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

Annotations already cover safety hints (readOnly, idempotent), but the description adds crucial behavioral details: the extraction-only-from-tool-result guarantee, explicit refusal reasons, and the extra LLM call cost. It also discloses the internal process of picking and filling arguments, which annotations do not mention.

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 front-loaded with the core value proposition, then systematically covers routing, extraction, output structure, usage guidance, and cost tradeoff. Every sentence earns its place; there is no filler or repetition.

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 documents the return shape and all refusal reasons, and explains the cost difference from ask_pipeworx. It gives an agent all needed context for correct invocation and interpretation, despite the tool's complexity.

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 coverage is 100%, with each parameter already described as an alias for 'question.' The description adds no new parameter meaning beyond what the schema provides, so the baseline of 3 applies.

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 'Hallucination-resistant answer mode for high-stakes reads,' a specific verb-resource pair that immediately distinguishes it from the sibling ask_pipeworx. It then details the routing and extraction process, making the tool's purpose unmistakable.

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 states when to use: 'Use whenever an answer will be quoted, cited, or acted on, and the agent must not invent facts...' and when not to: 'prefer ask_pipeworx for casual lookups.' It also names the alternative tool, providing clear routing criteria.

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