Website Change Monitor & Deterministic Diff

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

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, name (resolved against your own datasets), or full name as username~name.

Output Schema

Name	Required	Description	Default
No arguments

Schema Changelog

Changes observed during successful MCP inspections.

Changed1 schema field changedOct 29, 2026

changedInput schema / properties / datasetId / description

Previous value: -"Dataset ID or username~dataset-name."New value: +"Dataset ID, name (resolved against your own datasets), or full name as username~name."

First observedSep 30, 2026

TDQS

A4.2/5.0

Behavior4/5

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

Annotations already declare readOnly, idempotent, non-destructive, closed-world behavior. The description adds important non-annotation context: the tool requires an x402 payment signature in request metadata, plus default limit and clean=true behavior. It does not discuss error modes or rate limits, so it is strong but not exhaustive.

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?

The description is front-loaded with the core purpose and return distinction, then follows with usage and examples. It is generally efficient, though some statements such as default limit and clean behavior duplicate the schema, and the separate usage/examples sections add slight redundancy.

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?

Given the rich annotations, 100% schema description coverage, and an output schema, the description provides everything needed for correct invocation. It covers purpose, return semantics, usage context, default behavior, and the critical x402 payment requirement.

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 the schema already documents all 8 parameters, including default limit, clean behavior, fields/omit/flatten semantics, and datasetId resolution. The description reinforces a few of these and gives example field selections, but adds little parameter semantics beyond what the schema already provides.

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?

The description uses a specific verb and resource ('Get items (rows) from a dataset') and clarifies exactly what is returned versus what is not (metadata, counts, schema). It also gives the direct-call condition when the user provides a datasetId and asks for results, so an agent can distinguish this from adjacent dataset operations.

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?

It states when to use the tool ('when you need to read data from a dataset') and provides concrete user-input examples. It also excludes metadata/count/schema use cases, but it does not name alternative tools for those adjacent needs, so it falls short of full when/when-not/alternatives guidance.

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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