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

Beyond annotations (readOnly, openWorld, idempotent, non-destructive), the description discloses the refusal behavior with exact reasons, the 'ONLY what the tool result contains' constraint, and the extra LLM call cost. This is rich behavioral context that annotations do not provide.

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 well-structured: it leads with purpose, explains the mechanism, details return/refusal formats, then gives usage guidance and cost tradeoff. Every sentence carries necessary information without fluff, front-loading the critical distinction.

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?

For a high-stakes tool with no output schema, the description fully covers return shape (including refusal reasons), usage context, and cost trade-off. An agent has all information needed to decide and invoke correctly.

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 covers all 6 parameters with descriptions (100% coverage), so the description adds no parameter-level detail. Baseline 3 is appropriate; the aliases are self-explanatory and no further semantics are needed.

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 states it is a 'Hallucination-resistant answer mode for high-stakes reads' and explains the mechanism (same routing as ask_pipeworx but extracts answer using only tool result). It explicitly distinguishes from ask_pipeworx by emphasizing grounded extraction with evidence and refusal reasons, making its purpose unambiguous.

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: 'Use whenever an answer will be quoted, cited, or acted on, and the agent must not invent facts' with concrete examples. It also says 'prefer ask_pipeworx for casual lookups' and notes the extra cost, clearly guiding selection among siblings.

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