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

Annotations already declare readOnly, openWorld, idempotent, and non-destructive behavior. The description adds substantial behavioral detail: exactly what the tool returns on success and refusal, the refusal reasons enumerated, the verbatim-evidence requirement, and the extra-LLM-call cost. This goes well beyond what annotations alone convey.

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 and front-loaded with the core purpose, followed by return details, use cases, and cost tradeoff. It is slightly verbose with specifics like '5,743 across 1500 sources' and a long list of examples, but each sentence contributes decision-relevant information.

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 documents the full return shape on success and failure, including refusal reasons. It also covers routing behavior, use cases, limitations (extra cost), and the guideline for choosing the cheaper sibling. An agent has everything needed to invoke and interpret the 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?

The input schema already covers 100% of parameters with descriptions, including the question field and its aliases. The description adds no parameter-level meaning, so the baseline score of 3 applies: the schema does the heavy lifting and the description doesn't need to compensate.

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, differentiated purpose: a hallucination-resistant answer mode that extracts answers only from tool results and refuses when data does not directly answer. It explicitly contrasts with ask_pipeworx by describing the grounding step, making the tool's role clear even among a large sibling list.

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?

Provides explicit when-to-use guidance ('whenever an answer will be quoted, cited, or acted on... must not invent facts') and when to prefer an alternative ('prefer ask_pipeworx for casual lookups'). It also names the sibling it shares routing with, giving an agent a clear decision rule.

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