openrouter_chat

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. While it mentions querying models and API access, it doesn't disclose critical behavioral traits such as rate limits, authentication requirements, cost implications, error handling, or response format. For a tool that interacts with external AI models, this is a significant gap in transparency.

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 front-loaded with the core purpose in the first sentence and efficiently expands with model examples in the second. Every sentence earns its place by clarifying scope and accessibility, with zero wasted words, making it highly concise and well-structured.

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 complexity of querying multiple AI models via an external API, no annotations, and no output schema, the description is incomplete. It lacks information on authentication, costs, rate limits, error handling, and response structure, which are crucial for effective tool use. The description does not compensate for these gaps, making it inadequate for the tool's context.

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 description coverage is 100%, so the schema already documents both parameters ('content' and 'model') with descriptions and defaults. The description adds no additional meaning beyond what the schema provides, such as examples of model IDs or prompt formatting tips. Baseline 3 is appropriate when the schema does the heavy lifting.

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 specific action ('Query ANY AI model via OpenRouter') and resource ('AI models'), distinguishing it from sibling tools like 'openrouter_models' (which likely lists models) and 'fast_ai' (which might be a simpler interface). It explicitly mentions the scope ('Access Claude, GPT, Llama, Mistral, and 100+ models through single API'), making the purpose unambiguous.

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 querying AI models via OpenRouter but doesn't explicitly state when to use this tool versus alternatives like 'fast_ai' or 'consensus'. It mentions the single API access point, which suggests a broad use case, but lacks specific guidance on prerequisites, limitations, or comparative scenarios with sibling tools.

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