rejection_response

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

With no annotations provided, the description adds the behavioral trait that it does not count against the monthly draft limit. It also describes the output style (short, gracious, memorable) but could be more explicit about safety or side effects. However, it is sufficient for a generative writing tool.

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 very concise with two sentences. The first clearly states the purpose, and the second adds valuable nuance and a perk (draft limit). No unnecessary words.

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?

The description adequately explains the tool's purpose and output style (short, gracious). Since there is no output schema, the description compensates by describing the tone. It is complete enough for the tool's complexity, though it could briefly differentiate from the many sibling email tools.

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 provides 100% coverage with descriptions for all 5 parameters. The description does not add significant additional meaning beyond what the schema already states, such as the effect of 'keep_door_open' which is documented 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 writes a professional response to a client who chose another provider. It specifies the tone (gracious, not bitter) and distinguishes it from similar siblings like 'bid_lost_follow_up' or 'client_decline_email' by emphasizing keeping the door open.

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 states when to use (when a client has chosen another provider) and implies the context. It does not explicitly list alternatives or when not to use, but the context is clear enough for an AI agent to infer.

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