cachly-mcp-server

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It effectively describes key behavioral traits: it's a read operation (implied by 'Find'), mentions infrastructure details (pgvector HNSW index, embeddings never leave Germany), and specifies authentication and tier requirements. It could improve by addressing rate limits, error handling, or response format details.

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 appropriately sized and front-loaded, starting with the core purpose, followed by technical and prerequisite details, and ending with practical examples. Every sentence adds essential information without redundancy, making it efficient and well-structured for quick comprehension.

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 (7 parameters, no annotations, no output schema), the description is mostly complete but has minor gaps. It covers purpose, prerequisites, and examples well, but doesn't explain the return format (e.g., structure of results) or potential limitations like pagination or error cases, which would be helpful since there's no output schema.

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?

The schema description coverage is high (86%), so the baseline is 3. The description adds value by providing example queries ('find all cached responses about password reset', 'what did we answer about pricing?') that illustrate the 'query' parameter's usage in natural language, enhancing understanding beyond the schema's technical description. However, it doesn't detail other parameters like 'instance_id' or 'threshold'.

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 ('Find cached entries', 'semantically similar to a natural-language query') and distinguishes it from siblings by specifying it searches cached content using semantic similarity rather than direct key-based retrieval like cache_get or cache_mget. It identifies the exact resource (cached entries) and method (semantic search).

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 provides clear context for when to use this tool (finding semantically similar cached content via natural-language queries) and includes prerequisites (OPENAI_API_KEY, Speed/Business tier, CACHLY_VECTOR_URL). However, it doesn't explicitly state when NOT to use it or name specific alternative tools from the sibling list, such as cache_get for direct key-based retrieval or detect_namespace for namespace detection.

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