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

Goes far beyond the annotations by disclosing the refusal mechanism with exact refusal_reason enum values, the success response shape including verbatim evidence, and the extra LLM call cost. The readOnly/idempotent/openWorld annotations are consistent with the description. No hidden surprises remain for the agent.

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 long but every sentence earns its place: value proposition, routing behavior, return format, refusal format, usage criteria, and cost/alternative. It is front-loaded with the core differentiator and structured logically from mechanism to outcomes to guidance.

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 fully specifies both success and refusal return shapes, which is essential for an agent to interpret results. It also covers the extra-call cost, the source count, and when to prefer a sibling, leaving no critical information missing for correct invocation and decision-making.

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 fully documents the 'question' parameter plus aliases. The description does not add meaning beyond the schema for how to phrase or constrain the question, so the baseline of 3 applies.

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, differentiated purpose: a 'Hallucination-resistant answer mode for high-stakes reads' that extracts answers only from fetched tool results. It clearly distinguishes itself from ask_pipeworx by emphasizing grounding and non-invention. The resource and behavior are unambiguous.

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: 'Use whenever an answer will be quoted, cited, or acted on, and the agent must not invent facts', with concrete high-stakes examples. It also gives the alternative: 'prefer ask_pipeworx for casual lookups', and quantifies the cost trade-off. This is exemplary routing guidance.

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