list_categories

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

The description adds value beyond the annotations by specifying the return format (dictionary with 28 items) and potential error type ('upstream_error'). The annotations already cover read-only, idempotent, and non-destructive behavior, so the description complements them well.

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 extremely concise: one sentence stating the purpose, usage hint, and error note. No superfluous information. It front-loads the key action and is well-structured.

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 no parameters and no output schema, the description covers all essential information: what is returned (dictionary, size 28, content examples), how to use the result (in search), and error handling (upstream_error). It is fully complete for this tool's complexity.

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 has no parameters, so the description's explanation of the output (dictionary mapping IDs to names) and its purpose (feeding into search) adds meaning. With zero parameters, the baseline is 4, and the description fulfills this.

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 a dictionary of EUREKA document categories (id to name) with 28 items, listing examples. It specifies the verb 'returns' and the resource 'categories'. While it does not explicitly distinguish from sibling tools, it mentions usage in search, providing context.

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 tells when to use the tool: to obtain category IDs for the search tool's category_ids parameter. This gives clear context. However, it does not mention when not to use it or provide alternatives, so it misses explicit exclusions.

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