Trigger a DAG by ID in Apache Airflow to start workflow execution with optional parameters like run ID, data intervals, and execution date.
Trigger a DAG by ID
| Name | Required | Description | Default |
|---|---|---|---|
| dag_id | Yes | ||
| dag_run_id | No | ||
| data_interval_end | No | ||
| data_interval_start | No | ||
| execution_date | No | ||
| logical_date | No | ||
| note | No |
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 / properties / data_interval_end / titleRemoved value: -"Data Interval End"Input schema / properties / data_interval_start / titleRemoved value: -"Data Interval Start"Input schema / properties / execution_date / titleRemoved value: -"Execution Date"Input schema / properties / logical_date / titleRemoved value: -"Logical Date"Input schema / properties / note / titleRemoved value: -"Note"Input schema / titleRemoved value: -"post_dag_runArguments"Output schema / (root)Previous value: -{
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-}New value: +nullDoes the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. 'Trigger a DAG' implies a write/mutation operation, but it doesn't specify whether this creates a new DAG run, what happens if a run already exists, whether it's idempotent, or what the response looks like. For a mutation tool with zero annotation coverage, this is a significant gap in safety and operational context.
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 extremely concise at just 4 words, with zero wasted language. It's front-loaded with the core action and resource. While it's under-specified for a tool with 7 parameters, it's not verbose or poorly structured—it just lacks necessary detail.
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 the complexity (7 parameters, mutation operation, no output schema, 0% schema description coverage, no annotations), the description is incomplete. It doesn't explain what the tool returns, how parameters interact, error conditions, or behavioral nuances. For a tool that likely initiates workflow executions, this leaves critical gaps for an AI agent to use it correctly.
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%, meaning none of the 7 parameters have descriptions in the schema. The tool description adds no parameter information beyond the name 'dag_id' implied by 'by ID'. It doesn't explain what 'dag_run_id', 'data_interval_start/end', 'execution_date', 'logical_date', or 'note' are for, leaving most parameters undocumented. The description fails to compensate for the schema gap.
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 'Trigger a DAG by ID' clearly states the action (trigger) and target resource (DAG), which is better than a tautology. However, it lacks specificity about what 'trigger' means in this context (e.g., starting a workflow execution) and doesn't distinguish it from sibling tools like 'update_dag_run_state' or 'pause_dag/unpause_dag' that also affect DAG runs. The purpose is understandable but vague.
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?
The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., DAG must exist, be unpaused), when to use it over other DAG-related tools like 'update_dag_run_state', or any constraints (e.g., rate limits, permissions). With many sibling tools affecting DAGs, this omission leaves the agent without context for tool selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.