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

Beyond the readOnly/idempotent/non-destructive annotations, the description discloses that answers are extracted only from tool results, that refusals occur with specific reasons, and that it costs an extra LLM call. It also enumerates the refusal_reason enum, giving strong transparency into 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?

The description is information-dense but well-structured, front-loading the core purpose and then layering usage, return format, and cost tradeoff. It is longer than minimal, but nearly every sentence adds operational value and no sentence is redundant.

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?

With no output schema present, the description compensates thoroughly by specifying the success response fields, the refusal response variants, and the exact refusal_reason values. Combined with full schema coverage for the input, an agent has everything needed to invoke and interpret this tool correctly.

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% and the schema fully documents the single meaningful parameter with aliases. The description adds no additional parameter-level details, but that is acceptable because the schema carries the 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 this as a hallucination-resistant answer mode for high-stakes reads, with a specific verb/resource relationship and explicit distinction from ask_pipeworx. It states what the tool does, the exact return shape, and when it should be preferred, making sibling differentiation immediate.

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 explicitly says to use this tool when an answer will be quoted, cited, or acted on and facts must not be invented, and explicitly recommends ask_pipeworx for casual lookups due to the extra LLM call. This gives agents a clear decision rule and names the alternative.

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