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出口单 chukoudan

数据集数据行

get_dataset_rows
Read-onlyIdempotent

一个数据集版本的一页数据行,与发布的一致(不指定版本时取当前版本)。 A page of the rows of one dataset version, as published (the current version when none is named).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNo一页多少行,默认 1000,最多 5000。 Rows in the page (default 1000, at most 5000).
offsetNo跳过的行数,默认 0。 Rows to skip (default 0).
datasetYes数据集编号,来自 list_datasets,例如 central-parity(人民币汇率中间价)。 A dataset id from list_datasets.
versionNo版本号,来自 get_dataset;不填就是当前版本。 A version from get_dataset; the current one when left out.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

B3.2/5.0
Behavior3/5

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

Annotations already declare readOnlyHint, idempotentHint, openWorldHint=false and destructiveHint=false, so the safety profile is covered. The description usefully adds that rows match what was published and that the current version is used when none is named, but says nothing about pagination behavior, large-result handling, or result ordering.

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?

Two short, front-loaded sentences with no filler, and the most decision-relevant fact (equivalent to published data, current version by default) leads. The bilingual duplication adds length but is consistent with the schema's own bilingual style.

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

Completeness3/5

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

With no output schema, an agent would benefit from knowing the shape of a row (columns, keying, whether rows are JSON objects) and how to page through the full dataset, neither of which is covered. Adequate for invoking the tool, but thin for interpreting or iterating results.

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 every parameter is already documented in the schema, including the version default and the limit/offset semantics. The description's restatement of the version default adds no information beyond the schema; baseline 3 applies.

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

Purpose4/5

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

States a concrete verb and resource: retrieving a page of rows from one dataset version, with the version default resolved. It is distinguishable from get_dataset and list_datasets by the 'rows' framing, though it never names those siblings explicitly.

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

Usage Guidelines2/5

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

There is no when-to-use or when-not-to-use guidance and no mention of the alternatives (get_dataset for metadata, list_datasets for ids). The only conditional given is the version default, which is a behavior, not usage 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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