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Chat Completion

chat_completion

Send prompts to OpenRouter's AI models to generate chat completions, with controls for model choice, fallbacks, and sampling parameters.

Instructions

Generate a chat completion using an OpenRouter model

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
modelNoThe primary model to use (e.g., 'anthropic/claude-sonnet-4.6'). Defaults to 'openrouter/auto'.openrouter/auto
modelsNoAn optional list of fallback models to try in order if the primary model fails.
promptYesThe prompt to send to the model
max_tokensNoMaximum tokens to generate
temperatureNoSampling temperature (0-2)
system_promptNoOptional system prompt
Behavior2/5

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

The description does not disclose behavioral traits such as fallback model handling or response format. The schema includes a 'models' fallback array, but the description makes no mention of this behavior, relying solely on the vague openWorldHint annotation.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, front-loaded sentence that efficiently states the tool's core function. Every word earns its place.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The description is minimal and does not cover return values or usage context. With no output schema and many sibling tools, the agent lacks sufficient context to confidently invoke this tool over similar ones.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so all parameters are documented. The description adds no additional parameter meaning beyond the schema, warranting the baseline score.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool generates a chat completion using an OpenRouter model, which is a specific verb+resource. However, it does not differentiate from sibling tools like chat_ensemble or chat_routed, which also generate completions.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance is provided on when to use this tool versus alternatives. There is no mention of exclusions or alternative tools, leaving the agent without direction among the several chat-related sibling tools.

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

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