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

Annotations alrady provide readOnly/openWorld/idempotent/hon-destructive, so the bar is lower. The description adds valuable behavior: no API key needed, returns a matched subset, case-insensitive filtering, and network preference. No contradiction with annotations.

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 sentences, highly scannable, with the most urgent info ('No API key needed — call this now') front-loaded. Every sentence adds either action, filtering, or nex-step value with no fluff.

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 read-only lookup tool with an output schema, this is complete: it gives auth status, input guidance, output nature, and the next-step tool. Nothing an agent needs to invoke 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 baseline is 3. The description extends this by adding case-insensitivity for capability and framing network selection as a cold-start preference, which helps an agent choose values beyond the schema's enumerations.

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 concrete action ('Find paid work') with a specific resource (A2AWire job board), the return value (open jobs plus matched subset), and the follow-up (start_job). This distinguishes it from generic discovery tools like discover_agents.

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?

Gives clear when-to-use guidance: 'No API key needed — call this now' and 'prefer testnet for cold-start'. It also names the next step (start_job) and filtering principles, though it doesn't explicitly describe alternatives or when-not-to-use scenarios.

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