core Documentation, Integration Guides, Advanced Features, Templates) with helpful line counts and descriptions. |
Activation
Suggestions 3
Score
33%Overall Assessment
The description identifies a specific platform (Cloudflare Workers) and technology stack but relies on technical jargon without concrete actions or explicit usage triggers. The lack of a 'Use when...' clause significantly weakens its utility for skill selection, and the feature list reads more like marketing copy than actionable guidance.
Suggestions
- Add a 'Use when...' clause with explicit triggers like 'Use when building serverless AI agents, deploying to Cloudflare Workers, or integrating MCP tools with edge functions'
- Replace abstract features with concrete actions: 'Create and deploy AI agents, configure MCP tool connections, set up LLM provider authentication'
- Include natural user terms like 'serverless agent', 'edge AI', 'Workers AI', or 'wrangler' that users would actually say when needing this skill
| Dimension | Score | Reasoning |
|---|---|---|
Specificity | 2/3 | Names the domain (AI agents on Cloudflare Workers) and lists some capabilities (MCP integration, tool use, LLM providers), but these are high-level features rather than concrete actions like 'create', 'deploy', or 'configure'. |
Completeness | 1/3 | Describes what the skill does but completely lacks a 'Use when...' clause or any explicit trigger guidance for when Claude should select this skill. |
Trigger Term Quality | 2/3 | Includes relevant technical terms like 'AI agents', 'Cloudflare Workers', 'MCP', 'LLM providers', but missing common user phrases like 'deploy agent', 'serverless AI', 'edge AI', or file extensions/project types users might mention. |
Distinctiveness Conflict Risk | 2/3 | 'Cloudflare Workers' provides some distinctiveness, but 'AI agents', 'MCP integration', and 'LLM providers' are broad terms that could overlap with other agent-building or MCP-related skills. |
- Repository
- github.com/secondsky/claude-skills
- Last updated
- Created
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