[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M78SP7RH6Q3DVTZBVG2A050P":3,"skill-same:01M78SP7RH6Q3DVTZBVG2A050P":71},{"skillNo":4,"name":5,"nameZh":6,"description":7,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":15,"categories":16,"keywords":17,"publishedAt":18,"linkOnly":19,"markdownContent":20,"markdownBody":21,"frontMatter":22,"refName":27,"commitSha":28,"skillDirectory":29,"forksCount":30,"repositoryHtmlUrl":31,"repositoryHomepageUrl":6,"ownerHtmlUrl":32,"ownerBlogUrl":6,"ownerDescription":6,"updatedAt":33,"install":34,"resources":46},"01M78SP7RH6Q3DVTZBVG2A050P","contribution-tooling",null,"Contribute safely to the Apache Airflow monorepo with repo-specific tooling, validation, documentation, and PR conventions.","VectorSpaceLab\u002FAREX-Skill","VectorSpaceLab","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F180637102?v=4","01M7538C5WPSJGWF7KHR4EFZ9F","01M7538C6R2GFP53NPXTCZNBRT",351,"Apache-2.0","https:\u002F\u002Fgithub.com\u002FVectorSpaceLab\u002FAREX-Skill\u002Fblob\u002Fmain\u002Fskills\u002Frepositories\u002Frepo-skills\u002Fapache-airflow\u002Fsub-skills\u002Fcontribution-tooling\u002FSKILL.md",[],[],"2026-11-15 14:19:17",false,"---\nname: contribution-tooling\ndescription: \"Contribute safely to the Apache Airflow monorepo with\n  repo-specific tooling, validation, documentation, and PR conventions.\"\ndisable-model-invocation: true\nmetadata:\n  disco-role: operating\nlicense: Apache 2.0\n---\n\n\u003C!-- SPDX-License-Identifier: Apache-2.0 -->\n\n# Contribution Tooling\n\nUse this sub-skill when changing the Airflow repository itself: Python code, Task SDK, `airflowctl`, providers, docs, UI, Helm chart, CI\u002Fdev tooling, database migrations, generated files, or PR preparation.\n\n## Start Here\n\n1. Read `references\u002Frepo-map.md` to identify the owning distribution, nested rules, and likely tests.\n2. Read `references\u002Fdevelopment-workflows.md` before running commands; it contains the Airflow-specific Breeze, `uv`, and `prek` rules.\n3. Read `references\u002Fchange-patterns.md` for docs, newsfragment, changelog, generated-file, API, migration, provider, chart, and PR conventions.\n4. Use `references\u002Ftroubleshooting.md` when setup, Docker, Breeze, docs, generated files, or mypy caches fail.\n5. Optionally run `scripts\u002Fselect_test_command.py` with changed paths to get a quick first-pass command list, then refine with the real Airflow selective checks before final PR readiness.\n\n## Non-Negotiable Rules\n\n- Write **Dag** in prose. Keep literal tokens unchanged, such as `DAG`, `dag_id`, `dag`, `airflow dags list`, `get_dag`, and path\u002Fconfig names.\n- Do not run host `pytest`, `python`, or `airflow` commands directly. Prefer `uv run --project \u003Cproject>` for targeted local commands and use Breeze when system services, providers, or CI parity are needed.\n- After editing Python files, format and fix with `uv run ruff format \u003Cfile>` and `uv run ruff check --fix \u003Cfile>` before moving on.\n- Respect every applicable `AGENTS.md`. Nested instructions under providers, UI, dev scripts, registry, shared code, and prek scripts override broader guidance for files in their scope.\n- Do not hand-edit generated files when a generation hook or workflow owns them; regenerate and commit the result.\n- Keep security boundaries intact: scheduler code must not run user code, task execution must use the Execution API rather than direct metadata DB access, and providers must use public SDK\u002FAPI surfaces rather than core internals.\n\n## Quick Validation Flow\n\n```bash\n# First-pass recommendations from changed paths.\nuv run skills\u002Fapache-airflow\u002Fsub-skills\u002Fcontribution-tooling\u002Fscripts\u002Fselect_test_command.py \u003Cchanged-file> [...]\n\n# Authoritative CI-oriented selector once a commit\u002Fref exists.