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

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint, so the description is not burdened with stating safety. It adds useful behavioral detail: matching returns up to `limit` canonical models and includes gateway counts, free availability, and cost previews based on token usage.

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 filler. The primary action is front-loaded, return-value highlights are compact, and the routing instruction to compare_model_prices is placed at the end without bloating the description.

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 read-only, idempotent lookup tool with no output schema, the description adequately covers what the agent gets back and how parameters affect results. Minor omissions like ordering or exact slug format are not critical given the explicit return summary.

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 75%, and the description compensates well by explaining `limit` semantics ('Returns up to `limit` canonical models') and tying `inputTokens`/`outputTokens` to the 'cheapest monthly bill.' This adds value beyond the schema for the parameter that lacked a description.

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 states a specific action ('resolve a loose model name to canonical slugs') and clearly differentiates the tool from siblings like search_models and compare_model_prices. The mention of returning limit, gateway counts, free counts, and cheapest bill makes its purpose concrete.

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 explicitly says to use this tool 'before compare_model_prices when you only have a rough name,' giving a clear usage scenario and a named alternative. It does not exhaustively rule out other siblings like search_models or estimate_cost, but the guidance is strong.

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