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

Annotations already indicate read-only, idempotent, open-world behavior, but the description adds meaningful detail: it returns evidence quotes, confidence scores, explicit refusal reasons, and incurs an extra LLM call. This goes beyond the annotations and gives the agent a clear model of the tool's safety and failure behavior.

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: purpose, routing, return format, refusal cases, use cases, and cost tradeoff are all covered without redundancy. Key information is front-loaded, and the alternative behavior is stated at the end.

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?

Despite lacking an output schema, the description explicitly documents the success return fields and all refusal reason enum values. It also covers pricing/behavioral tradeoffs and use-case boundaries, making the tool fully understandable in context. Nothing critical is missing for an agent to invoke it 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 description coverage is 100%, with all six parameters being aliases for the question input and fully documented. The description does not add parameter-level detail, but it doesn't need to because the schema already explains the aliases and natural language question format. A baseline score 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 hallucination-resistant answer mode for high-stakes reads, distinct from ask_pipeworx. It specifies the verb, resource, and key behavior: extracting answers only from tool results. It differentiates from siblings by explaining the grounded extraction process and refusal semantics.

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 this tool: whenever an answer will be quoted, cited, or acted on, and when inventing facts is unacceptable. It also names the alternative ask_pipeworx and gives a clear preference rule for casual lookups, making the selection decision unambiguous.

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