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

Annotations mark it read-only, open-world, idempotent, and non-destructive; the description goes well beyond this by disclosing the refusal behavior, the exact refusal_reason enums, evidence quoting, and the constraint that it extracts only from tool results. It does not contradict any annotation.

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 information-dense and front-loaded with the core differentiator. Each sentence adds value, including return shapes and refusal reasons; however, it is a long single paragraph and could be slightly better structured with separation of concerns. Still, no filler exists.

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?

Given the tool's high complexity (routing across 5,743 tools), the simple one-parameter schema, and the absence of an output schema, the description is complete: it covers success and refusal return shapes, use cases, cost tradeoff, and the alternative tool. Nothing an agent needs to call or decide on this tool 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?

Schema description coverage is 100%, with all six parameters documented as aliases for 'question'. The description adds no new parameter-level meaning, but the schema already fully covers the single semantic input. 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?

States a specific mode ('Hallucination-resistant answer mode'), describes the underlying routing ('Same routing as ask_pipeworx'), and clearly differentiates itself by adding extraction-only grounding. The agent can immediately distinguish this from ask_pipeworx and ask_pipeworx_beta.

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?

Explicitly says when to use it: 'whenever an answer will be quoted, cited, or acted on, and the agent must not invent facts.' It also names the alternative and the tradeoff: 'Costs one extra LLM call vs ask_pipeworx — prefer ask_pipeworx for casual lookups.' This is clear when/when-not guidance.

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