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

Annotations already indicate read-only, idempotent, non-destructive behavior, so the description goes beyond by disclosing the extra LLM call cost, the structured success and refusal responses, the specific refusal reasons (not_in_source, no_tool_match, tool_error, data_truncated, llm_error), and the guarantee to use only tool-returned data. No contradiction with annotations exists.

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 each sentence earns its place: mode, routing behavior, output shape, refusal behavior, usage guidance, and cost trade-off. It is front-loaded with the core purpose and the reader never has to hunt for key facts.

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 specifies the success return shape and the refusal shape with enumerated reasons. It also covers cost, use cases, and the relationship to its sibling, making it complete for an agent to decide when to call it and what to expect.

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 coverage is 100%, and the schema describes the question parameter and its aliases. The description adds little about parameter semantics beyond saying the tool 'fills arguments' internally, but it does not need to compensate because the schema already fully documents the single meaningful input.

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 this as a hallucination-resistant answer mode for high-stakes reads, with a specific verb ('answer') and resource (Pipeworx). It explicitly distinguishes itself from the sibling ask_pipeworx by describing the same routing but a stricter extraction behavior ('EXTRACTS the answer using ONLY what the tool result contains').

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 provides explicit when-to-use guidance: 'Use whenever an answer will be quoted, cited, or acted on, and the agent must not invent facts' with concrete examples. It also names the alternative and gives the trade-off: 'Costs one extra LLM call vs ask_pipeworx — prefer ask_pipeworx for casual lookups.'

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