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

The description richly discloses behavior beyond annotations: it states the tool returns either a grounded answer with evidence or an explicit refusal with specific refusal_reason values. It also explains the internal mechanism (routing across 5,743 tools and extracting only from tool results). Annotations already declare readOnlyHint and openWorldHint, and the description adds substantial safety-relevant detail 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 purposeful: each clause adds a distinct fact — what the mode does, what it returns, how it refuses, when to use it, and the cost trade-off. It is front-loaded with the most important differentiator and stays well within a compact 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?

With no output schema, the description fully explains the return shape, including the refusal_reason enum and required evidence field. It also covers routing behavior, use cases, and the cost difference from ask_pipeworx. An agent has everything needed to call and interpret this tool 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?

Schema description coverage is 100%, and the schema already documents aliases for the question parameter. The tool description does not add meaning beyond the schema, but the schema fully carries the burden. 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 opens with a specific purpose: 'Hallucination-resistant answer mode for high-stakes reads.' It clearly identifies the verb (ask), the resource (Pipeworx), and the distinguishing behavior (extracts answers only from tool results). It also differentiates itself from the sibling ask_pipeworx by describing the same routing with an added extraction step.

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?

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 and alternative: 'Costs one extra LLM call vs ask_pipeworx — prefer ask_pipeworx for casual lookups.' This leaves no ambiguity about when to choose this tool over its sibling.

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