Content
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-crafted skill that provides highly actionable, clearly structured guidance for driving the Alethia MCP server. The three primary workflows are well-sequenced with validation checkpoints, the NLP phrasing guide gives exact syntax, and structured response fields are documented for agent self-repair. Minor verbosity in the trigger terms list and a few explanatory asides prevent a perfect conciseness score, but overall token efficiency is good.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The skill is mostly efficient and avoids explaining basic concepts, but some sections are slightly verbose — e.g., the 'Use when' trigger terms list is long, and some explanatory prose (like 'This is the primitive that makes Alethia a verifiable-safety framework, not just a test runner') could be trimmed. The safety classifications table and reason codes are well-structured and earn their tokens. | 2 / 3 |
Actionability | The skill provides concrete, copy-paste-ready NLP phrasings, executable JSON config, specific tool call sequences, and structured response field names. Every workflow has specific tool names and clear expected outputs. The NLP phrasing guide is particularly actionable with exact syntax examples. | 3 / 3 |
Workflow Clarity | Three distinct workflows (A, B, C) are clearly sequenced with numbered steps. Workflow A includes a self-repair loop (read suggestedFix, retry). Workflow B has explicit validation (passed: true/false) with clear guidance on what to do when validation fails. The status check as step 1 serves as a liveness checkpoint. | 3 / 3 |
Progressive Disclosure | The skill provides a concise overview with clear one-level-deep references to docs/index.md and rules/alethia.md. Content is well-organized into logical sections (workflows, NLP guide, response fields, safety, limitations) without being monolithic. The inline content is appropriately scoped for what an agent needs during execution. | 3 / 3 |
Total | 11 / 12 Passed |