list_databases

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

No annotations are provided, so the description carries full burden. It describes the return format (JSON string, bare array of dicts with specific keys) but does not mention any behavioral aspects like authentication, rate limits, or safety implications. For a simple listing, this is acceptable but not thorough.

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 concise and well-structured: it opens with a clear summary, then provides usage guidance, and ends with the return format. Every sentence serves a purpose with no redundancy.

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 simplicity of the tool (zero parameters, explicit return keys), the description covers all necessary information: what it does, when to use it, and what it returns. It also explicitly contrasts with the canonical sibling, making the context complete.

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 input schema is empty (0 parameters), so schema coverage is 100%. The description does not need to add parameter semantics, and the baseline for zero parameters is 4. No additional parameter info is required.

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 returns all available RDF databases with specific keys, and the verb 'list' matches the name. It distinguishes itself from the sibling 'find_databases' by noting it is a supplementary fallback for unfiltered catalog dumps.

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 explicitly states when to use this tool ('only when you need the entire catalog with no filter') and when not to ('for every normal workflow, call find_databases first'). This provides clear guidance on alternatives.

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