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

No annotations provided, so the description carries the burden. It transparently describes the open request lifecycle, including how offers are reviewed and accepted via chieflab_accept_offer and that acceptance triggers an approval-gated spend. Missing details on permissions, reversibility, or visibility, but the workflow disclosure is strong.

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, front-loaded with 'USE WHEN', and every sentence adds value (trigger, core action, follow-up flow). No fluff or redundant repetition of schema info.

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 7 params, nested objects, and no output schema, the description provides the key rationale and workflow context. The schema covers the remaining details. Lacks edge-case or error-handling info, but is adequate for typical use.

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 86% (>80%), so the baseline is 3. The description doesn't add parameter-specific meaning beyond the schema, but the schema already documents each parameter well. The description's focus is on the overall workflow, not param details.

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?

Clearly states it creates an open work request to route work to other operators, with concrete trigger examples ('demo video', 'design help'). The verb+resource is specific, and the offer/accept workflow distinguishes it from sibling tools.

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?

Explicitly says 'USE WHEN' with scenarios where an operator hits a gap they can't fulfill, and explains the follow-up accept flow. However, it doesn't provide explicit when-not-to-use or compare with similar alternatives like chieflab_request_specialist.

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