\nbreeze selective-checks --commit-ref \u003Ccommit_with_squashed_changes>\n\n# Fast static checks before PR handoff.\nprek run --from-ref \u003Ctarget_branch> --stage pre-commit\n```\n\n## When To Route Elsewhere\n\n- Deployment, admin operation, and runtime configuration questions belong in the deployment\u002Foperations coverage of the root skill.\n- Deep API authoring, Dag authoring, scheduler behavior, provider implementation, UI, Helm, or Task SDK changes may need their specialized sub-skills after this one sets contribution guardrails.\n- Java SDK and Go SDK work is intentionally out of scope here except for routing and CI cautions; use specialized SDK guidance when available.\n- Provider release-manager bulk classification is specialized, path-dependent work; use the repo-local release-management skill if the user explicitly asks for that workflow.\n","\u003C!-- SPDX-License-Identifier: Apache-2.0 -->\n\n# Contribution Tooling\n\nUse this sub-skill when changing the Airflow repository itself: Python code, Task SDK, `airflowctl`, providers, docs, UI, Helm chart, CI\u002Fdev tooling, database migrations, generated files, or PR preparation.\n\n## Start Here\n\n1. Read `references\u002Frepo-map.md` to identify the owning distribution, nested rules, and likely tests.\n2. Read `references\u002Fdevelopment-workflows.md` before running commands; it contains the Airflow-specific Breeze, `uv`, and `prek` rules.\n3. Read `references\u002Fchange-patterns.md` for docs, newsfragment, changelog, generated-file, API, migration, provider, chart, and PR conventions.\n4. Use `references\u002Ftroubleshooting.md` when setup, Docker, Breeze, docs, generated files, or mypy caches fail.\n5. Optionally run `scripts\u002Fselect_test_command.py` with changed paths to get a quick first-pass command list, then refine with the real Airflow selective checks before final PR readiness.\n\n## Non-Negotiable Rules\n\n- Write **Dag** in prose. Keep literal tokens unchanged, such as `DAG`, `dag_id`, `dag`, `airflow dags list`, `get_dag`, and path\u002Fconfig names.\n- Do not run host `pytest`, `python`, or `airflow` commands directly. Prefer `uv run --project \u003Cproject>` for targeted local commands and use Breeze when system services, providers, or CI parity are needed.\n- After editing Python files, format and fix with `uv run ruff format \u003Cfile>` and `uv run ruff check --fix \u003Cfile>` before moving on.\n- Respect every applicable `AGENTS.md`. Nested instructions under providers, UI, dev scripts, registry, shared code, and prek scripts override broader guidance for files in their scope.\n- Do not hand-edit generated files when a generation hook or workflow owns them; regenerate and commit the result.\n- Keep security boundaries intact: scheduler code must not run user code, task execution must use the Execution API rather than direct metadata DB access, and providers must use public SDK\u002FAPI surfaces rather than core internals.\n\n## Quick Validation Flow\n\n```bash\n# First-pass recommendations from changed paths.\nuv run skills\u002Fapache-airflow\u002Fsub-skills\u002Fcontribution-tooling\u002Fscripts\u002Fselect_test_command.py \u003Cchanged-file> [...]\n\n# Authoritative CI-oriented selector once a commit\u002Fref exists.\nbreeze selective-checks --commit-ref \u003Ccommit_with_squashed_changes>\n\n# Fast static checks before PR handoff.\nprek run --from-ref \u003Ctarget_branch> --stage pre-commit\n```\n\n## When To Route Elsewhere\n\n- Deployment, admin operation, and runtime configuration questions belong in the deployment\u002Foperations coverage of the root skill.\n- Deep API authoring, Dag authoring, scheduler behavior, provider implementation, UI, Helm, or Task SDK changes may need their specialized sub-skills after this one sets contribution guardrails.\n- Java SDK and Go SDK work is intentionally out of scope here except for routing and CI cautions; use specialized SDK guidance when available.