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

Even though annotations already mark this as readOnly/idempotent/non-destructive, the description goes beyond them: it discloses the grounded extraction behavior, the exact success and refusal return shapes, the refusal_reason enum, and the fact that it will refuse rather than guess. It also discloses the hidden operational cost of an extra LLM call. These are valuable behavioral traits not visible in 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 sentence contributes: purpose, routing, behavior, return/refusal contract, usage, and tradeoff against ask_pipeworx. The most important qualifier ('Hallucination-resistant answer mode for high-stakes reads') is front-loaded, and the rest follows logically without 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 compensates by specifying the return object and refusal object in detail. It covers when to use, when not to use, key behavioral constraints, the cost implication, and the exact failure modes. An agent has everything needed to invoke it 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 one functional parameter, question, is fully documented with aliases. The description adds no semantic detail about how to phrase the question or what makes a good query. Under the baseline rule for high schema coverage, 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 precise value proposition: 'Hallucination-resistant answer mode for high-stakes reads.' It clearly distinguishes this tool from ask_pipeworx by stating it extracts answers using ONLY the tool result and returns explicit refusals when the data doesn't directly answer. This gives an agent a clear, specific verb+resource+behavior profile.

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 it — 'whenever an answer will be quoted, cited, or acted on, and the agent must not invent facts' — and when not to, with 'prefer ask_pipeworx for casual lookups.' It even names the alternative tool and explains the cost tradeoff (one extra LLM call). This is ideal routing guidance.

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