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

Beyond the readOnly/idempotent/non-destructive annotations, the description discloses material behavior: no AI model, fixed lists plus the posting's own terms, results are general recruiter practice rather than a guarantee, and it never reads LinkedIn or any site — the pasted text is used only for the duration of the call. These are exactly the caveats an agent needs to set user expectations and handle privacy concerns.

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 core purpose is front-loaded in the first clause, and every sentence carries information (inputs, outputs, limits, data handling). It is a dense single block rather than scannable, and the run of related caveats could be tightened, but there is little genuine filler.

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 5-parameter tool with an output schema and full schema coverage, the description is more than complete: it enumerates the return payload (per-role variant/skill/tool/seniority words, example boolean string and match result, headline/About tips), states input modes, and flags data-handling and non-guarantee limits. Nothing needed to call it correctly is missing.

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%, so the baseline is 3, but the description adds relational meaning: it explains the two targeting modes ('targetTitles or company and job') and notes the applyUrl/title as the expected value for job. It omits the optional 'level' parameter, which only the schema documents.

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 opens with a specific verb+resource: comparing recruiter/LinkedIn keywords against a profile's text, headline, About or resume. It also distinguishes itself from siblings by naming find_company_jobs as the source of the applyUrl and by framing itself as a keyword-gap check rather than a fit score or job ranking.

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 concrete triggering questions ('does my profile have the right keywords', 'what words am I missing', 'how do I make my headline findable') and states the required input pattern (profileText plus either targetTitles or company+job). It does not, however, explicitly say when NOT to use it versus close siblings like job_fit_brief or rank_jobs_for_profile, so alternatives are implied rather than named.

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