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

Annotations already mark this as read-only, open-world, idempotent, and non-destructive, and the description adds important behavioral context: it costs an extra LLM call, uses only tool-result content, returns explicit refusal reasons, and shapes success/refusal output formats. This goes well beyond what annotations convey.

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: definition, routing behavior, success/refusal shapes, usage criteria, and cost tradeoff. It is well-structured and front-loaded with the core purpose and key caveat.

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 fully explains the return values and refusal reasons. It also covers when to use it, how it differs from its sibling, and operational cost, leaving no critical gap for an agent deciding whether and how to invoke it.

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 coverage is 100%, so the schema fully documents the question parameter and its aliases. The description adds context about how the question is routed, but it does not need to repeat parameter-level semantics; 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 states a specific, differentiated function: a hallucination-resistant, grounded answer mode for Pipeworx. It explicitly contrasts with ask_pipeworx by explaining that it extracts answers only from tool results and can refuse when evidence is insufficient.

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 when the agent must not invent facts. It also names the alternative ask_pipeworx and recommends it for casual lookups, making the usage boundary clear.

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