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

Annotations already declare readOnlyHint=true and openWorldHint=false, so safety is covered. The description adds real behavioral value by enumerating the filter categories that cause exclusions, telling the agent what kind of diagnosis to expect. It does not describe the shape of the returned diagnosis beyond that.

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?

Two tight sentences: the diagnosis first, then how to phrase the input with a concrete example. No filler, and the most important information is front-loaded.

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?

With no output schema, the description must imply return content, and it does so well by naming the excluded jobs and the blocking filters. Minor gap: it never explains when the optional 'place' parameter kicks in or how a missing place is resolved.

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 100%, so both 'question' and 'place' are already documented; the description only reinforces 'plain words' and supplies an example query. It adds marginal meaning beyond the schema, so the baseline of 3 applies.

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?

States a specific and unusual capability: it returns the jobs a person is NOT shown and names the personal filter (languages, level, education, eligibility, excluded companies/industries, role kinds) blocking each. That is clearly distinguishable from search_jobs and count_jobs, which only find or tally jobs.

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 purpose statement plus the worked example ('sales jobs in Amsterdam') makes the triggering scenario obvious to an agent. It stops short of naming alternatives (e.g., use search_jobs to actually list jobs) or stating when not to use it, so it is clear context without explicit routing.

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