get_comps

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

No annotations are provided, so the description carries the full burden. It discloses the embedding-based similarity method and the return format, which is transparent. It does not mention authorization or error cases, but remains informative for a read-only 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 about 6 sentences, well-structured with a clear purpose, technical detail, usage context, and parameter/return specs. Every sentence adds value, 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 tool's complexity (2 params, no nesting) and the presence of an output schema, the description covers purpose, method, usage, parameters, and return fields. It lacks error handling details, but the completeness is high for a straightforward tool.

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 0%, meaning no descriptions in the schema. The description compensates by explaining both parameters: appid is the Steam app ID, k is the number of comps (1-20, default 5). This adds full semantic value.

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 it fetches top-K nearest-neighbor comparable Steam games for an appid. It specifies the resource (comps) and action (fetch), and distinguishes from sibling tools like boxleiter_estimate by focusing on comps rather than estimation.

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 a specific use case: 'sanity-checking a forecast.' It explains why comps are useful but does not explicitly state when not to use it or mention alternative tools. However, the context is clear enough for appropriate selection.

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