cachly-mcp-server

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full burden. It discloses the tool's behavior by indicating it returns reports and a prioritized list with fix instructions, but it lacks details on permissions, rate limits, or side effects. The description adds value by specifying outputs but does not fully cover behavioral traits like error handling or performance implications.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is front-loaded with the core purpose and efficiently lists reports and return values in a single, well-structured sentence. Every element (health check, reports, actionable recommendations) earns its place without redundancy, making it concise and easy to parse.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's complexity (diagnostic with one parameter) and lack of annotations or output schema, the description is reasonably complete. It explains what the tool does and what it returns, though it could benefit from more behavioral context (e.g., execution time or error cases). The absence of an output schema is partially compensated by describing the return format.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the schema already documents the single parameter (instance_id as UUID). The description does not add any meaning beyond the schema, such as explaining what an instance_id represents or how it relates to health checks. Baseline 3 is appropriate since the schema handles parameter documentation adequately.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose with specific verbs ('check health', 'get recommendations') and resource ('AI Brain'), and it distinguishes itself from siblings by focusing on health diagnostics rather than caching, learning, or recall operations. The detailed list of reports (lesson count, context entries, etc.) further clarifies its unique function.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage for health monitoring and issue resolution, but it does not explicitly state when to use this tool versus alternatives (e.g., cache_stats for cache health or get_api_status for API status). No exclusions or prerequisites are mentioned, leaving usage context inferred rather than clearly defined.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.