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

The annotations already establish readOnly/idempotent/openWorld safety, and the description adds substantial behavioral context beyond them: the exact success return shape ({answer, evidence, confidence, source, fetched_at, refusal_reason:null}), the refusal contract with five enumerated reasons, and the extra-LLM-call cost. No statement contradicts the annotations; 'fetches the data... EXTRACTS' is consistent with readOnlyHint=true.

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 definition is front-loaded with the purpose ('Hallucination-resistant answer mode for high-stakes reads') and every subsequent sentence carries functional detail: routing behavior, return contract, refusal reasons, use cases, and cost tradeoff. It is dense but not bloated; the refusal enum and return shape are justified since there is no output schema to carry that 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?

With no output schema, the description correctly assumes the burden of documenting the full return contract, including the refusal variants with all reason codes. Combined with annotations covering the read-only/idempotent safety profile and the description covering usage, cost, and routing scope (5,798 tools across 1,517 sources), nothing essential for correct invocation or interpretation 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%, so the schema fully documents the only required parameter and all five aliases (q, text, input, query, prompt). The description adds nothing parameter-specific beyond the general context of asking a natural-language question, so the baseline 3 applies.

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 names a specific verb and mode ('Hallucination-resistant answer mode... EXTRACTS the answer using ONLY what the tool result contains') tied to a clear resource. It explicitly differentiates from the sibling ask_pipeworx by describing the same routing but with grounded extraction and explicit refusals, so an agent can distinguish them without opening schemas.

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: '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 gives the when-not-to-use and alternative: 'Costs one extra LLM call vs ask_pipeworx — prefer ask_pipeworx for casual lookups,' including the cost rationale that drives the selection.

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