aa_compare_models

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

No annotations provided. The description only states the return format ('comparison table and per-model details') without disclosing behavioral traits like read-only nature, side effects, or rate limits. For a comparison tool, this is insufficient.

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, using two clear sentences plus structured Args/Returns. It is front-loaded with the purpose. Could be reduced to one line without losing meaning.

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 output schema exists, return values are covered. The parameter is well-defined. Lacks context about error conditions or model availability, but for a simple comparison tool with one parameter it is adequate.

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%, but the description's Args section fully explains the parameter: 'List of model ids, slugs, or names (at least 2).' This adds essential meaning beyond the raw schema.

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 'Compare multiple LLM models side by side on key metrics,' which specifies the verb (compare), resource (LLM models), and scope (multiple). This distinguishes it from siblings like aa_get_model (single model) and aa_list_llms (list all).

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?

No explicit guidance on when to use this tool versus alternatives (e.g., list vs compare). The description does not mention prerequisites or when not to use it, such as for large model lists.

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