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

Beyond the readOnly/idempotent/openWorld annotations, the description discloses the refusal contract (enumerated refusal_reason values), the success envelope with verbatim evidence, the grounding guarantee ('using ONLY what the tool result contains'), and the extra-LLM-call cost. This is the kind of behavioral context no annotation can convey.

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?

Information-dense with zero filler: the core differentiator is front-loaded, the mechanism follows, then the return/refusal contract (essential given no output schema), then usage and cost guidance. Every sentence carries distinct 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?

For a high-complexity tool with no output schema, the description is unusually complete: it supplies the full success and refusal return envelopes, enumerates every refusal_reason, covers the evidence format, and positions the tool against its sibling. An agent has everything needed to call it correctly and interpret the result.

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 baseline is 3 and the schema already documents the question parameter plus all five aliases. The description adds value by revealing how the question is consumed — routed to one of 5,860 tools and decomposed into arguments — implying well-specified questions yield better tool matches, slightly beyond the schema's 'natural language' phrasing.

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+resource pairing — 'Hallucination-resistant answer mode' — and explains the exact mechanism: routing across 5,860 tools and extracting the answer using ONLY tool results. It explicitly differentiates itself from siblings by referencing 'Same routing as ask_pipeworx' and the cost contrast, so an agent can distinguish it from ask_pipeworx and ask_pipeworx_beta.

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: 'whenever an answer will be quoted, cited, or acted on' with concrete domains (financial verdicts, legal claims, medical lookups, public statements). Equally explicit about when not to — 'prefer ask_pipeworx for casual lookups' — naming the exact alternative and the cost reason.

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