Scrapling x402 Data Store

Preview a dataset

preview_dataset

Read-only

FREE. Sample of a dataset before buying: up to 10 real rows from the dataset (never more than half of it), all field names, total row count, created_at timestamp and the exact USDC price buy_dataset will charge. JSON output.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "dataset_id": "<dataset_id>"
    },
    "name": "preview_dataset"
  }
}

Input Schema

Name	Required	Description	Default
`dataset_id`	Yes	Id from list_datasets.

Schema Changelog

Changes observed during successful MCP inspections.

First observedOct 21, 2026

TDQS

A4.3/5.0

Behavior4/5

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

Annotations already declare readOnlyHint=true and openWorldHint=false, so the safety profile is covered. The description still earns credit by disclosing cost ('FREE'), sampling caps (max 10 rows, never more than half the dataset), and exactly what the response contains, which annotations cannot express. It does not mention rate limits or latency.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

One dense sentence with the most decision-relevant fact ('FREE') front-loaded, followed by contents and limits. No redundant or filler text.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a one-parameter read tool with no output schema, the description enumerates the return payload (sample rows, field names, row count, created_at, exact price) so an agent knows what it gets back. Nothing needed to call it correctly is missing.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100% and the single parameter is already documented as 'Id from list_datasets.' The description adds no syntax, format, or constraint detail beyond the schema, so baseline 3 applies.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb and resource ('Sample of a dataset') and immediately scopes it against the sibling buy_dataset ('before buying'). An agent can distinguish it from list_datasets and buy_dataset without reading either schema.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

'Sample of a dataset before buying' clearly frames when to call it relative to buy_dataset, and the price-preview detail reinforces the pre-purchase use case. It stops short of an explicit when-not-to-use statement, but the sequencing intent is unambiguous.

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

All Scrapling x402 Data Store tools Inspect

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