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

Annotations already declare readOnly/openWorld/idempotent, and the description adds significant behavioral context: it returns only what the tool result contains, produces a structured refusal with enumerated refusal_reason values, and incurs one extra LLM call. It also specifies the exact success and refusal output shapes, going well beyond the 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?

The description is dense but every sentence earns its place: purpose, routing behavior, output contract, use cases, and cost/alternative routing. It is front-loaded with the most important selection signal ('hallucination-resistant') and structured so an agent can quickly decide whether to use this tool.

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?

There is no output schema, so the description correctly compensates by specifying the full return shape for both success and refusal, including refusal_reason enumeration. It also covers routing, cost tradeoff, and when to prefer a sibling. For a tool of this complexity, nothing essential 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 coverage is 100%, so the schema already documents the single semantic parameter and all aliases. The description adds no new parameter syntax details; its mention of 'fills arguments' is behavioral rather than parameter-specific. Baseline 3 is appropriate because the schema carries the parameter documentation burden.

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 opens with a specific function: 'Hallucination-resistant answer mode for high-stakes reads.' It clearly states the mechanism (same routing as ask_pipeworx, then extracts only from tool results) and the output contract (answer with evidence or explicit refusal). It also distinguishes itself from the sibling ask_pipeworx by the grounded extraction and refusal 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: '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, etc.). It also gives an exclusion: 'prefer ask_pipeworx for casual lookups' and names the cost difference, allowing the agent to route correctly.

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