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

Annotations already carry readOnly/openWorld/idempotent/non-destructive hints, and the description adds substantial behavior beyond them: the exact success payload shape, the explicit refusal contract with enumerated refusal_reason values (not_in_source, no_tool_match, tool_error, data_truncated, llm_error), the guarantee that extraction uses ONLY the tool result, and the extra-LLM-call cost tradeoff. This tells the agent precisely what will happen when data is insufficient — no hallucination, an explicit refusal.

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: mode identity, routing mechanics, success shape, refusal shape, usage trigger, and cost tradeoff. The key differentiator is front-loaded. It is slightly long, but for a tool with this much behavioral nuance — a refusal contract plus cost implications — the length is justified and well-sequenced.

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?

Despite having no output schema, the description fully documents the return contract (both success and refusal shapes), the cost implication, the use cases, and the routing behavior. The single parameter is covered by the schema. An agent has everything it needs to decide when to call this tool, invoke it correctly, and interpret the response — nothing significant is missing.

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%, with the question parameter already documented as "Your question in natural language. Accepts query, q, prompt, text, input as aliases." The description mentions "fills arguments" in the routing pipeline but adds no parameter-level meaning beyond the schema. Baseline 3 is correct since the schema does the heavy lifting.

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, differentiated statement: "Hallucination-resistant answer mode for high-stakes reads." It names the verb (answer/ask), the resource (Pipeworx grounded mode), and its defining trait (grounded extraction from tool results only). It clearly distinguishes itself from sibling ask_pipeworx by emphasizing evidence, confidence, and refusal behavior rather than just routing.

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?

Provides explicit when-to-use guidance: "Use whenever an answer will be quoted, cited, or acted on, and the agent must not invent facts (financial verdicts, legal claims, medical lookups, public statements)." It also names the alternative and the condition selecting it: "Costs one extra LLM call vs ask_pipeworx — prefer ask_pipeworx for casual lookups." This is exactly the exclusion logic an agent needs.

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