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

Beyond the annotations, the description discloses the full success return shape, the refusal shape with enumerated refusal reasons, the constraint that the answer uses only tool-result content, and the extra LLM call cost. This gives the agent a complete behavioral model without needing an output schema.

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?

Every sentence in the description carries high-value operational information: purpose, mechanism, return contract, refusal contract, usage triggers, and cost tradeoff. The critical purpose and differentiation are front-loaded, and the length is justified by the tool's complexity.

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?

Despite having no output schema, the description fully documents what the tool returns and how it behaves, including refusal cases. It also covers cost, safety, and when to prefer an alternative, making this a self-sufficient definition.

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%, and the question parameter plus aliases are already fully documented in the schema. The description does not add parameter-level meaning, but it doesn't need to because the schema already carries that burden.

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 identifies a specific mode ('hallucination-resistant answer mode') and a specific behavior: extracting answers only from tool results with verbatim evidence. It explicitly distinguishes itself from ask_pipeworx, so an agent can tell what this tool does versus its sibling.

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 guidance ('quoted, cited, or acted on', 'must not invent facts'), names the alternative (ask_pipeworx), and provides a when-not-to-use condition ('prefer ask_pipeworx for casual lookups'). This is exactly the kind of routing guidance agents need.

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