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

Annotations already indicate read-only, idempotent, open-world, non-destructive behavior. The description adds valuable context beyond that: explicit success response shape, refusal reasons, evidence as verbatim quote, and the extra LLM call cost. 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?

The description is dense but front-loaded with the core purpose, and every major behavioral point earns its place. Some repetition exists in spelling out routing steps after saying 'Same routing as ask_pipeworx', but overall it remains well-structured and focused.

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 covers the return contract and refusal cases, identifies the sibling tool and usage trade-off, and documents the aliases through the schema. An agent has enough context to invoke and interpret this tool correctly.

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% and all parameters are aliases for the single question field. The description reinforces the natural-language question expectation but does not add meaning beyond the schema's own parameter documentation. Baseline 3 is appropriate.

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 clearly states a specific mode ('hallucination-resistant answer mode for high-stakes reads') and differentiates itself from ask_pipeworx by emphasizing extraction using only tool results. The verb 'answer' plus resource and behavioral scope make the purpose unmistakable.

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 when to use: 'whenever an answer will be quoted, cited, or acted on, and the agent must not invent facts', lists high-stakes examples, and names the alternative: 'prefer ask_pipeworx for casual lookups.' This gives clear routing guidance.

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