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

With annotations already marking this as read-only, idempotent, and non-destructive, the description adds substantial behavioral detail: refusal behavior, refusal_reason enum, verbatim evidence, source and confidence fields, and the guarantee to use only tool-retrieved data. This goes far beyond what annotations alone communicate.

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 and mostly earns its length, with return shapes compactly specified and the cost tradeoff front-loaded near the usage guidance. There is minor redundancy between the first sentence and the later use-case sentence, but no wasted words overall.

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 tool with no output schema, the description provides everything needed for correct selection and invocation: routing behavior, success/refusal response shapes, refusal reasons, example high-stakes domains, and sibling preference. Nothing critical 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%, and the schema fully documents that all six parameters are aliases for the single required question. The description adds no per-parameter syntax or value guidance, so 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 clearly identifies this as a grounded, hallucination-resistant answer mode that reuses ask_pipeworx's routing but differs by extracting answers only from tool results. This distinguishes it from the main sibling ask_pipeworx without requiring the agent to open schemas.

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?

Explicitly states when to use it ('whenever an answer will be quoted, cited, or acted on') and when not to ('prefer ask_pipeworx for casual lookups'), including the concrete cost tradeoff of one extra LLM call. This gives the agent actionable decision criteria.

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