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

The description fully discloses the success return structure (answer, evidence, confidence, source, fetched_at, refusal_reason) and the refusal return structure with specific refusal_reason enum values. It also notes the extra LLM call cost. Annotations declare readOnly/idempotent, and the description adds meaningful behavioral context without contradicting them.

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: purpose, routing mechanism, output contracts, refusal reasons, usage context, and cost tradeoff are all covered without redundancy. The key risk property 'Hallucination-resistant' is front-loaded, followed by immediate contrast with the sibling tool.

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?

Since there is no output schema, the description compensates by fully specifying the return object and all refusal_reason values. It also covers routing scope, high-stakes use cases, and the performance/cost tradeoff. Nothing critical for correct invocation is missing.

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 the 'question' parameter with aliases and natural-language description. The tool description adds no parameter-level meaning beyond what the schema provides, so the 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 states a specific purpose: hallucination-resistant answering for high-stakes reads, and explicitly contrasts itself with ask_pipeworx by saying 'Same routing as ask_pipeworx' but 'EXTRACTS the answer using ONLY what the tool result contains.' It clearly identifies the tool's unique behavior of grounding answers strictly in tool results, distinguishing it from siblings.

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 ('whenever an answer will be quoted, cited, or acted on, and the agent must not invent facts') and when-not-to-use guidance ('prefer ask_pipeworx for casual lookups'). It names the alternative tool and even explains the cost tradeoff ('Costs one extra LLM call vs ask_pipeworx').

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