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SKILL verified MIT Self-run

Apache Airflow Api

skill-cogni-ai-ou-cogni-ai-agent-skills-apache-airflow-api · by Cogni-AI-OU

Execute Apache Airflow Stable REST API queries, manage DAGs, backfills, connections, variables, and assets. You MUST load this skill when interacting with the Airflow API.

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Install

$ agentstack add skill-cogni-ai-ou-cogni-ai-agent-skills-apache-airflow-api

✓ scanned · ✓ verified, works with Claude Code, Cursor, and more.

Security review

✓ Passed

No issues found. Passed automated security review. · v0.1.0 How review works →

  • ✓ Prompt-injection patterns
  • ✓ Secret / credential exfiltration
  • ✓ Dangerous shell & filesystem operations
  • ✓ Untrusted network calls
  • ✓ Known-malicious package signatures

What it can access

  • ● Network access Used
  • ✓ Filesystem access No
  • ✓ Shell / process execution No
  • ✓ Environment & secrets No
  • ✓ Dynamic code execution No

From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.

View the full security report →

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Reliability & compatibility

✓ Security review passed
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Declared compatibility

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Compatibility is declared by the source manifest. End-to-end runtime verification is coming, see below.

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About

apache-airflow-api

When to Use

  • Querying, triggering, or managing DAGs and DAG Runs via the Airflow REST API.
  • Managing Airflow Variables, Connections, Pools, or Assets autonomously.
  • Extracting Task Instance logs, XCom entries, or execution statistics.
  • Handling backfill operations (pause, unpause, cancel) programmatically.

When Not to Use

  • When interacting with Airflow internal database directly (use standard SQL queries instead).
  • When modifying DAG source files locally (use python or standard editing skills instead).
  • When using Airflow UI-only endpoints (endpoints under /ui are subject to breaking changes).

Core Process

  1. Authentication: Determine the authentication method configured for the Airflow API (e.g., Basic Auth, OAuth2). For Basic Auth, use --user :.
  2. Endpoint Identification: Identify the appropriate /api/v2/ endpoint from the API mindmap or documentation.
  3. Payload Construction: For POST, PUT, or PATCH requests, construct the correct JSON payload (e.g., {"is_paused": true}).
  4. Execution: Use curl or a scripting tool (like Python's requests) to execute the API call. Include appropriate headers (e.g., -H "Content-Type: application/json").
  5. Response Validation: Ensure the response is HTTP 200, 201, or 204. If 401 or 403, verify credentials. If 422, verify payload format.

Best Practices

  • Stable Endpoints: Always use the /api/v2/ (or /api/v1/ depending on the Airflow environment version) stable endpoints, avoiding /ui endpoints.
  • Filtering and Pagination: Use limit, offset, and order_by query parameters when querying large collections like Task Instances or DAG Runs.
  • Dry Runs: Use the dry_run endpoints (e.g., /api/v2/backfills/dry_run, /api/v2/dags/{dag_id}/dagRuns/{dag_run_id}/taskInstances/{task_id}/dry_run) to validate operations before committing them.

Mindmap of API Paths

The following mindmap outlines the structure of the Apache Airflow Stable REST API endpoints:

mindmap
  root(("Airflow API"))
    /api
      /v2
        /assets
          /aliases
            /{asset_alias_id}
          /events
          /{asset_id}
            /materialize
            /queuedEvents
        /auth
          /login
          /logout
        /backfills
          /dry_run
          /{backfill_id}
            /cancel
            /pause
            /unpause
        /config
          /section
            /{section}
              /option
                /{option}
        /connections
          /defaults
          /test
          /{connection_id}
        /dagSources
          /{dag_id}
        /dagStats
        /dagTags
        /dagWarnings
        /dags
          /{dag_id}
            /assets
              /queuedEvents
              /{asset_id}
                /queuedEvents
            /clearTaskInstances
            /dagRuns
              /list
              /{dag_run_id}
                /clear
                /hitlDetails
                /taskInstances
                  /list
                  /{task_id}
                    /dependencies
                    /dry_run
                    /externalLogUrl
                      /{try_number}
                    /links
                    /listMapped
                    /logs
                      /{try_number}
                    /tries
                      /{task_try_number}
                    /xcomEntries
                      /{xcom_key}
                    /{map_index}
                      /dependencies
                      /dry_run
                      /hitlDetails
                        /tries
                          /{try_number}
                      /tries
                        /{task_try_number}
                /upstreamAssetEvents
                /wait
            /dagVersions
              /{version_number}
            /details
            /favorite
            /tasks
              /{task_id}
            /unfavorite
        /eventLogs
          /{event_log_id}
        /importErrors
          /{import_error_id}
        /jobs
        /monitor
          /health
        /parseDagFile
          /{file_token}
        /plugins
          /importErrors
        /pools
          /{pool_name}
        /providers
        /variables
          /{variable_key}
        /version

Common Pitfalls

  • Authentication Missing: Forgetting to pass the bearer token or basic auth credentials, resulting in a 401 Unauthorized response.
  • Incorrect Content Type: Omitting -H "Content-Type: application/json" when executing POST or PATCH requests, which Airflow will reject.
  • URL Encoding Paths: Forgetting to URL-encode variables, connection IDs, or DAG IDs that contain special characters.
  • Timezone Mismatches: Airflow expects timestamps in strict ISO-8601 format (e.g., 2026-05-20T12:00:00Z). Passing timezone-naive strings can cause validation errors.

References

Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

Install and usage instructions live in the source repository linked above.

Reviews

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Versions

  • v0.1.0 Imported from the upstream source.