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

Beyond the annotations (readOnly, openWorld, idempotent), the description adds substantial behavioral detail: answers are extracted only from tool results, evidence is a verbatim quote, refusals happen with specific reasons, and one extra LLM call is incurred. It also describes the exact success and refusal return shapes. Nothing about the behavior is hidden or contradicted by 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 detailed but front-loaded with the core purpose before diving into mechanics. The routing explanation and refusal reason list are useful and earn their place. It is slightly longer than strictly necessary, but each section serves a distinct purpose for tool selection and invocation.

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 compensates by specifying the return fields, including evidence, confidence, source, and refusal_reason variants. It also covers the use case, cost tradeoff, and safe read-only nature. An agent has everything needed to decide when to invoke and what to expect.

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%, and the schema already explains the question parameter and its six aliases. The description adds general context about how the question is routed internally but no additional parameter-level detail. A baseline 3 is appropriate because the schema carries the parameter documentation burden.

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 function: a 'Hallucination-resistant answer mode for high-stakes reads,' then details the routing and extraction behavior. It clearly distinguishes this tool from ask_pipeworx by emphasizing evidence-grounded answers and explicit refusals. This is enough for an agent to know exactly what it does and how it differs from the closest sibling.

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 explicitly states when to use the tool: 'whenever an answer will be quoted, cited, or acted on' and when to avoid it: 'prefer ask_pipeworx for casual lookups.' It also references the alternative, ask_pipeworx, and explains the cost tradeoff. This gives clear routing guidance with no inference required.

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