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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, destructiveHint. The description adds rich behavioral context: refusal reasons (not_in_source, no_tool_match, etc.), the guarantee of extracting only from tool results, and the return structure including evidence and confidence. It also discloses the extra LLM call cost. This goes well beyond the annotations and provides critical operational details.

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 compact yet information-dense. It front-loads the core purpose, then explains the mechanism, return format, refusal behavior, and usage guidance, all in about three sentences. Every sentence serves a distinct function with no filler, and the structure flows logically.

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 complex tool with high-stakes usage and no output schema, the description fully covers what an agent needs: return format, refusal reasons, cost implications, and when to use it. It also clarifies the relationship to ask_pipeworx. Nothing essential is missing for correct invocation and interpretation.

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% — every parameter (including aliases) has a description. The tool description itself doesn't add parameter-level meaning beyond restating that the question is in natural language. With full schema coverage, baseline 3 is appropriate; the description adds no extra semantic value.

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 states a specific purpose: 'Hallucination-resistant answer mode for high-stakes reads.' It explicitly contrasts with ask_pipeworx by describing the extraction mechanism, and the resource (routing across 5,801 tools) is clear. It distinguishes itself from the sibling ask_pipeworx and other tools.

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 when-to-use guidance: 'Use whenever an answer will be quoted, cited, or acted on' and 'prefer ask_pipeworx for casual lookups.' It also mentions the cost trade-off (one extra LLM call) and names the alternative (ask_pipeworx). This fully satisfies the when/when-not/alternatives requirement.

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