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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint false. The description adds substantial behavioral context beyond that: it costs an extra LLM call, returns a structured payload with evidence and confidence, and can explicitly refuse with enumerated refusal_reason values. This fully discloses safety-relevant and operational behavior.

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 information-dense yet every sentence serves a purpose: defining the behavior, specifying the exact return contract, listing refusal reasons, and providing cost/usage trade-offs. It is front-loaded with the core differentiator ('hallucination-resistant') and structured logically from mechanism to output to usage guidance.

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?

There is no output schema, yet the description fully specifies the success return shape ({answer, evidence, confidence, source, fetched_at, refusal_reason:null}) and all failure refusal reasons. It also covers cost implications, routing behavior, and usage boundaries, making the description complete for an agent to call 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?

Schema description coverage is 100%, and every parameter is documented as an alias for 'question' with a natural-language description. The tool description itself does not add parameter-level detail, but with full schema coverage the baseline of 3 is appropriate; the description's routing and output semantics compensate for any lack of param elaboration.

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 a specific verb ('EXTRACTS the answer') and resource ('tool result'), explaining that it is a hallucination-resistant grounded answer mode. It distinguishes itself from sibling ask_pipeworx by emphasizing evidence-only extraction and explicit refusals, 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?

Explicitly states when to 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 condition for preferring it: 'prefer ask_pipeworx for casual lookups.' This is clear when-to-use and when-not-to-use guidance.

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