category_members

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

With no annotations, the description carries the behavioral disclosure burden. It includes several meaningful behaviors: it returns a 1-2 sentence extract and a thumbnail URL per entry, filters out subcategories and files by limiting to main namespace, and treats the 'Category:' prefix as optional. It does not cover pagination, ordering, or error behavior, but these are minor for a list-read tool.

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 front-loads the core action, then guides to the sibling tool, then details the output, then adds a non-obvious filtering behavior, and finishes with the direct pairing. No sentence is wasted, and the flow makes it easy to scan.

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 absence of an output schema, the description supplies adequate shape information: each entry contains a title (implended by 'enumerate who's actually in it') plus an extract and thumbnail URL when available. It also shares the main-namespace filter and the prefix tolerance. Notationally, it could state ordering or pagination, but for a tool with 3 parameters and understandable semantics, this is sufficiently 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?

Schema coverage is 100%, so the baseline is 3. The description adds meaningful value: it clarifies that the category parameter accepts an optional prefix, and it explains the practical meaning of the extract and thumbnail responses that depend on the query. This goes beyond the schema's bare field descriptions.

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 uses a specific verb and resource ('List Wikipedia articles filed under a category') and immediately differentiates itself from siblings by calling out `categories` and `search`. It even names a concrete example ('Machine learning researchers'), so an agent knows exactly what the tool does without opening the schema.

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 gives clear usage context: it is the reverse of `categories`, and it pairs with `categories` (to build the taxonomy) and `search` (to find an entry point). This implies when to choose this tool over the obvious alternatives, though it does not spell out an explicit 'when not to use' list beyond that alignment.

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