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

Annotations already declare readOnly, idempotent, and open-world, so the safety profile is covered. The description adds real context beyond that: provenance (listings come from the hiring companies' own job boards, not an aggregator) and a freshness caveat via 'hourly pay as posted', signaling pay is unnormalized. It stops short of stating freshness, deduplication, or ordering behavior.

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?

It is essentially one long but well-ordered sentence: what the tool returns, where the data comes from, the returned fields, then the optional filter. It is front-loaded and has no filler, though the parenthetical license list and source list make it denser than strictly necessary.

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 only two optional parameters, no output schema, and no nested objects, the main risk is unknown return fields — and the description enumerates them (title, pay, contract type, location, date posted). Safety behavior is handled by annotations. Minor gaps remain around result ordering, freshness, and duplicate listings across the three boards.

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 parameters (limit with default 10 and max 25, query as a title word) are already documented, and the description adds little beyond confirming the filter matches a word in the title. Baseline 3 is appropriate when the schema carries the semantics.

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 names a specific verb+resource: open, paid roles for licensed mental-health clinicians to train or evaluate AI models, and names the exact sources (micro1, Mercor, AfterQuery). It lists the clinician license types in scope and the fields returned, which lets an agent distinguish it immediately from the online-therapy-service siblings.

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?

Usage is only implied: an agent can infer this is the job-listing lookup rather than a therapy-service lookup, since no sibling covers hiring boards. There is no explicit when-to-use/when-not statement, and the only guidance is that the title filter is optional, leaving the agent to infer that omitting it returns the default set.

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