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

Beyond the readOnly/openWorld/idempotent annotations, the description adds substantial behavioral detail: it returns evidence quotes, explicit refusal reasons, and never invents facts. It also fully specifies both success and refusal shapes, including the exact refusal_reason enums.

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?

Every sentence in the description carries operational value: purpose, routing behavior, output shape, refusal modes, when-to-use, and cost tradeoff. It is front-loaded with the core 'grounded answer' identity and remains structured while covering a no-output-schema tool.

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?

Given there is no output schema, the description compensates by specifying both the success payload and refusal payload explicitly. Combined with the annotations and a single obvious required parameter, an agent has everything needed to select and invoke 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 description coverage is 100% and the schema already documents the required 'question' plus all aliases. The tool description does not add parameter-level detail, but it doesn't need to; the baseline of 3 applies because the schema does the heavy lifting.

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 opens with a specific verb and mode — 'Hallucination-resistant answer mode for high-stakes reads' — and explains that it routes like ask_pipeworx but extracts answers only from tool results. This clearly distinguishes it from the sibling ask_pipeworx and from casual lookups.

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?

It explicitly states when to use this mode ('whenever an answer will be quoted, cited, or acted on') and lists high-stakes examples. It also gives the exclusion: 'prefer ask_pipeworx for casual lookups', including the cost tradeoff of one extra LLM call.

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