affinda-automation
Automate Affinda tasks via Rube MCP (Composio). Always search tools first for current schemas.
Install with Tessl CLI
npx tessl i github:haniakrim21/everything-claude-code --skill affinda-automation65
Does it follow best practices?
If you maintain this skill, you can automatically optimize it using the tessl CLI to improve its score:
npx tessl skill review --optimize ./path/to/skillEvaluation — 77%
↑ 4.52xAgent success when using this skill
Validation for skill structure
Discovery
22%Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.
This description is too vague and lacks the specificity needed for Claude to effectively select it from a pool of skills. It fails to explain what Affinda actually does (document parsing, resume extraction, etc.) and provides no explicit trigger guidance. The instruction to 'search tools first' is operational advice rather than a description of capabilities.
Suggestions
Add specific capabilities that Affinda provides, such as 'Parse resumes and CVs, extract invoice data, process receipts and documents'
Add a 'Use when...' clause with natural trigger terms like 'resume parsing', 'CV extraction', 'invoice processing', 'document AI'
Remove the operational instruction 'Always search tools first for current schemas' as this belongs in the skill body, not the description
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | The description uses vague language like 'Automate Affinda tasks' without specifying what concrete actions are possible. No specific capabilities like 'parse resumes', 'extract invoice data', or 'process documents' are mentioned. | 1 / 3 |
Completeness | The description partially addresses 'what' (automate Affinda tasks) but is extremely vague. There is no 'Use when...' clause or explicit trigger guidance for when Claude should select this skill. | 1 / 3 |
Trigger Term Quality | Includes 'Affinda', 'Rube MCP', and 'Composio' as technical terms, but lacks natural user keywords. Users might say 'resume parsing', 'CV extraction', or 'document AI' rather than these product names. | 2 / 3 |
Distinctiveness Conflict Risk | The mention of 'Affinda' and 'Rube MCP (Composio)' provides some distinctiveness through product names, but 'automate tasks' is generic and could overlap with other automation skills. | 2 / 3 |
Total | 6 / 12 Passed |
Implementation
85%Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
This is a well-structured skill that efficiently guides Claude through Affinda automation via Rube MCP. The workflow is clear with proper validation checkpoints, and the content respects token budget. The main weakness is that tool call examples use placeholder syntax rather than fully concrete examples, which slightly reduces immediate actionability.
Suggestions
Replace pseudocode argument placeholders with at least one concrete, complete example showing actual Affinda-specific arguments (e.g., a real document parsing call with specific field values)
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The content is lean and efficient, avoiding explanations of what Affinda or Composio are. Every section provides actionable information without padding or unnecessary context. | 3 / 3 |
Actionability | Provides concrete tool call patterns with parameter examples, but uses pseudocode-style blocks rather than fully executable code. The argument placeholders like '/* schema-compliant args from search results */' reduce copy-paste readiness. | 2 / 3 |
Workflow Clarity | Clear 3-step workflow with explicit sequencing (discover → check connection → execute). Includes validation checkpoint for connection status and explicit instruction to confirm ACTIVE before proceeding. | 3 / 3 |
Progressive Disclosure | Well-organized with clear sections progressing from prerequisites to setup to workflow to pitfalls. External reference to toolkit docs is one level deep. Quick reference table provides efficient navigation for common operations. | 3 / 3 |
Total | 11 / 12 Passed |
Validation
90%Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.
Validation — 10 / 11 Passed
Validation for skill structure
| Criteria | Description | Result |
|---|---|---|
frontmatter_unknown_keys | Unknown frontmatter key(s) found; consider removing or moving to metadata | Warning |
Total | 10 / 11 Passed | |
- Reviewed
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