Website Change Detector & Diff API

Get dataset items

get-dataset-items

Read-onlyIdempotent

Get items (rows) from a dataset — the output/results produced by an Actor run. Returns the rows themselves, not dataset metadata, counts, or a schema. When the user provides a datasetId and asks to retrieve results, output, data, or rows, call this tool directly. Default limit is 20. Use clean=true to skip empty items and hidden fields.

USAGE:

Use when you need to read data from a dataset (all items or only selected fields).

USAGE EXAMPLES:

user_input: Retrieve results from dataset abc123
user_input: Get only metadata.url and title from dataset username~my-dataset

This tool requires an x402 payment. Include a valid x402 payment signature in the request metadata (_meta["x402/payment"]). Your MCP client must support the x402 payment protocol.

Input Schema

TableJSON Schema

Name	Required	Description
`desc`	No	If true, results are returned in reverse order (newest to oldest).
`omit`	No	Comma-separated list of fields to exclude from results.
`clean`	No	If true, returns only non-empty items and skips hidden fields (starting with #). Shortcut for skipHidden=true and skipEmpty=true.
`limit`	No	Maximum number of items to return. Default is 20.
`fields`	No	Comma-separated list of fields to include in results. Fields in output are sorted as specified. Use dot notation for nested objects (e.g. "metadata.url"); the server auto-flattens parent prefixes.
`offset`	No	Number of items to skip at the start. Default is 0.
`flatten`	No	Comma-separated list of fields to flatten (e.g. flatten="metadata" turns {"metadata":{"url":"x"}} into {"metadata.url":"x"}). Normally derived automatically from dot-notation in `fields`; specify only as a diagnostic override.
`datasetId`	Yes	Dataset ID or username~dataset-name.

Output Schema

TableJSON Schema

Name	Required	Description	Default
No arguments

Schema Changelog

Changes observed during successful MCP inspections.

First observedSep 30, 2026

TDQS

A4.1/5.0

Behavior4/5

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

Annotations already cover the read-only/idempotent/non-destructive profile, so the description's added value is the payment requirement ('requires an x402 payment... include a valid x402 payment signature in _meta') plus the default limit of 20 and the clean=true shortcut semantics. The payment/auth disclosure is meaningful context annotations cannot express, though return/pagination behavior is left unstated.

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

Conciseness4/5

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

Front-loaded with the core purpose and scope, followed by trigger condition, examples, and payment notice. The USAGE/EXAMPLE blocks are somewhat verbose but each line carries usable information; no wasted restatement of annotations.

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

Completeness4/5

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

An output schema exists so return values need not be explained, and the key operational extras (payment protocol requirement, default pagination, clean flag) are present. Missing only explicit guidance on alternatives/non-use cases for a fully documented multi-param read tool.

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 description coverage is 100%, so all eight parameters are already documented in the input schema. The description only echoes limit default and clean semantics, adding no syntax or format detail beyond the schema, which matches the baseline 3 when the schema does the heavy lifting.

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 ('get items (rows) from a dataset') and explicitly scopes it against adjacent capabilities: 'Returns the rows themselves, not dataset metadata, counts, or a schema.' An agent can distinguish this from metadata/count-style tools without opening the 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?

Gives a clear trigger condition ('When the user provides a datasetId and asks to retrieve results, output, data, or rows, call this tool directly') plus two concrete usage examples. It does not name an alternative sibling or state when NOT to use it, so it stops short of the top tier.

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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