\n- Provider release-manager bulk classification is specialized, path-dependent work; use the repo-local release-management skill if the user explicitly asks for that workflow.\n",{"name":5,"license":23,"metadata":24,"description":7,"disable-model-invocation":26},"Apache 2.0",{"disco-role":25},"operating",true,"main","ac3fe1afa80fb9a09775ecfb2b6cc3ba850a2db6","skills\u002Frepositories\u002Frepo-skills\u002Fapache-airflow\u002Fsub-skills\u002Fcontribution-tooling",27,"https:\u002F\u002Fgithub.com\u002FVectorSpaceLab\u002FAREX-Skill","https:\u002F\u002Fgithub.com\u002FVectorSpaceLab","2026-09-03 10:25:21",{"source":8,"skillName":5,"commands":35,"prompt":45,"zipAvailable":26},[36,39,42],{"tool":37,"command":38},"npx","npx skills add VectorSpaceLab\u002FAREX-Skill --skill contribution-tooling",{"tool":40,"command":41},"bunx","bunx skills add VectorSpaceLab\u002FAREX-Skill --skill contribution-tooling",{"tool":43,"command":44},"pnpm","pnpm dlx skills add VectorSpaceLab\u002FAREX-Skill --skill contribution-tooling","安装技能，技能地址：https:\u002F\u002Fgithub.com\u002FVectorSpaceLab\u002FAREX-Skill\u002Fblob\u002Fmain\u002Fskills\u002Frepositories\u002Frepo-skills\u002Fapache-airflow\u002Fsub-skills\u002Fcontribution-tooling\u002FSKILL.md",[47,53,57,61,65],{"path":48,"resourceType":49,"resourceTypeDesc":50,"sizeBytes":51,"sourceHtmlUrl":52},"references\u002Fchange-patterns.md","REFERENCE","参考文档",10327,"https:\u002F\u002Fgithub.com\u002FVectorSpaceLab\u002FAREX-Skill\u002Fblob\u002Fmain\u002Fskills\u002Frepositories\u002Frepo-skills\u002Fapache-airflow\u002Fsub-skills\u002Fcontribution-tooling\u002Freferences\u002Fchange-patterns.md",{"path":54,"resourceType":49,"resourceTypeDesc":50,"sizeBytes":55,"sourceHtmlUrl":56},"references\u002Fdevelopment-workflows.md",7254,"https:\u002F\u002Fgithub.com\u002FVectorSpaceLab\u002FAREX-Skill\u002Fblob\u002Fmain\u002Fskills\u002Frepositories\u002Frepo-skills\u002Fapache-airflow\u002Fsub-skills\u002Fcontribution-tooling\u002Freferences\u002Fdevelopment-workflows.md",{"path":58,"resourceType":49,"resourceTypeDesc":50,"sizeBytes":59,"sourceHtmlUrl":60},"references\u002Frepo-map.md",6670,"https:\u002F\u002Fgithub.com\u002FVectorSpaceLab\u002FAREX-Skill\u002Fblob\u002Fmain\u002Fskills\u002Frepositories\u002Frepo-skills\u002Fapache-airflow\u002Fsub-skills\u002Fcontribution-tooling\u002Freferences\u002Frepo-map.md",{"path":62,"resourceType":49,"resourceTypeDesc":50,"sizeBytes":63,"sourceHtmlUrl":64},"references\u002Ftroubleshooting.md",7163,"https:\u002F\u002Fgithub.com\u002FVectorSpaceLab\u002FAREX-Skill\u002Fblob\u002Fmain\u002Fskills\u002Frepositories\u002Frepo-skills\u002Fapache-airflow\u002Fsub-skills\u002Fcontribution-tooling\u002Freferences\u002Ftroubleshooting.md",{"path":66,"resourceType":67,"resourceTypeDesc":68,"sizeBytes":69,"sourceHtmlUrl":70},"scripts\u002Fselect_test_command.py","SCRIPT","脚本",11064,"https:\u002F\u002Fgithub.com\u002FVectorSpaceLab\u002FAREX-Skill\u002Fblob\u002Fmain\u002Fskills\u002Frepositories\u002Frepo-skills\u002Fapache-airflow\u002Fsub-skills\u002Fcontribution-tooling\u002Fscripts\u002Fselect_test_command.py",[72,79,86,93,100,107],{"skillNo":73,"name":74,"nameZh":6,"description":75,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":76,"categories":77,"keywords":78,"publishedAt":18},"01M799NYSH1R3RVAHSM2D88Y84","passnet-triton-opt","Make a single PassNet Triton kernel fast AND numerically faithful: performance model (when a replacement can win at all), block\u002Fgrid\u002Fwarp tuning, autotune policy, launch overhead, and per-op numeric recipes to pass the dtype baseline tolerances. Use when a pass matches and is correct but speedup below expected, or when correctness fails by small numeric