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

Annotations already declare readOnly/openWorld/idempotent/non-destructive, and the description adds substantial behavior beyond that: the full success return shape, the explicit refusal contract with all five refusal_reason enum values, the evidence-as-verbatim-quote guarantee, and the cost tradeoff of one extra LLM call. 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?

Purpose is front-loaded in the first sentence and every subsequent clause earns its place — the return shape, refusal reasons, cost note, and usage guidance are all decision-relevant. Slightly verbose in the middle ('picks the right tool from 5,743 across 1500 sources, fills arguments, fetches the data') but this conveys mechanism and scale compactly.

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?

This is a complex tool with no output schema, so the description carries the full burden of explaining return values — it does, with precise success and failure shapes plus all enum values. Combined with annotations covering the safety profile and usage guidance covering selection, nothing an agent needs to invoke this correctly 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% — all six parameters and the alias relationships are fully documented there. The description adds context (the question gets routed and drives argument filling) but no syntax or format detail, so the baseline of 3 for fully-covered schemas 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, differentiating purpose — 'Hallucination-resistant answer mode for high-stakes reads' — and describes a concrete mechanism: route via ask_pipeworx's 5,743 tools, fetch data, then extract answers using only tool results. It explicitly contrasts with the sibling ask_pipeworx for casual lookups, so an agent can tell them apart without inspecting 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?

Gives explicit when-to-use criteria: 'whenever an answer will be quoted, cited, or acted on, and the agent must not invent facts,' backed by concrete domains (financial verdicts, legal claims, medical lookups, public statements). Also gives an explicit when-not: 'prefer ask_pipeworx for casual lookups,' naming the alternative and the selection condition.

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