query_models

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

No annotations are provided, so the description carries full burden. It only says 'filter by provider, type, or modality support' which adds minimal behavioral info. It omits return format, pagination, error handling, and any side effects. The schema details parameters but not overall 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?

Two sentences with no wasted words. The purpose is front-loaded, and every part is functional. It efficiently conveys the tool's action and filter options.

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?

Despite 6 parameters and no output schema, the description does not explain what the response contains (e.g., model IDs, full details). It also lacks usage constraints, limits, or pagination behavior. For a search tool, this leaves significant gaps in understanding.

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 baseline is 3. The description summarizes filter dimensions ('provider, type, modality support') but does not add significant meaning beyond what the schema already provides. The mapping from 'type' to 'model_type' is clear, but no extra context.

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 the specific verb 'Search and filter' and clearly identifies the resource as 'AI models available via API'. It distinguishes from sibling tools (compare_models, get_model, list_model_ids) by focusing on search/filter versus comparison, single retrieval, or ID listing.

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 when to use (when needing to find models by criteria) but does not explicitly state when not to use or provide alternatives. It mentions filter dimensions but lacks guidance on choosing between this and siblings like get_model for exact model lookup.

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