margins.","https:\u002F\u002Fgithub.com\u002FVectorSpaceLab\u002FAREX-Skill\u002Fblob\u002Fmain\u002Fskills\u002Ftask-oriented\u002FPassNet\u002Fskills\u002Fpassnet-triton-opt\u002FSKILL.md",[],[],{"skillNo":80,"name":81,"nameZh":6,"description":82,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":83,"categories":84,"keywords":85,"publishedAt":18},"01M799NS5APEC0N1FZ7XZVW6BN","passnet-solve","END-TO-END playbook for solving one PassNet sample: analyze the computation graphs, decide the optimization strategy (what to fuse, what to replace, what to leave alone), drive the iteration loop, and maximize the sample score. This is the ENTRY skill — invoke it first for any PassNet optimization task; it tells you when to use passnet-pattern-fusion, passnet-triton-opt and passnet-feedback.","https:\u002F\u002Fgithub.com\u002FVectorSpaceLab\u002FAREX-Skill\u002Fblob\u002Fmain\u002Fskills\u002Ftask-oriented\u002FPassNet\u002Fskills\u002Fpassnet-solve\u002FSKILL.md",[],[],{"skillNo":87,"name":88,"nameZh":6,"description":89,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":90,"categories":91,"keywords":92,"publishedAt":18},"01M799NNY9BKSM21V5R7QVTBJX","passnet-skill","PassNet GPU kernel optimization via compiler passes. Design and implement Triton-based optimization passes, create pass files under .\u002Fpass_dir\u002F, self-evaluate with pass_evaluator, and iterate to maximize GPU speedup.","https:\u002F\u002Fgithub.com\u002FVectorSpaceLab\u002FAREX-Skill\u002Fblob\u002Fmain\u002Fskills\u002Ftask-oriented\u002FPassNet\u002Fskills\u002Fpassnet-skill\u002FSKILL.md",[],[],{"skillNo":94,"name":95,"nameZh":6,"description":96,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":97,"categories":98,"keywords":99,"publishedAt":18},"01M799NHH6NP7Z1RK77KGXAN6S","passnet-pattern-fusion","Author PassNet pass files: write patterns that actually MATCH the FX graph, pick fusion regions (which ops to absorb into one Triton kernel), and structure multi-pass submissions with the mandatory shared-dispatch architecture. Use when creating or fixing pattern()\u002Freplacement_args()\u002Freplacement_func() files, when a pass \"failed to match\", or when deciding how to fuse multiple kernels\u002Fops.","https:\u002F\u002Fgithub.com\u002FVectorSpaceLab\u002FAREX-Skill\u002Fblob\u002Fmain\u002Fskills\u002Ftask-oriented\u002FPassNet\u002Fskills\u002Fpassnet-pattern-fusion\u002FSKILL.md",[],[],{"skillNo":101,"name":102,"nameZh":6,"description":103,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":104,"categories":105,"keywords":106,"publishedAt":18},"01M799ND2J4WNC2PGAZ0A06NDF","passnet-orchestrate","Round\u002Fbatch planning and decision support for PassNet graph optimization. Use for multi-sample triage, worker allocation, eval-budget policy, and post-eval keep\u002Frevert decisions. For solving one concrete sample end to end, use passnet-solve as the entry skill; consult this skill only when you need broader planning or a specific decision gate.","https:\u002F\u002Fgithub.com\u002FVectorSpaceLab\u002FAREX-Skill\u002Fblob\u002Fmain\u002Fskills\u002Ftask-oriented\u002FPassNet\u002Fskills\u002Fpassnet-orchestrate\u002FSKILL.md",[],[],{"skillNo":108,"name":109,"nameZh":6,"description":110,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":111,"categories":112,"keywords":113,"publishedAt":18},"01M799N8SBTMY02ZDG2AZF5ZWE","passnet-feedback","Fast, deterministic feedback for PassNet work: pre-flight pattern\u002Fmatch verification WITHOUT burning a GPU evaluation, per-node bottleneck analysis of a sample's graphs, and eval-log parsing into per-variant status + estimated score + failure classification. Use BEFORE every GPU evaluation (check_pattern), at the START of a sample (analyze_graph), and AFTER every evaluation (parse_eval_log).","https:\u002F\u002Fgithub.com\u002FVectorSpaceLab\u002FAREX-Skill\u002Fblob\u002Fmain\u002Fskills\u002Ftask-oriented\u002FPassNet\u002Fskills\u002Fpassnet-feedback\u002FSKILL.md",[],[]]