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

Annotations already indicate read-only, idempotent, open-world, and non-destructive behavior. The description goes well beyond this by disclosing the exact output contract on success and failure, enumerating specific refusal reasons, and explaining the constraint that answers come only from the tool result. This is substantive behavioral information an agent would not otherwise know.

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?

Despite its length, every sentence adds operational value: the core behavior is front-loaded, the return contract is specified precisely, usage scenarios are named, and the cost comparison is included. The refusal-reason enumeration is dense but directly actionable for an agent deciding whether to retry or report failure.

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 specifies both success and failure return shapes, key fields, refusal reasons, and the extra LLM call cost. It also clarifies the relationship to the sibling ask_pipeworx tool. No critical calling information appears to be 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?

Input schema coverage is 100%, with all six parameters documented as aliases for the free-text question. The description does not add parameter-specific detail, but the schema already handles that burden fully. The baseline of 3 applies because the description adds no extra meaning beyond the schema's clear alias documentation.

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 precise purpose: a hallucination-resistant answer mode that extracts answers only from tool results. It explicitly differentiates itself from ask_pipeworx by describing the extraction and refusal behavior, making the tool's unique function unmistakable.

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.' It also names the alternative (ask_pipeworx) and gives a clear exclusion criterion: 'prefer ask_pipeworx for casual lookups.' The cost tradeoff is also stated, which helps an agent decide correctly.

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