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

The description goes far beyond the annotations, disclosing that the tool routes across 5,798 tools, fills arguments, fetches data, extracts only from the tool result, returns a structured success payload, and emits an explicit refusal with specific refusal_reason values. This is highly transparent about what happens and what kind of failure modes exist, with no contradiction to the readOnly/idempotent 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 every sentence earns its place: it opens with the core purpose, explains the mechanism, specifies exact return/refusal shapes, gives concrete use cases, and closes with cost guidance. It is well-organized and front-loaded with the most important information.

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 having no output schema, the description fully documents the return shape, refusal reasons, and success fields. It also covers when to use it, why it differs from the sibling, the cost implication, and the kinds of high-stakes scenarios it serves. Nothing essential 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?

The description does not elaborate on the question parameter's content or format, but the input schema already covers this fully with a clear description and alias list. With 100% schema description coverage, the baseline of 3 applies; the description adds no extra parameter-level meaning beyond the schema.

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 a distinct, grounded answer mode that extracts answers only from fetched tool results, and explicitly contrasts it with ask_pipeworx. It names the resource (Pipeworx tool routing), the verb (answer with grounded extraction), and the behavioral differentiator (refusals when data is insufficient).

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 tool: whenever the answer will be quoted, cited, or acted on and hallucination is unacceptable. It also gives a direct exclusion: prefer ask_pipeworx for casual lookups, and explains 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.