Retrieve dataset events from upstream dependencies for a specific DAG run in Apache Airflow to monitor data lineage and dependencies.
Get dataset events for a DAG run
| Name | Required | Description | Default |
|---|---|---|---|
| dag_id | Yes | ||
| dag_run_id | Yes |
Changes observed during successful MCP inspections.
v1.0.0Input schema / properties / dag_id / titleRemoved value: -"Dag Id"Input schema / properties / dag_run_id / titleRemoved value: -"Dag Run Id"Input schema / titleRemoved value: -"get_upstream_dataset_eventsArguments"Output schema / (root)Previous value: -{
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-}New value: +nullDoes the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden but only states the basic action without behavioral details. It lacks information on permissions, rate limits, pagination, or what constitutes 'dataset events', making it insufficient 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.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, direct sentence with no wasted words, making it highly concise and front-loaded. It efficiently conveys the core purpose without unnecessary elaboration.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 2 parameters with 0% schema coverage, no annotations, and no output schema, the description is incomplete. It fails to explain parameter meanings, behavioral traits, or return values, which are critical for this data retrieval tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
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 but adds no parameter details. It does not explain what 'dag_id' or 'dag_run_id' represent, their formats, or how they relate to dataset events, leaving parameters semantically unclear.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Get') and target resource ('dataset events for a DAG run'), making the purpose understandable. However, it does not explicitly differentiate from sibling tools like 'get_dataset_events' (which lacks the DAG run context), leaving some ambiguity about scope.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
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. The description does not mention prerequisites (e.g., needing a valid DAG run), exclusions, or comparisons to siblings like 'get_dataset_events', leaving usage context unclear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.