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

The description goes far beyond the readOnly/openWorld/idempotent annotations by disclosing the exact success return shape, the explicit refusal reasons, the grounded extraction behavior, and the extra LLM call cost. It clearly explains what happens when data is insufficient, which is critical for an agent deciding whether to trust the answer.

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: core behavior, return contract, failure modes, usage context, and cost tradeoff. It is front-loaded with the most decision-relevant trait (hallucination resistance) and avoids fluff.

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?

With no output schema, the description compensates by fully specifying the success and refusal response shapes. It also covers enough operational context—routing, evidence verbatim, confidence, cost, and when to prefer the sibling—for an agent to invoke the tool correctly in high-stakes scenarios.

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%, so the input schema fully documents the 'question' parameter and its aliases. The description adds no additional parameter semantics; the auto-fill routing behavior is mentioned but does not change how the agent should supply arguments.

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 defines a grounded, hallucination-resistant answer mode, with a specific verb ('EXTRACTS the answer') and resource (Pipeworx routing across 5,798 tools/sources). It explicitly distinguishes itself from ask_pipeworx, so an agent can tell the difference without opening other tools.

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?

Provides explicit when-to-use guidance: when an answer will be quoted, cited, or acted on, and when the agent must not invent facts. It also names the alternative (ask_pipeworx) and states the cost tradeoff, advising casual lookups to use the cheaper sibling.

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