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

Beyond the readOnly/idempotent annotations, the description discloses refusal modes with concrete refusal_reason values, states that extraction uses ONLY the tool result, and warns of the extra LLM call cost. This is exactly the behavioral context an agent needs and no contradiction with annotations was found.

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 clause adds operational value: routing, return contract, refusals, use cases, and cost tradeoff. The most important differentiator (grounded, hallucination-resistant) is front-loaded, and only the long lists of refusal reasons and example domains add modest length.

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 no output schema, the description defines the exact success shape ({answer, evidence, confidence, ...}) and every failure shape with refusal_reason values. Combined with rich annotations and full schema coverage, an agent has everything needed to invoke and interpret the result 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?

Input schema already documents the natural-language question parameter with aliases at 100% coverage, so the description is not required to add parameter details. It adds little beyond the schema here, but that is acceptable because the schema carries the full burden.

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?

Opening phrase 'Hallucination-resistant answer mode for high-stakes reads' names the verb, mode, and domain, and 'Same routing as ask_pipeworx' explicitly relates it to its sibling. It clearly identifies the tool as a grounded extractive answering tool rather than a generic search or retrieval tool.

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?

States explicit when-to-use conditions: 'whenever an answer will be quoted, cited, or acted on' and domains like financial verdicts and legal claims. It also names the alternative ask_pipeworx and the criterion for choosing it ('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.