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

Annotations already indicate read-only, open-world, idempotent, non-destructive. The description adds valuable behavioral context: extraction is limited to tool results, refusal reasons are enumerated (not_in_source, no_tool_match, tool_error, data_truncated, llm_error), and it discloses the extra LLM call cost. 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?

Three dense sentences cover purpose, routing, output format, refusal behavior, use cases, exclusions, and cost. Every clause adds information and the primary purpose is front-loaded. No filler.

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?

Despite no output schema, the description fully documents the success and refusal return shapes, the routing mechanism, the use context, and the tradeoff versus ask_pipeworx. An agent has enough to decide whether to call it and what to expect in response.

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% with all six properties documented as aliases for 'question'. The description explains the routing/processing but does not add meaning about the question parameter beyond what the schema already provides. Baseline 3 applies because the schema fully carries parameter documentation.

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 clearly identifies this as a hallucination-resistant answer mode that routes like ask_pipeworx but extracts answers only from tool results, returning evidence and confidence. It distinguishes itself from the sibling ask_pipeworx by explicitly naming the alternative and the added grounding/evidence behavior.

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 states when to use: 'whenever an answer will be quoted, cited, or acted on, and the agent must not invent facts', with concrete domains (financial verdicts, legal claims, medical lookups, public statements). It also gives a clear fallback: 'prefer ask_pipeworx for casual lookups.'

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