generate_text

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

The description lacks disclosure of important behavioral traits such as network dependency, latency, authentication requirements, or side effects. It only states the basic action, leaving the agent unaware of potential costs, rate limits, or the need for configuration.

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 extremely brief (one sentence) but fails to provide enough context for a tool with four parameters. It essentially restates the tool name, making it under-specified rather than efficiently concise.

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 lack of output schema and annotations, the description is far from complete. It does not explain what the tool returns, how errors are handled, what happens if the model is not configured, or the relationship between parameters. This inadequacy would confuse an AI agent.

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?

With 0% schema description coverage and no additional explanation in the description, the agent gets no guidance on the parameters. The description does not explain what 'prompt', 'model', 'temperature', or 'maxTokens' do, nor does it mention defaults or constraints beyond what is in the schema.

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 tool generates text using an OpenAI-compatible model. It uses a specific verb ('generate') and resource ('text'), and it distinguishes well from sibling tools which focus on file operations, listing, and server health.

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?

No guidelines are provided on when to use this tool versus alternatives. For instance, there is no mention that 'list_models' should be used first to see available models, or that this tool is for generating new content as opposed to echoing or reading files.

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