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

Annotations already declare readOnly and idempotent behavior, and the description goes beyond by disclosing refusal modes ('not_in_source', 'no_tool_match', 'tool_error', etc.), evidence extraction, and the extra LLM call cost. These behavioral traits are meaningful for an agent deciding whether to trust or rely on the output, and nothing contradicts 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: core behavior, return contract, refusal semantics, use-case guidance, and cost tradeoff. It is front-loaded with the decisive 'hallucination-resistant' characteristic, and the output-shape detail is an efficient substitute for a missing output schema rather than 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?

With no output schema, the description fully specifies both success and refusal return shapes including refusal_reason enum values, plus the cost/alternative tradeoff. It also explains the routing concept, the sourcing scale, and when the tool should be preferred, so an agent has everything needed to call and interpret it 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 coverage is 100% and the question parameter plus aliases are fully described in the schema, so the baseline for this dimension is 3. The description adds general context about taking a natural-language question and filling arguments internally, but does not add parameter-level format or constraint details beyond what the schema already provides.

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 verb-plus-mode: 'Hallucination-resistant answer mode for high-stakes reads,' and then explains it routes like ask_uipeworx but 'EXTRACTS the answer using ONLY what the tool result contains.' This clearly differentiates it from the sibling ask_uipeworx and other lookup tools without needing to inspect schemas.

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?

It gives explicit when-to-use guidance: 'Use whenever an answer will be quoted, cited, or acted on' and lists non-invention domains like financial verdicts, legal claims, and medical lookups. It also gives the exclusion and alternative: 'prefer ask_uipeworx for casual lookups,' naming the exact sibling and the cost tradeoff.

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