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

The description goes well beyond the annotations, detailing the success response shape ({answer, evidence, confidence, source, fetched_at, refusal_reason:null}) and the explicit refusal path with specific refusal_reason values. It also discloses the internal behavior of extracting only from tool results and the extra LLM call, which is highly relevant for agent behavior. No contradiction with readOnlyHint, openWorldHint, idempotentHint, or destructiveHint.

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 detailed yet disciplined: it front-loads the core value proposition, gives the key behavioral guarantee, provides the structured return/refusal contracts, and closes with a cost-conscious routing note. Every sentence earns its place and no information is redundant with the 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 tool's complexity and high-stakes context, the description is exceptionally complete. It covers behavior, return shapes, refusal reasons, comparison to the sibling, cost tradeoff, and appropriate usage. The lack of an output schema is mitigated by the explicit response contract in the description.

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 fully documents the question parameter and its aliases. The description does not add parameter-level detail, but none is needed given the schema's clarity. A baseline of 3 is appropriate because the schema carries the parameter documentation burden.

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, grounded answer mode for high-stakes reads, with a specific verb ('EXTRACTS the answer using ONLY what the tool result contains'). It explicitly distinguishes itself from ask_pipeworx by the grounded, non-inventing behavior, making the differentiation from siblings immediate.

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 provides 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 for casual lookups, ask_pipeworx, and warns about the extra LLM call cost, giving the 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.