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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint=false, so the safety profile is known. The description adds significant behavioral detail beyond annotations: the exact success return shape, the refusal contract with enumerated refusal_reason values, the 'only what the tool result contains' grounding constraint, and the extra cost versus ask_pipeworx. No contradiction with 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 earns its place: purpose, routing/behavior, return contract, refusal contract, usage criteria, and cost/alternative. The most important differentiator, 'grounded' and 'only what the tool result contains,' is front-loaded. Despite substantial detail, there is no fluff or repetition of schema content.

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?

For a tool with no output schema, the description fully covers return values, error/refusal behavior, use cases, alternatives, and performance trade-offs. The parameter semantics are fully covered by the input schema. With sibling-tool context and annotations, the description leaves no important behavior undocumented for an agent 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 coverage is 100%, and all six parameters are documented aliases of the question parameter, so the schema carries the semantic load. The description adds context about what the tool does with the question (routes it, fills arguments, fetches data) but does not need to explain parameter meaning further because the schema already does so completely. Baseline 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 explicitly identifies this as a hallucination-resistant answer mode for high-stakes reads, with a clear verb: it routes, fetches, and extracts an answer using only tool-result content. It distinguishes itself from ask_pipeworx by emphasizing grounding, evidence quotes, and explicit refusals, so an agent can tell them apart.

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 states 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, medical lookups, and public statements. It also gives an explicit exclusion and alternative: prefer ask_pipeworx for casual lookups because this mode costs an 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.