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

The description adds substantial behavioral context beyond the annotations: it details the success return object, the refusal contract with specific refusal_reason enum values, the strict grounding guarantee, and the extra LLM call cost. The annotations only provide readOnly/openWorld/idempotent/destructive hints, so this description carries real behavioral weight.

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 description is front-loaded with the core purpose, then carefully structured: mechanism, return contract, usage conditions, and cost tradeoff. Every sentence adds distinct value, and no filler or redundant restatement appears.

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 no output schema, the description fully compensates by spelling out the return shape and refusal reasons. It also covers the decision-relevant cost tradeoff and usage boundaries, making the tool fully contextualized without requiring the agent to inspect schemas or infer behavior.

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 100%, so the input schema already documents all six parameters. The description speaks of 'fills arguments' and natural-language questions but does not add parameter-level detail beyond what the schema provides. This meets the baseline for high schema 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?

The description states a specific mode ('Hallucination-resistant answer mode') and a distinct behavior: it extracts answers using ONLY what the tool result contains. It explicitly compares to sibling ask_pipeworx by noting the same routing but adding grounded extraction, making the purpose unambiguous.

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 explicitly states when to use: 'Use whenever an answer will be quoted, cited, or acted on, and the agent must not invent facts.' It also gives an exclusion and alternative: 'Costs one extra LLM call vs ask_pipeworx — prefer ask_pipeworx for casual lookups.' This is clear, actionable guidance.

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