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

While annotations already declare readOnlyHint=true, idempotentHint=true, and openWorldHint=true, the description adds substantial behavioral context beyond them: the refusal behavior with its five enumerated refusal_reason values (not_in_source, no_tool_match, tool_error, data_truncated, llm_error), the return envelope shape including verbatim evidence quotes, and the 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, mechanism, output envelope, refusal semantics, when-to-use, and cost tradeoff. The structure flows logically from what it does to how it behaves to when to select it. The middle sentence is long, but given the complexity of the return contract it documents, the length is justified.

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?

For a grounded-answer tool with only one required parameter and complete schema coverage, the description covers everything an agent needs: what it returns on success and refusal, the cost differential vs the sibling, and the conditions under which it should be selected. Nothing critical is missing for 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?

Schema description coverage is 100%, so the schema already fully documents the 6 parameters including the question parameter with aliases. The description references routing and argument-filling mechanics but doesn't add meaningful parameter-level semantics beyond what the schema provides. Baseline 3 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 purpose: 'Hallucination-resistant answer mode for high-stakes reads.' It clearly distinguishes this tool from ask_pipeworx by emphasizing that the answer is EXTRACTED using ONLY what the tool result contains, with evidence and confidence returned. This makes the grounded-mode distinction explicit and unambiguous.

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: 'Use whenever an answer will be quoted, cited, or acted on, and the agent must not invent facts' with concrete examples (financial verdicts, legal claims, medical lookups). It also gives an explicit when-not-to-use with rationale: 'Costs one extra LLM call vs ask_pipeworx — prefer ask_pipeworx for casual lookups.' This is exemplary routing guidance.

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