菜单
Bump the Airflow or Python version across all project files. Use when the user wants to update AIRFLOW_VERSION or PYTHON_VERSION.
用 Codex 或 Claude 帮你安装 复制这段 Prompt，粘贴到 Codex、Claude 或其他助手里，让它检查 Skill 页面并帮你完成安装。
基于 SOC 职业分类
Create a new Whirl environment in the envs/ directory. Use when the user wants to add, scaffold, or create a new Docker Compose environment for the Whirl local Airflow development tool. Also invoked by the create-example skill when the user needs a custom environment. Triggers on requests like "create a new environment", "add an environment for Kafka", "I need an environment with Redis and S3".
Create a new Whirl example project in the examples/ directory. Use when the user wants to scaffold, add, or create a new Airflow DAG example for the Whirl local development tool. Triggers on requests like "create a new example", "add an example", "scaffold an example for X".
Before committing, work out which Whirl examples need a CI run to verify changes still work, then run them after confirming with the user. Use whenever the user is about to commit and asks "what should I test / verify before committing", "which examples does this change affect", "run CI for what I changed", or wants to validate edits to examples, envs, or core whirl files. Identifies the CI runs first and asks permission before running anything.
| name | version-bumper |
| description | Bump the Airflow or Python version across all project files. Use when the user wants to update AIRFLOW_VERSION or PYTHON_VERSION. |
| argument-hint | [airflow|python] <new-version> |
| disable-model-invocation | false |
Bump a version across all relevant files in the whirl project.
The user will specify which version to bump (airflow or python) and the new version number.
If the version type or target version is unclear, ask the user before proceeding.
The version string appears as a hardcoded literal (not a shell variable reference like ${AIRFLOW_VERSION}) in these file types:
**/.whirl.env — as AIRFLOW_VERSION=<version> or PYTHON_VERSION=<version>**/Dockerfile and **/Dockerfile.* — as ARG AIRFLOW_VERSION=<version> or ARG PYTHON_VERSION=<version>**/*.yml — as airflow_version: ["<version>"] or in python_version: [...] listsCLAUDE.md — as prose references to the current versionDiscover the current version by searching for the literal version pattern across the relevant file types:
# For AIRFLOW_VERSION
grep -rn "AIRFLOW_VERSION=[0-9]" --include="*.env" --include="Dockerfile*" .
grep -rn "airflow_version:" --include="*.yml" .
grep -rn "AIRFLOW_VERSION" CLAUDE.md
# For PYTHON_VERSION
grep -rn "PYTHON_VERSION=[0-9]" --include="*.env" --include="Dockerfile*" .
grep -rn "python_version:" --include="*.yml" .
This reveals the current version and every file that needs updating.
Exclude false positives — skip matches where the version is a shell variable reference (e.g. ${AIRFLOW_VERSION}) or a minimum-version guard (MINIMAL_AIRFLOW_VERSION). These must not be changed.
Edit each matched file using the Edit tool, replacing the old version string with the new one. Use replace_all: true for files where the string appears multiple times (e.g. Dockerfiles with two ARG lines, CI workflows with multiple matrix blocks).
Verify by re-running the discovery grep from step 1 and confirming no occurrences of the old version remain:
grep -rn "<old-version>" --include="*.env" --include="Dockerfile*" --include="*.yml" .
grep -n "<old-version>" CLAUDE.md
Report which files were changed and the new version value in each.
Check docker-compose changes against the official Airflow release (Airflow version bumps only):
Fetch the official docker-compose for the new version:
curl -Lf 'https://airflow.apache.org/docs/apache-airflow/<NEW_VERSION>/docker-compose.yaml'
Then read each envs/*/docker-compose.yml in this repo and compare the Airflow service definitions (api-server, scheduler, dagprocessor, triggerer) against the official file. Focus on:
x-airflow-common blockdepends_on)Known intentional differences to ignore — these are whirl-specific and must NOT be "fixed":
| Topic | Official docker-compose | Whirl envs |
|---|---|---|
| Image | apache/airflow:<version> | docker-whirl-airflow:py-${PYTHON_VERSION}-local |
| Port | api-server on 8080 | api-server on 5000 (with -p 5000 command arg) |
| Executor | CeleryExecutor with worker + Redis | No executor set (uses LocalExecutor via .whirl.env) |
| Env vars (official only) | AIRFLOW__CORE__EXECUTOR, AIRFLOW__DATABASE__SQL_ALCHEMY_CONN, AIRFLOW__CELERY__*, AIRFLOW__CORE__FERNET_KEY, AIRFLOW__CORE__DAGS_ARE_PAUSED_AT_CREATION, AIRFLOW__CORE__LOAD_EXAMPLES, AIRFLOW_CONFIG, _PIP_ADDITIONAL_REQUIREMENTS | Sourced from .whirl.env via env_file |
| Env vars (whirl only) | — | WHIRL_SETUP_FOLDER, AIRFLOW__FAB__AUTH_BACKENDS, AIRFLOW__API_AUTH__JWT_SECRET |
| Volume mounts (official only) | logs/, config/, plugins/ directories | Not mounted |
| Volume mounts (whirl only) | — | whirl.setup.d → env.d/ and dag.d/, src/ + setup.py → /opt/airflow/custom/, named build volumes per service |
| Init service | airflow-init for DB migration + user creation | Handled by whirl entrypoint scripts |
| Restart policy | restart: always | Not set |
| User | "${AIRFLOW_UID:-50000}:0" | Not set |
Report any differences that are NOT in the table above — those may indicate new config or behaviour in the Airflow release that should be adopted in the whirl envs.