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

Beyond the annotations (readOnly, idempotent, non-destructive), the description discloses the key behavioral contract: success returns a specific shape with an evidence verbatim quote and confidence, while failure returns an explicit refusal with a concrete refusal_reason enum. It also explains the grounding mechanism and extra LLM call cost. No contradiction with 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: purpose, routing comparison, output/refusal contract, high-stakes use cases, and cost tradeoff. The core identity is front-loaded in the first sentence, and no filler is present.

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 covers the return contract, refusal behavior, use cases, and tradeoff relative to ask_pipeworx. It is complete enough despite the lack of an output schema. A small gap is that the sibling ask_pipeworx_beta is not mentioned or differentiated, but this does not seriously impair correct invocation.

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 fully documents the single semantic parameter question and lists all five aliases with 100% coverage. The description does not add parameter-level meaning, so the baseline score 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 opens with a specific, distinctive purpose: 'Hallucination-resistant answer mode for high-stakes reads.' It then differentiates itself from ask_pipeworx by explaining that it routes the same way but additionally extracts the answer using only the tool result, with verbatim evidence and refusals.

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 explicitly states when to use it: 'whenever an answer will be quoted, cited, or acted on' and when not to: 'prefer ask_pipeworx for casual lookups.' It also gives a cost-based tradeoff ('Costs one extra LLM call'), making the decision between the grounded variant and the standard variant concrete.

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