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MetaX-MACAMetaX-MACA/vLLM-metax/.agents/skills/environment-check/SKILL.md

environment-check

Skill188 starsChanged 10 days agoApache-2.0View on GitHub

Prepare and verify the Python environment, target upstream checkout and source installations for vLLM-MetaX upgrades. Gather one complete preparation plan for user approval before installation or adaptation; verify the installed result without repeated confirmation.

2 other projects use a version of this.

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We split this skill into the rules it gives an agent

6 rules. About 0 are common, 4 are distinctive, and 2 are very specific to this project.

  • ≈0

    Common · estimate

    Many files like this have a rule of this kind.

  • ≈4

    Distinctive · estimate

    This author's own choices. Worth a look.

  • 2

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Distinctive:

    Use before a full framework upgrade, or when a domain upgrade needs environment preparation.

    line 8
  2. Very specific:

    Read preparation.md for the plan schema, commands and installation procedure, and inventory.md for independent SDK/GPU/package/source …

    line 11
  3. Very specific:

    Ask for an existing upstream checkout or approve a shallow clone from https://github.com/vllm-project/vllm.git.

    line 53
  4. Distinctive:

    Create/select the environment and prepare checkouts as approved.

    line 74
  5. Distinctive:

    Keep other requirements unchanged in the final source diff.

    line 81
  6. Distinctive:

    Use the same plan across specialists/resume.

    line 110

≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

Upgrade environment preparation

Use before a full framework upgrade, or when a domain upgrade needs environment preparation. Maintaining skills/tooling does not itself start this workflow. Shared source and validation rules remain in common-sense. Read preparation.md for the plan schema, commands and installation procedure, and inventory.md for independent SDK/GPU/package/source collection and diagnostic provenance.

Gather all decisions before work

Require an explicit upstream branch/tag, resolve its full commit and public version, and identify the previous release for the review interval. If these depend on the user supplying the target in the initial bundled answer, resolve them read-only afterward under that approved selection and freeze them before installation. Do not infer a target from the installed package or silently follow a moving branch.

Discover Python through the actual interpreter and pyvenv.cfg. Prefer a detected default uv environment. If none is found, include these conditional choices in the single confirmation list: an undetected uv environment and its path; otherwise create project .venv; otherwise use the current global environment (usually Conda). New uv environments use the approved image base Python and --system-site-packages after checking ABI and package identities. Never mix a different Conda environment's private packages with the selected uv environment.

Inventory installed vLLM/MetaX and ask whether to reuse the environment. Reuse retains Python/image dependencies but conditionally reinstalls framework packages that do not match the target/source. Declining reuse uninstalls and reinstalls both framework packages in the selected environment. MetaX must always be editable from the project owning this skill. Package presence, version equality or cwd shadowing alone is insufficient.

Include a mandatory question in the initial list: does this upgrade depend on mcoplib? Record kernel_provider: mcoplib or source; package presence is not a selection. mcoplib uses the locked environment installation and explicitly sets USE_PRECOMPILED_KERNEL=1 for build/runtime. Source mode explicitly sets it to 0 for both, requires rebuilding MetaX and prohibits runtime fallback to mcoplib, including Python/Triton helpers. Keep an installed but unused mcoplib unchanged. Both choices require all csrc sources to be fully upgraded, using csrc-upgrade; include isolated local-source component checks in the plan even when production uses mcoplib.

Inspect pre-commit availability and the configured hooks' runtime/dependency needs before the initial approval. Include any needed lint-tool preparation under the approved dependency bounds, keeping image/private packages locked. The final upgrade must pass pre-commit run --all-files; missing lint prerequisites must not first surface only when the long adaptation run is otherwise complete.

Ask for an existing upstream checkout or approve a shallow clone from https://github.com/vllm-project/vllm.git. MetaX defaults to this project on master. Preserve dirty files, index and local commits; select a clean upstream alternative if switching would conflict. Include branch-switch/clone paths and conditional reinstalls in the plan. Capture source baselines before persistent preparation edits.

Present all pending decisions and known gaps together, and obtain the user's explicit approval of the complete preparation plan once before mutations. Include target ref/commit/version and previous release, Python/ABI/base, both checkouts and Git actions, installed-package decisions, kernel provider/build/runtime flag, full csrc coverage, image locks, ordinary dependency changes, temporary file restoration, chip/resource scope and recovery limits. Save the actual reply against the immutable resolved plan digest. If the reply fills a conditional choice (such as an undetected uv path or target ref), preserve the displayed proposal and actual reply, then materialize only those explicitly authorized choices without another confirmation. Never claim the user saw a resolved digest they were not shown. Existing explicit session answers count; do not ask again. Missing required answers keep preparation pending; silence is not approval.

Execute the approved preparation

Create/select the environment and prepare checkouts as approved. Initial clone is restricted to the selected ref; try to retain the previous-release-to-target history during initial preparation, using bounded shallow fetch/deepening when needed. Do not fetch all branches or the entire history.

Synchronize only requirements/common.txt byte-for-byte from target upstream and the fixed public base version in setup.py; preserve MetaX SCM/MACA/Torch suffix logic. Keep other requirements unchanged in the final source diff.

Install target vLLM with VLLM_TARGET_DEVICE=empty, no build isolation and no dependencies. For MetaX, source env.sh, run use_existing_metax.py, then install editable without build isolation. Run the cleaner inside the recoverable temporary-file wrapper: restore all affected requirements and pyproject.toml after success/failure, including pre-existing dirty contents. Never restore with Git checkout/reset. Recover interrupted cleanup first.

Bind every installation to the selected interpreter. Use python -m pip when available, otherwise uv pip --python <selected executable>. Permit ordinary common/build dependency changes under exact locks for installed Torch, Triton and all image/private requirements, including packages without +metax/+maca suffixes. No private-package replacement, parent-environment uninstall or dependency conflict workaround is implicitly authorized.

Verify before adaptation

Collect fresh facts and automatically verify the prepared result against the approved plan. Keep the user's plan authorization separate from the machine's final environment verification. Record actual installed provenance, package/private/native identities, source correspondence and final environment fingerprint. Do not ask for a second snapshot confirmation or invent a new user reply after installation.

Both frameworks must be successfully installed and verified before compatibility decisions, adaptation edits or adaptation tests begin. An old plugin that cannot install on target vLLM is a preparation blocker; do not start source adaptation to repair it. Environment diagnostics and already-approved installation retries may continue. Never construct/load a complete model as an installation check; all model execution still waits for the coordinator's final phase.

Use the same plan across specialists/resume. Recollect facts on every request. Unchanged verified identity retains approval; drift requires automatic checking against the same plan, not another user prompt. Out-of-plan changes block dependent work and are recorded with logs/next actions. Do not broaden authorization or repeatedly ask during the long run; continue only independent work whose gates remain satisfied. Report an unresolved preparation blocker instead of bypassing it.

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