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

No annotations were provided, so the description carries full weight. It discloses the grounded-extraction mechanism, success return shape, explicit refusal modes and reasons, and the extra cost relative to ask_pipeworx. This is unusually transparent for a tool description.

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 clause earns its place: purpose, routing behavior, return shape, refusal modes, use cases, and cost tradeoff. Each idea forwards selection or invocation.

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?

Covers the full decision surface: when to use (high-stakes, quoted/cited), when not to (prefer cheapest sibling), what success/refusal looks like, and specific refusal reasons. The input schema is trivial (question string), and the output schema is described in enough detail to call and interpret the tool without a separate schema.

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 already fully documents the single `question` parameter and its aliases (100% coverage), so the tool description adds no parameter semantics beyond noting the natural-language question. Baseline 3 applies because the schema carries the load.

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 tool mode ('hallucination-resistant answer mode') distinct from ask_pipeworx)Skip the regular mode—and names exact resources: it routes among tools, fills arguments, fetches data, and extracts an answer using only the tool result. It clearly explains what the tool is and what it is not (a grounded, refusal-capable variant of a sibling).

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 states explicitly when to use it ('whenever an answer will be quoted, cited, or acted on', 'high-stakes reads') and when not to ('prefer ask_pipeworx for casual lookups'), including the cost tradeoff of one extra LLM call.

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