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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint=false, and the description adds substantial non-redundant behavior: it returns verbatim evidence, refuses with a specific refusal_reason when data doesn't answer, and surfaces the extra LLM call cost. The refusal enum ('not_in_source', 'no_tool_match', 'tool_error', etc.) makes failure behavior transparent. 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?

The description is long but every sentence earns its place: mode, routing, extraction constraint, return shape, refusal shape, use cases, and cost trade-off. It is front-loaded with the most important distinction ('Hallucination-resistant') and structured as a coherent sequence from what it does to when to use it.

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?

The description is complete for an agent to call this tool correctly: it specifies inputs, outputs, refusal behavior, evidence format, when to prefer it, when to avoid it, and how it differs from ask_pipeworx. There is no output schema, but the description explicitly lists the success and refusal return fields, so nothing critical 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 description coverage is 100%, so the schema already documents the 'question' parameter and its aliases. The description adds only that the tool 'fills arguments' internally, which is routing context rather than parameter semantics. Per the baseline rule for high schema coverage, a 3 is appropriate.

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, distinctive purpose: 'Hallucination-resistant answer mode for high-stakes reads.' It clearly names the resource and verb ('ask Pipeworx'), and differentiates from sibling ask_pipeworx by noting it 'EXTRACTS the answer using ONLY what the tool result contains.' The return contract with success and refusal shapes makes the tool's function concrete.

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 gives explicit use criteria: 'Use whenever an answer will be quoted, cited, or acted on, and the agent must not invent facts (financial verdicts, legal claims, medical lookups, public statements).' It also states when not to use it: 'prefer ask_pipeworx for casual lookups' and gives a cost-based reason. This is model guidance for tool selection.

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