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

The description discloses detailed behavioral traits beyond the readOnlyHint/openWorldHint/idempotentHint annotations: it returns a structured {answer, evidence, confidence, source, fetched_at, refusal_reason} object, or an explicit refusal with enumerated refusal_reason values, and explains that it extracts using ONLY tool results. It also surfaces the cost of one extra LLM call.

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, mechanism, output contract, refusal behavior, use cases, and cost tradeoff are all covered without repetition. It is front-loaded with the most decision-relevant information.

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 explains return values, evidence quoting, confidence, source, and refusal reasons. It also gives concrete examples of high-stakes domains and notes the cost/alternative, making the tool safe to invoke without further context.

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%: all six parameters are explicitly documented as aliases for 'question', with a clear natural-language description. The tool description adds no additional parameter semantics, which is acceptable because the schema already carries the full 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 verb and resource: 'Hallucination-resistant answer mode for high-stakes reads.' It explicitly contrasts with ask_pipeworx ('Same routing as ask_pipeworx... then EXTRACTS the answer'), clearly distinguishing this tool from its primary sibling.

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?

The description states exactly when to use this tool: 'Use whenever an answer will be quoted, cited, or acted on, and the agent must not invent facts.' It also gives an explicit alternative and exclusion: 'prefer ask_pipeworx for casual lookups' and notes the extra LLM call cost as a tradeoff.

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