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

The description explains the grounded/hallucination-resistant behavior, the refusal mechanism with specific refusal reason categories, and the extra LLM call cost. The annotations (readOnlyHint, openWorldHint, idempotentHint) are consistent with the read-only, non-destructive nature described. A minor gap: it doesn't explicitly describe response format details for the returned answer, but the behavioral traits are well covered.

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 well-structured, with each sentence contributing meaningful information: what it does, how it routes, return format, use cases, and cost trade-off. No filler or redundancy.

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 sibling context (ask_pipeworx exists), the description adequately explains the relationship and trade-offs. It covers return format, refusal reasons, and when to use. A slight gap is not describing what kind of questions it handles beyond 'high-stakes reads', but the examples (financial verdicts, legal claims, medical lookups, public statements) provide sufficient context.

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 schema covers 100% of parameters with descriptions, listing five aliases (q, text, input, query, prompt) all mapped to 'question' and the question property itself is described. The description adds no additional semantic detail beyond the schema, but the schema is already comprehensive.

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 states the tool is a 'Hallucination-resistant answer mode for high-stakes reads' and explains it routes like ask_pipeworx but extracts answers using only tool results. It distinguishes itself from the sibling ask_pipeworx by noting the extra LLM call cost and recommending ask_pipeworx for casual lookups.

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 says when to use this tool ('Use whenever an answer will be quoted, cited, or acted on, and the agent must not invent facts') and when to prefer the alternative ('prefer ask_pipeworx for casual lookups'). This gives clear usage guidance relative to siblings.

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