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

Annotations already declare readOnly, idempotent, non-destructive, closed-world behavior. The description adds genuinely non-obvious output semantics — that no aggregate score is produced and that absence of evidence is not treated as a gap — which prevents an agent from over-reading results. It still says nothing about how evidence is sourced or how the mapping is structured.

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?

Three short sentences, front-loaded with the core action and followed by two constraint statements. Every sentence carries information; the telegraphic phrasing is slightly clipped but not padded.

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 should convey the return shape; it only indirectly signals 'a mapping without a percentage score'. For a single free-text-list parameter tool this is close to adequate, but an agent cannot predict the structure or number of mapped results.

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 0% and the single 'requirements' array has no item description, so the description carries the burden; it clarifies that each entry is an individual job requirement, which is the key semantic. It adds nothing about granularity expectations (one skill per item vs. a full sentence) despite the 3–800 char item bounds.

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 verb+resource pair ('Map individual job requirements to public professional evidence'), which tells an agent what the tool produces. It doesn't differentiate against siblings like match_problem_to_service, but the subject matter (job requirements vs. professional evidence) is distinct enough on its own.

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 two trailing sentences ('No synthetic percentage score', 'Missing evidence is not a proven skill gap') are interpretive caveats, not usage guidance. There is no statement of when to call this vs. siblings, nor any prerequisite or exclusion condition.

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