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

Annotations already mark the tool as read-only, open-world, idempotent, and non-destructive. The description adds valuable behavioral context beyond those: the extraction-only constraint, the exact success return shape with verbatim evidence, the five explicit refusal_reason values, and the extra LLM call cost. Nothing is hidden from the agent.

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 earns its place: mode, workflow, return shape, refusal reasons, use cases, and cost trade-off. The key differentiator ('hallucination-resistant') is front-loaded, and the guidance ends with a clear routing preference. No filler or repetition.

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 return values and refusal semantics. Combined with the alias coverage in the input schema and the thorough when-to-use guidance, an agent has everything needed to call this correctly, assess the result, and route between siblings.

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%, with the property descriptions already documenting that all aliases map to the natural-language question. The description does not add meaning beyond the schema, and per the baseline rule, a 3 is appropriate when the schema does the heavy lifting.

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 opens with a specific, distinguishable statement: 'Hallucination-resistant answer mode for high-stakes reads.' It then details the exact workflow (routing, argument filling, fetching, extracting only from tool result) and names the sibling it is not ('Same routing as ask_pipeworx'), so an agent can clearly tell it apart from the other ask_pipeworx variants.

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

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