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yangkyeongmo

MCP Server for Apache Airflow

by yangkyeongmo

get_dag_run

Retrieve specific DAG run details from Apache Airflow by providing DAG ID and run ID for workflow monitoring and debugging.

Instructions

Get a DAG run by DAG ID and DAG run ID

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
dag_idYes
dag_run_idYes
Behavior2/5

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

No annotations are provided, so the description carries full burden. It states it 'gets' a DAG run, implying a read-only operation, but doesn't disclose behavioral traits like error handling (e.g., what happens if IDs are invalid), authentication needs, rate limits, or response format. This leaves gaps for safe and effective use.

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, efficient sentence with zero waste—it directly states the tool's purpose without fluff. It's appropriately sized for a simple retrieval tool and front-loaded with essential information.

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?

Given no annotations, 0% schema coverage, no output schema, and a read operation with two required parameters, the description is incomplete. It lacks details on parameter semantics, behavioral context (e.g., errors, permissions), and what the tool returns, making it inadequate for reliable agent use.

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

Parameters2/5

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

Schema description coverage is 0%, so the description must compensate. It mentions parameters 'dag_id' and 'dag_run_id' but adds no meaning beyond their names—no explanation of what these IDs represent, their format, or where to obtain them. This is insufficient for a tool with two required parameters.

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?

The description clearly states the verb ('Get') and resource ('a DAG run'), specifying it's retrieved by DAG ID and DAG run ID. It distinguishes from sibling tools like 'get_dag_runs' (plural) which likely lists multiple runs, but doesn't explicitly contrast with 'get_dag' or 'get_task_instance' which fetch different resources.

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?

No guidance is provided on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., needing existing DAG and run IDs), contrast with 'get_dag_runs' for listing runs, or specify use cases like monitoring or debugging. The agent must infer usage from the name and context alone.

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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