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fastmcp-me

MCP-Airflow-API

by fastmcp-me

list_datasets

List all datasets in an Airflow system, with support for pagination and URI pattern filtering.

Instructions

[Tool Role]: Lists all datasets in the Airflow system (v1 API only - v2 uses Assets).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNo
offsetNo
uri_patternNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior2/5

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

With no annotations, the description carries the full burden of behavioral disclosure. It only states the core action and the API version constraint. It does not mention pagination (though limit/offset exist), filtering capabilities, sort order, or any side effects. The v1/v2 nuance is useful but insufficient for a transparent view of behavior.

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?

The description is a single sentence that front-loads the tool role and includes a crucial API version constraint. It is concise with no fluff, every word adds value, and it is appropriately scoped for a list tool.

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

Completeness2/5

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

Although an output schema exists, which reduces the need to describe return values, the description omits any explanation of the pagination and filter parameters. With three optional parameters and no parameter descriptions, the description is incomplete for an agent trying to use the tool effectively. The API version note adds some context but cannot offset the missing parameter semantics.

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

Parameters1/5

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

Schema description coverage is 0% and the description does not mention any of the three parameters (limit, offset, uri_pattern). The agent gets no guidance on what uri_pattern filters, how limit/offset affect results, or their syntax. The description fails to compensate for the complete lack of schema descriptions.

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 clearly states the tool's purpose: 'Lists all datasets in the Airflow system'. It distinguishes itself from siblings like 'get_dataset' (specific dataset) and 'list_dataset_events' (events) by focusing on listing all datasets. The added 'v1 API only - v2 uses Assets' note further differentiates it from v2 asset-related tools.

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?

The description gives clear context on when to use this tool: only for Airflow v1, explicitly excluding v2. It does not name alternative tools for v2, but the exclusion is direct and helps the agent decide between versions. This is more than implied usage but lacks explicit alternative recommendations.

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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