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

The description goes well beyond the annotations by disclosing the refusal behavior, the exact refusal_reason enum values, and the structured success response. It also states that answers are extracted using ONLY the tool result, and that grounded mode costs an extra LLM call. These are important behavioral traits not captured by 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 dense but well-organized, front-loading the core purpose, then explaining routing, return behavior, and usage guidance in a logical flow. Every sentence contributes essential information, and the cost comparison with ask_pipeworx earns its place. It is long only because it packs genuinely useful detail.

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?

Despite lacking an output schema, the description fully specifies the success return shape, refusal shape, refusal reason categories, and high-stakes use cases. It also explains the relationship to ask_pipeworx and when to prefer the cheaper sibling. For a single-parameter tool with rich behavioral nuance, this is complete.

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 covers all six parameters, with 100% description coverage, documenting 'question' and its aliases. The description adds context about the question being routed and grounded, but does not add new parameter-level semantics. A baseline score of 3 is appropriate since 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 the tool as a hallucination-resistant, grounded answer mode for high-stakes reads, using a specific verb ('extracts the answer') and a concrete resource. It explicitly distinguishes itself from ask_pipeworx by emphasizing that answers are drawn only from tool result content. This lets an agent immediately understand what the tool does and how it differs from its sibling.

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 gives explicit when-to-use guidance: 'Use whenever an answer will be quoted, cited, or acted on' and lists high-stakes domains like financial verdicts, legal claims, medical lookups, and public statements. It also names ask_pipeworx as the alternative for casual lookups and explains the cost tradeoff. This fully routes an agent to the correct tool.

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