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

Discloses substantial behavioral details beyond the annotations: extraction is limited to tool results, the refusal contract is fully enumerated, and the output includes evidence, confidence, source, fetched_at, and refusal_reason. The description enriches rather than contradicts the readOnly/idempotent 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 clause earns its place: purpose, routing, extraction constraint, output/refusal contract, usage guidance, and cost tradeoff. The most important framing ('hallucination-resistant answer mode for high-stakes reads') is front-loaded.

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?

For a tool with no output schema, the description fully covers return shape, failure modes, when to invoke it, and cost implications. Nothing needed to select and call it correctly 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%, so the baseline is 3. The description does not add parameter-level detail beyond what the schema already provides, though it usefully indicates that routing and argument-filling behavior match ask_pipeworx.

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 names a specific verb-resource pair ('answer mode for Pipeworx') and immediately contrasts it with ask_pipeworx, making the tool's unique role clear. It states what it does, how it differs, and when it should be preferred over the sibling 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?

Explicitly says when to use (high-stakes, quoted/cited/acted-on answers) and when not to (casual lookups, prefer ask_pipeworx). The cost tradeoff of one extra LLM call is also disclosed, giving the agent a clear decision rule.

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