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

Annotations already declare readOnlyHint=true, destructiveHint=false and openWorldHint=false, so the safety profile is covered — openWorldHint=false is consistent with browsing a fixed service catalog. The description adds that results are structured and may include evidence, which is useful, but it discloses nothing about pagination, catalog size, or how evidence is returned.

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 and usage context are front-loaded in the first clause, and every enumerated capability contributes to task matching rather than filler. The enumeration is long and run-on, but no sentence is redundant.

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 zero-parameter discovery tool with no output schema, the description covers what it enumerates, the nature of the results (structured, may include evidence), and the fallback path. Only minor gaps remain around result volume and the exact name of the fallback tool.

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?

There are zero parameters, so the baseline is 4; the trivial empty schema leaves nothing for the description to clarify, and it correctly implies no input filtering is required.

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 states a clear verb (discover/list) and resource (human capabilities), then enumerates concrete capability categories — phoning suppliers, price/stock checks, physical-world verification, reviewing AI output. An agent immediately understands this is a catalog of human-performed services, though the tool is not explicitly contrasted with siblings like human_create_job or human_request_quote.

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 explicit when-to-use context (tasks software cannot complete alone, information only obtainable by speaking to a person) and a routing fallback: 'If no listed capability fits, use custom-human-task.' This is strong guidance, though the named fallback does not exactly match any sibling name in the provided list, which slightly weakens the routing.

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