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

The description discloses key behavioral traits: it sends the job to businesses (external effect), returns a briefToken for async polling, and indicates the nature of responses (real number, coverage, validity). It does not contradict annotations (readOnlyHint=false, openWorldHint=true are consistent). It lacks some details like what triggers a match or failure behavior, but adds meaningful context beyond the annotations.

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 core action, and contains no filler. It efficiently packs in purpose, workflow, and an alternative, making every sentence valuable.

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?

Despite having 9 parameters and no output schema, the description explains the return value (briefToken), how to use it (poll compare_quotes, then accept_quote), and the goal (get multiple quotes). It doesn't detail every parameter, but the schema covers that. The workflow guidance makes the tool's context complete enough for an agent to use it correctly.

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 78%, which is high, so the schema already documents most parameters. The description does not elaborate individual parameters further, but implies that 'details' and 'customerContact' are central (since they are required) and mentions 'send it to the businesses' which relates to 'slugs'. Since the schema carries most semantic weight, a baseline score of 3 is appropriate.

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's function: 'Describe a job once and send it to the businesses that can price it.' It also distinguishes from a likely sibling by saying 'Use this instead of calling request_quote at each business separately,' making the scope (multiple businesses at once) explicit.

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 this tool versus an alternative ('Use this instead of calling request_quote at each business separately') and provides workflow context: poll compare_quotes with the returned briefToken and then accept_quote. This gives clear guidance on the tool's role in a larger process.

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