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

Beyond the readOnlyHint and idempotentHint annotations, the description discloses substantial behavioral detail: it only extracts from tool results, returns a structured success payload with evidence, and explicitly refuses with defined refusal_reason values when data doesn't directly answer. No contradiction exists between the description and annotations.

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: it front-loads the core purpose, explains the routing behavior, enumerates the return and refusal contracts, gives concrete use cases, and provides a cost-based comparison with the sibling. Nothing is redundant.

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?

Given there is no output schema, the description compensates by fully specifying the success return shape and all refusal reasons. It also covers practical selection context, cost tradeoffs, and use-case fit. An agent has everything needed to invoke the tool correctly and interpret its output.

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%, with all six parameters documented as aliases for the single required 'question' parameter. The description itself adds no parameter-level detail, but the schema already fully covers semantics, so baseline 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 clearly states the tool is a 'Hallucination-resistant answer mode for high-stakes reads' and explains that it routes like ask_pipeworx but extracts answers using only tool results. This is a specific verb+resource pairing, and it names the sibling it differentiates from (ask_pipeworx), making the distinction explicit.

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.' It also gives an exclusion condition: 'prefer ask_pipeworx for casual lookups' and explains the cost difference of one extra LLM call. This fully routes the agent to the correct alternative.

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