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BrianLondon

airflow-dev-mcp

by BrianLondon

list_dag_runs

Fetch recent runs of a DAG or across all DAGs, with optional state filtering and pagination, to review execution history without needing a run_id.

Instructions

List recent runs of a DAG — useful when you don't already hold a run_id.

Args: dag_id: DAG identifier. Pass "~" to list runs across all DAGs. limit: Max runs to return (default 25). offset: Pagination offset. state: Optional filter, e.g. ["running"], ["failed"], ["success", "queued"].

Returns: DagRunList with dag_runs (each a DagRunSummary) and total_entries.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNo
stateNo
dag_idYes
offsetNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
dag_runsYes
total_entriesNo
Behavior4/5

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

No annotations provided, so description carries full burden. It describes the return format (DagRunList with dag_runs and total_entries) and parameter behavior. However, it lacks details on pagination or potential performance implications.

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 concise, uses bullet points for args and returns, and front-loads the main purpose. Every sentence adds value without 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 tool has 4 parameters and an output schema, the description covers purpose, all parameters, and return value. It is complete for an agent to select and invoke correctly.

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

Parameters5/5

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

Schema description coverage is 0%, so description must document all parameters. It explains dag_id (including special value '~'), limit, offset, and state with examples. This fully compensates for missing schema documentation.

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 lists recent runs of a DAG and when it is useful. It distinguishes from siblings like get_run_status by specifying it's for when you don't hold a run_id.

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 provides a clear usage context ('useful when you don't already hold a run_id'), but does not explicitly state when not to use or name sibling alternatives. It gives enough guidance for selection.

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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