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

The annotations already mark the tool as read-only, idempotent, and non-destructive, but the description goes well beyond that by detailing the success response shape, the refusal response shape, and the exact refusal_reason values. It also discloses the extra LLM call cost. This is strong behavioral transparency with no contradiction.

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 every sentence adds value: purpose, routing behavior, response contract, refusal reasons, use cases, and cost tradeoff. It is front-loaded with the primary purpose and maintains focus throughout. No filler or redundant restatement of the tool name or schema.

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?

Given the absence of an output schema, the description thoroughly explains what the tool returns on both success and refusal paths. It also covers when to use it, how it routes, and the cost tradeoff. The input side is fully covered by the schema, so nothing essential is missing for an agent to invoke this 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 the schema already documents the `question` parameter plus all aliases in natural language. The description does not add parameter-level detail, but it does not need to since the schema fully covers that. A baseline 3 is appropriate when the schema handles parameter documentation.

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 identifies this as a 'hallucination-resistant answer mode for high-stakes reads' and explains that it routes like ask_pipeworx but extracts the answer using only the tool result. It distinguishes itself from the sibling ask_pipeworx by emphasizing grounded, evidence-based answering. This is specific enough for an agent to understand what the tool does and how it differs.

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?

The description explicitly states when to use the tool: 'whenever an answer will be quoted, cited, or acted on, and the agent must not invent facts.' It also provides clear guidance to prefer ask_pipeworx for casual lookups due to the extra LLM call cost. This gives the agent a concrete decision rule and names the alternative.

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