Papers in a Category Region (inferred)

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

With no annotations provided, the description takes full responsibility for behavioral disclosure. It clearly reveals that the mapping is inferred rather than authoritative, notes varying confidence levels across category types, and describes the ranking and tagging of results. This provides essential context about the tool's limitations and behavior.

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 compact yet comprehensive, covering purpose, input source, reliability caveats, and output characteristics in a well-organized manner. Each sentence adds meaningful information without 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?

For a tool with no output schema, the description adequately explains what is returned (papers ranked by citation count, tagged with proximity). It also provides the necessary context about the inference limitations and input requirements, making it complete for an agent to decide when and how to use it.

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%, with both limit and category_id fully described in the schema. The description adds some context by referencing browse_taxonomy as the source for category_id, but this is already in the schema. No additional parameter semantics beyond what the schema provides.

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 identifies the tool as listing influential papers near an inferred semantic region for a PhilPapers category, using specific language ('inferred semantic region', 'SPECTER2 centroid') that distinguishes it from sibling tools like search_papers or get_related. It also explicitly states what it is NOT, reinforcing its purpose.

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?

It instructs to pass a category_id from browse_taxonomy, establishing the required input source. It also warns about reliability based on category granularity, implying appropriate use cases. However, it does not explicitly name alternative tools for different scenarios (e.g., search_papers for keyword search).

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