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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint:false. The description adds substantial behavior beyond those: it extracts answers ONLY from tool results, returns a structured refusal object with specific refusal_reason values, and discloses that it costs an extra LLM call. It also reveals that routing is identical to ask_pipeworx, which is important operational context.

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 long but information-dense, and every clause earns its place: mode, routing scope, extraction constraint, return contract, refusal reasons, use cases, and cost tradeoff. It front-loads the core purpose and then supplies operational guidance. 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 supplies the full return contract on success and failure, including refusal_reason variants. It also covers routing behavior, evidence format, and when to prefer the cheaper sibling. For a tool with this complexity, the description gives an agent everything needed to select and 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 schema already documents the single question parameter plus five aliases. The description mentions that the tool "fills arguments" but does not add parameter-level meaning beyond the schema. Baseline 3 is appropriate since the schema fully covers parameters.

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 defines a specific, distinct mode: a hallucination-resistant grounded answer mode for high-stakes reads. It names the resource (Pipeworx routing over 5,798 tools/1517 sources), describes the extraction behavior, and clearly contrasts with ask_pipeworx by emphasizing evidence-based answers and refusals. This makes it immediately distinguishable from sibling tools.

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?

It explicitly states when to use the tool: "Use whenever an answer will be quoted, cited, or acted on, and the agent must not invent facts," with concrete examples like financial verdicts and legal claims. It also tells the agent when not to use it: "prefer ask_pipeworx for casual lookups," and explains the cost tradeoff of one extra LLM call. This is exemplary usage routing.

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