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

The description adds substantial behavior beyond annotations: it explains the grounded extraction mechanism, the structured success return with verbatim evidence, the explicit refusal cases with specific refusal_reason values, and the extra LLM call cost. This aligns with the readOnly and idempotent annotations and enriches agent understanding of failure modes.

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?

Every sentence earns its place: purpose, mechanism, return contract, usage guidance, and cost tradeoff are all covered in a compact, front-loaded description. There is 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 complex grounded-read tool with no output schema, the description is complete: it covers success shape, refusal reasons, use cases, alternatives, and cost. An agent has enough information to invoke it correctly and interpret both success and refusal outcomes.

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 documents the question parameter and its aliases. The tool description itself does not add parameter semantics beyond mentioning that the tool fills arguments, but with full schema coverage the baseline of 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 states a specific verb and resource: it is a hallucination-resistant grounded answer mode that routes through Pipeworx and extracts answers only from fetched tool results. It explicitly contrasts itself with ask_pipeworx, making its identity and differentiation clear.

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 when answers will be quoted, cited, or acted on and facts must not be invented, citing examples like financial verdicts and legal claims. It also names ask_pipeworx as the preferred alternative for casual lookups, so the agent knows when not to select this tool.

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