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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is clear. The description adds that the tool returns provider, endpoint, and capabilities, and that it lists models from ia-qa.com. It does not disclose pagination or rate limits, but for such a simple tool this is adequate. No contradiction exists.

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, front-loaded with the primary purpose and output fields. The second sentence explains filtering and usage examples. Every phrase adds value, with no fluff or 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 low complexity (one optional parameter), strong annotations, and the existence of an output schema, the description is sufficiently complete. It covers the main behavior, output scope, and typical use cases without needing to explain return structures.

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 schema already documents the optional 'provider' parameter at 100% coverage, including examples. The description adds meaning by explaining the filtering effect and explicitly stating that omitting the parameter returns the full catalog, which is not apparent from the schema alone.

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 action ('List'), the resource ('LLM models available on ia-qa.com'), and the output fields (provider, API endpoint, capabilities). It accurately conveys the tool's purpose but does not explicitly differentiate it from closely related sibling tools like 'model_info' or 'compare_models', which also deal with LLM models.

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 explicit use cases: 'discover which models are available before calling an LLM API, or to compare providers.' This gives clear context for when to use the tool, though it does not explicitly mention alternatives or when not to use it.

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