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

Beyond the readOnly/openWorld/idempotent annotations, the description reveals critical behavioral traits: it returns either a success object with evidence/confidence/source/fetched_at or an explicit refusal with a specific refusal_reason. It also states that the tool 'EXTRACTS the answer using ONLY what the tool result contains,' making its non-inventiveness guarantee explicit.

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 earns its place: it covers routing, grounding behavior, return/refusal shapes, usage conditions, and cost tradeoff. It is front-loaded with the core value proposition and does not repeat structured annotation information.

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?

Given there is no output schema, the description fully compensates by spelling out the success shape, refusal shape, and all refusal reason enum values. It also provides routing context, cost tradeoff, and use-case boundaries, leaving no significant gap for an agent deciding or invoking the tool.

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?

The input schema already covers all six parameters at 100% and clearly documents them as aliases for the single 'question' parameter. The description does not need to add parameter detail, so the baseline of 3 applies; it neither enhances nor reduces schema clarity.

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 clearly identifies the tool as a 'hallucination-resistant answer mode for high-stakes reads,' which is a specific verb (answer/ground) plus resource (pipeworx tool results). It also distinguishes itself from ask_pipeworx by stating it follows the same routing but extracts answers only from tool-result content.

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 tells the agent when to use this tool: whenever an answer will be quoted, cited, or acted on and facts must not be invented, with concrete domains like financial verdicts, legal claims, and medical lookups. It also names the alternative (ask_pipeworx) and gives a clear preference rule: prefer ask_pipeworx for casual lookups because this mode costs an extra LLM call.

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