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

Annotations already declare readOnly, openWorld, idempotent, and non-destructive behavior, and the description goes well beyond that. It discloses that answers are extracted only from tool results, returns verbatim evidence, refuses rather than invents when data is insufficient, and enumerates the exact refusal reason codes.

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 well-structured and front-loaded with the core value proposition. It covers routing, output contract, refusal behavior, use cases, and cost tradeoff without redundant fluff. Every sentence contributes useful decision-making 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?

There is no output schema, so the description correctly takes responsibility for describing return values and failure modes. It fully explains what success looks like, what refusal looks like, when to use the tool, and how it relates to ask_pipeworx. Nothing an agent needs to call it correctly 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?

The input schema has 100% coverage and documents the question parameter plus all six aliases clearly. The description does not add parameter-specific guidance, but with full schema coverage it does not need to; the baseline of 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 states a specific verb and resource: it is a hallucination-resistant answer mode that routes through Pipeworx, fetches data, and extracts answers only from the tool result. It clearly distinguishes itself from ask_pipeworx by emphasizing grounded, evidence-backed answers for high-stakes reads.

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 says when to use the tool — whenever an answer will be quoted, cited, or acted on, with examples like financial verdicts, legal claims, and medical lookups. It also gives an explicit exclusion: prefer ask_pipeworx for casual lookups, and it names the cost tradeoff of 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.