Analyze Job Description

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

Against annotations of readOnlyHint=false and idempotentHint=false, the description clarifies that no resume or settings are modified and that the only real cost is AI credits from a connected account. It doesn't address whether repeated calls consume credits again (relevant given idempotentHint=false), leaving a small 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?

Four tight sentences: purpose first, then behavioral constraints, then the exclusion, then the follow-up chain. Every clause carries differentiating information and there is no repetition of the title or schema.

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?

An output schema exists, and the description still summarizes the return shape (category, importance, must-have). Combined with the account/credit prerequisites and next-step guidance, an agent has everything needed to call 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?

With a single parameter at 100% schema coverage, the schema already defines job_description. The description adds useful semantics by implying the input is the full posting text rather than a link, which shapes the value an agent supplies.

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 uses a specific verb ('Extract') and names the exact resource and output shape (ATS keywords and requirements with category, importance, must-have flag). It also distinguishes itself from getmattered_get_matches, which handles link-based reading.

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 gives an explicit when-not ('Do not use it to read a posting from a link; use getmattered_get_matches with job_url') and concrete next-step routing to score_resume or optimize_resume with the same job description. There's no ambiguity about when this tool is the right choice.

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