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

Annotations already indicate readOnly, openWorld, idempotent, and non-destructive behavior. The description goes well beyond this by disclosing the answer extraction strategy, the exact success and refusal return shapes, the specific refusal_reason enum values, and the extra LLM call cost. It clearly communicates what the tool will and will not do.

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: the core promise is front-loaded, followed by the routing mechanism, return contracts, refusal semantics, usage conditions with examples, and cost-based alternative. Despite length, there is no filler or redundant repetition of schema or annotations.

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 fully documents the success return shape, the refusal shape and all refusal reasons, and the behavioral contract. It also provides use-case context and sibling differentiation. Combined with the rich annotations, an agent has everything needed to invoke this tool correctly and interpret its results.

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%: all parameters are aliases for the same 'question' concept and are described in the schema. The description itself doesn't add parameter-level semantics, which is acceptable given the schema already covers it. It does mention 'fills arguments' at a high level but that is behavioral rather than parameter-specific. 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 starts with a precise, specific purpose: 'Hallucination-resistant answer mode for high-stakes reads.' It clearly distinguishes this variant from ask_pipeworx by emphasizing grounded extraction and explicit refusal behavior, and names the sibling it relates to. The verb 'answer' plus resource scope and return contract make the tool easily identifiable.

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?

Explicit usage guidance is provided: use when an answer will be quoted, cited, or acted on and facts must not be invented, with concrete examples. It also states a clear exclusion — 'prefer ask_pipeworx for casual lookups' — and explains the cost tradeoff. This is strong when/when-not guidance relative to siblings.

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