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

The annotations already declare readOnlyHint, openWorldHint, and idempotentHint, but the description still adds substantial behavioral context: it discloses the extra LLM call cost, the strict evidence-only extraction policy, the exact success return shape, and the explicit refusal behavior with a detailed refusal_reason enum. Nothing contradicts the annotations, and the description adds value well beyond them.

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: it front-loads the core concept, then explains routing, extraction, return values, refusal cases, usage guidance, and tradeoff against the sibling in a logical order. 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?

For a tool with no output schema, the description is remarkably complete: it covers the success response shape, all refusal reasons, the relationship to ask_pipeworx, and the cost tradeoff. The complexity is high (routing across 5,714 tools, extraction, refusal logic), and nothing needed to invoke or interpret this tool's result is missing.

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%, with all six parameters documented as aliases for 'question'. The schema already handles parameter semantics fully. The description does not add any parameter-level detail, so the baseline of 3 applies.

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?

Names a specific mode ('Hallucination-resistant answer mode for high-stakes reads') and explicitly distinguishes it from its sibling ask_pipeworx by describing the same routing but a different extraction behavior ('EXTRACTS the answer using ONLY what the tool result contains'). An agent can clearly tell what this tool does and how it differs from the sibling without opening the schema.

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, public statements), and gives a direct alternative ('prefer ask_pipeworx for casual lookups') with a cost-based reason ('Costs one extra LLM call vs ask_pipeworx').

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