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

Beyond the annotations, which already declare this is read-only, open-world, idempotent, and non-destructive, the description discloses the extraction-only behavior, the exact success payload, the refusal reasons, and what llm_error causes mean. It also explains the cost tradeoff, which is important behavioral context for tool selection.

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 front-loaded, starting with the core mode and then covering routing, return shape, refusal cases, and cost comparison. Every sentence carries useful selection or invocation information for a complex tool with no output schema.

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?

Although there is no output schema, the description fully describes the success and refusal return shapes, including confidence, evidence, source, fetched_at, refusal_reason, and refusal_cause for llm_error. Together with the complete parameter schema and annotations, an agent has everything needed to select and call the 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 question aliases and prefer_tool in detail. The description adds routing context but does not substantially deepen parameter semantics beyond what the schema provides, so 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 states a specific mode: hallucination-resistant grounded answers that route to a tool, fetch data, and extract an answer only from the tool result. It clearly distinguishes itself from the sibling ask_pipeworx by explaining the extra extraction step and the refusal behavior.

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 gives explicit when-to-use guidance: use whenever an answer will be quoted, cited, or acted on and the agent must not invent facts. It also names the alternative and the condition for choosing it: prefer ask_pipeworx for casual lookups because this mode costs an extra LLM call.

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