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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and non-destructive. The description adds valuable behavioral detail beyond annotations: the exact success/refusal response shapes, the refusal_reason enumeration, the guarantee of extracting only from tool results, and the cost of one extra LLM call. It contradicts none of the annotations.

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 tightly organized: it leads with the mode's core value, explains internal behavior, specifies output/refusal shapes, then gives usage guidance and cost/alternative. Every sentence adds functional information with minimal waste.

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?

There is no output schema, but the description compensates by fully documenting the return shape, including evidence, confidence, source, fetched_at, and the full refusal_reason vocabulary. It also clarifies scope, safety, and cost, so an agent has enough context to select and invoke the tool correctly without further information.

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 the question parameter fully self-describing and its aliases documented in the schema. The description does not add parameter-level meaning beyond that, but because the schema already carries the burden, the baseline 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 names a specific verb ('ask') and resource ('Pipeworx') with a clearly defined mode: a grounded, hallucination-resistant answer mode that extracts only from fetched tool results. It distinguishes itself from the sibling ask_pipeworx by emphasizing 'ONLY what the tool result contains' while sharing routing logic, so an agent can see exactly what this variant adds.

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: high-stakes reads, quoted/cited/acted-on answers, and domains where inventing facts is dangerous, such as financial, legal, and medical lookups. It also names the alternative for casual lookups ('prefer ask_pipeworx') and even discloses the extra LLM-call cost, making the trade-off clear.

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