compare_models

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

Annotations were absent, so the description carries full burden for behavioral disclosure. It mentions the cost of 1 credit but does not state whether the tool is read-only, requires authentication, or has rate limits. It also does not address potential latency from fetching news. The credit cost is useful, but other behavioral aspects are missing.

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 two sentences with a clear first sentence stating purpose and outputs. It is concise and front-loaded. Minor improvement could be breaking the outputs into a list for readability, but it remains efficient.

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 has no output schema and only one parameter, the description provides a complete overview: purpose, output constituents, and cost. It does not detail error handling or edge cases (e.g., invalid IDs), but for typical usage it is sufficient.

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 covers the 'ids' parameter with 100% coverage, including examples and format. The description does not add additional meaning beyond the schema's description, only restating the purpose. With high schema coverage, a baseline of 3 is appropriate.

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 compares 2-5 AI models side-by-side and lists specific outputs (pricing, benchmarks, rankings). It effectively distinguishes this from sibling tools like get_model_pricing or benchmark_series by emphasizing the comparative aspect and the variety of returned data.

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 implies usage for comparing multiple models in detail, but lacks explicit guidance on when not to use it or alternatives. For instance, it does not mention that get_model_pricing might suffice for a single model. The context is clear enough for typical use but lacks exclusions.

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