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

Discloses polling behavior, return fields, auto-credit policy, and buyer visibility. Annotations already state read-only; description adds meaningful context 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 efficient sentences front-loading purpose, then additional behavior. Very concise but could be slightly more structured.

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?

Adequately covers purpose, return values, and business logic for a simple poll tool. Lacks potential error details but acceptable given low complexity.

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?

Single parameter job_id with schema description clarifying source. Description adds no extra meaning beyond schema; baseline 3 for 100% coverage.

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?

Description clearly states 'Poll a Cradle or Merge job by job_id' with specific outputs (status, result, error, refund state). Distinguishes from sibling tools like cradle_breed_agent and merge_models.

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?

Implied usage context (polling jobs created by specific tools) but no explicit when-to-use or when-not-to-use guidance.

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