Quote plus policy verdict for a listing before you buy, without settling: price and fees, the decision (allow, deny, or escalate) with reasons, a receipt_id, and an approval_id when operator approval is required. Emits a decision receipt. Call this before get_dataset or a paid tool to commit to a decision.
| Name | Required | Description | Default |
|---|---|---|---|
| listing_id | Yes | Dataset id, provider slug, or product id. |
Changes observed during successful MCP inspections.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations indicate readOnlyHint false and destructiveHint false. The description adds that it emits a decision receipt and is a preview without settling, offering useful behavioral context beyond 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?
Description is front-loaded with purpose and key outputs, but somewhat verbose. It effectively packs necessary info without redundancy, earning a high score.
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 simple tool with one parameter and no output schema, the description covers all essential aspects: behavior, outputs, usage context, and prerequisites.
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?
Single parameter listing_id is fully described in schema (100% coverage). The tool description does not add extra parameter details, so baseline score of 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 clearly states the tool provides a quote and policy verdict before purchase, listing outputs like price, fees, decision, and identifiers. It distinguishes from siblings like get_dataset and paid 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?
Explicitly instructs to call this before get_dataset or paid tools to commit to a decision, providing clear when-to-use context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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