airflow
Queries, manages, and troubleshoots Apache Airflow using the af CLI. Covers listing DAGs, triggering runs, reading task logs, diagnosing failures, debugging DAG import errors, checking connections, variables, pools, and monitoring health. Also routes to sub-skills for writing DAGs, debugging, deploying, and migrating Airflow 2 to 3. Use when user mentions "Airflow", "DAG", "DAG run", "task log", "import error", "parse error", "broken DAG", or asks to "trigger a pipeline", "debug import errors", "check Airflow health", "list connections", "retry a run", or any Airflow operation. Do NOT use for warehouse/SQL analytics on Airflow metadata tables — use analyzing-data instead.
94
92%
Does it follow best practices?
Impact
Pending
No eval scenarios have been run
Advisory
Suggest reviewing before use
Quality
Discovery
100%Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.
This is an excellent skill description that hits all the marks. It provides specific concrete actions, comprehensive natural trigger terms, explicit 'Use when' and 'Do NOT use' clauses, and clear boundaries that distinguish it from related skills. The description is thorough without being unnecessarily verbose.
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | Lists multiple specific concrete actions: listing DAGs, triggering runs, reading task logs, diagnosing failures, debugging DAG import errors, checking connections/variables/pools, monitoring health, and routing to sub-skills for writing/debugging/deploying/migrating. | 3 / 3 |
Completeness | Clearly answers both 'what' (queries, manages, troubleshoots Airflow via af CLI with specific operations listed) and 'when' (explicit 'Use when...' clause with detailed trigger phrases). Also includes a 'Do NOT use' boundary condition, which further strengthens completeness. | 3 / 3 |
Trigger Term Quality | Excellent coverage of natural trigger terms users would say: 'Airflow', 'DAG', 'DAG run', 'task log', 'import error', 'parse error', 'broken DAG', 'trigger a pipeline', 'debug import errors', 'check Airflow health', 'list connections', 'retry a run'. These are highly natural phrases. | 3 / 3 |
Distinctiveness Conflict Risk | Highly distinctive with a clear niche around Apache Airflow CLI operations. The explicit exclusion clause ('Do NOT use for warehouse/SQL analytics on Airflow metadata tables — use analyzing-data instead') directly addresses potential overlap and reduces conflict risk. | 3 / 3 |
Total | 12 / 12 Passed |
Implementation
85%Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
This is a strong, well-structured skill that serves as an effective hub for Airflow operations. Its greatest strengths are the fully executable command examples, clear workflow sequences, and excellent progressive disclosure to related skills. The main weakness is some verbosity in the User Intent Patterns section, which could be condensed, though it does serve as a useful routing guide.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The skill is fairly comprehensive but includes some sections that could be tightened. The 'User Intent Patterns' section is quite long and somewhat redundant with the quick reference table. The instance configuration section is thorough but verbose. However, most content earns its place given the breadth of the CLI tool. | 2 / 3 |
Actionability | Excellent actionability throughout — every command is concrete and copy-paste ready. The quick reference table, common workflows, and jq filtering examples all provide fully executable commands with real arguments and flags. | 3 / 3 |
Workflow Clarity | Multi-step workflows are clearly sequenced with numbered steps (investigate failed run, morning health check, validate before deploying). The 'Investigate a Failed Run' workflow includes a clear sequence from discovery through diagnosis to retry. The instance discover command includes an important safety checkpoint (--dry-run first, ask for consent). | 3 / 3 |
Progressive Disclosure | Excellent progressive disclosure with a clear overview in the main file and well-signaled one-level-deep references to related skills (authoring-dags, debugging-dags, deploying-airflow, etc.) and supplementary files (api-reference.md). The Related Skills table at the end provides clear navigation with 'Use when...' context. | 3 / 3 |
Total | 11 / 12 Passed |
Validation
100%Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.
Validation — 11 / 11 Passed
Validation for skill structure
No warnings or errors.
- Repository
- astronomer/agents
- Commit
0642adb
- Reviewed
Table of Contents
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