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

Beyond the annotations (readOnlyHint=false, destructiveHint=false, idempotentHint=false), it discloses two real behavioral traits: a connected GetMattered account is required and the call consumes the user's AI credits. It also previews the output content, though with an output schema present that is partly redundant. It does not address whether repeated identical calls re-charge credits despite idempotentHint=false, which is the one remaining gap.

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 purpose leads, the output shape follows, then prerequisites, then the exclusion and the next-step routing. Every sentence carries distinct information (capability, cost/auth, alternative, follow-on) with no filler or restatement of the tool name.

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?

For a single-input extraction tool with a published output schema, an agent needs purpose, input expectations, cost/auth preconditions, and next steps — all four are present. The description correctly avoids re-documenting return fields that the output schema already covers.

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 coverage is 100% for the single parameter, so the baseline is 3, but the description earns an extra point by clarifying that the input is the posting's own text rather than a URL, and by tying the parameter to the resume's use of the posting's language. It adds an interpretation of the parameter's expected content, not just its existence.

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 gives a specific verb+resource ('Extract the ATS keywords and requirements in a job posting') and even specifies the shape of each extracted term (category, importance, must-have flag). It explicitly separates itself from the link-reading path handled by getmattered_get_matches with job_url, so an agent can distinguish it from siblings without opening a schema.

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?

It provides an explicit when-not ('Do not use it to read a posting from a link; use getmattered_get_matches with job_url') and an explicit next step ('getmattered_score_resume or getmattered_optimize_resume with the same job description'). Both a negative routing rule and a downstream alternative are named, leaving nothing to inference.

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