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

Annotations already cover readOnly, idempotent, openWorld, and non-destructive, so the bar is lower. The description adds meaningful behavior: the tool can return an explicit refusal with reasons like not_in_source, no_tool_match, tool_error, data_truncated, llm_error; it discloses costing an extra LLM call; and it states the extraction uses ONLY the tool result. That is valuable behavioral context beyond the 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 every sentence earns its place: behavior, return shape, refusal reasons, usage guidance, and cost tradeoff are all packed efficiently. It is front-loaded with the key differentiator (hallucination-resistant grounded answer mode). It is appropriately sized for a tool with this much decision-relevant context.

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?

The description explains the routing pipeline, the output contract, refusal cases, when to use it, and the cost tradeoff versus the sibling. There is no output schema, so the explicit return and refusal shape is essential and fully provided. For a complex grounded-answer tool, nothing an agent needs to call it correctly is missing.

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 schema says the question parameter accepts several aliases. The description does not need to repeat parameter meanings; the one remaining gap is that it doesn't mention the aliases in prose, but the schema fully covers them. 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 states a specific verb+resource: it is a hallucination-resistant answer mode that routes through the same pipeline as ask_pipeworx and extracts grounded answers from tool results. It clearly distinguishes itself from the sibling ask_pipeworx by emphasizing grounded extraction and refusal behavior, so an agent can tell them apart without opening schemas.

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 says when to use this tool: when an answer will be quoted, cited, or acted on and the agent must not invent facts. It also gives a when-not-to-use: prefer ask_pipeworx for casual lookups because this costs one extra LLM call. It even names the sibling alternative. This is explicit routing guidance.

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