skills/vllm-omni-pre-check/SKILL.md
Use before submitting a PR to vllm-project/vllm-omni — self-check the branch against project conventions, catch dead code, verify accuracy/performance claims, and confirm merge readiness. Use when the user says "pre-check", "self review", "pre-submit check", or "check my PR before I open it."
npx skillsauth add hsliuustc0106/vllm-omni-skills vllm-omni-pre-checkInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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Some scanners were skipped, did not run, or reported a non-clean status. Review each row below.
Self-review your branch before creating a PR. Two modes: quick catches showstoppers, full does a thorough maintainer-grade review. Never posts to GitHub.
| Mode | When | Time | |------|------|------| | Quick | About to push, final sanity check | ~3 min | | Full | Ready for review, want maintainer-level scan | ~10 min |
Default to quick if unsure. Run full before marking a PR "ready for review."
BASE=$(git merge-base HEAD origin/main 2>/dev/null || git merge-base HEAD main 2>/dev/null)
git diff --name-only ${BASE}...HEAD
If no base is found, use main.
| Diff contains | PR type |
|---------------|---------|
| New files under vllm_omni/model_executor/models/<name>/ | New Model |
| Changes to vllm_omni/diffusion/ | Diffusion Model |
| [Perf] in branch name, or benchmark/throughput changes | Performance |
| [Bugfix] or [Bug] in branch name, or single-file fix | Bug Fix |
| Everything else | General |
Ask: "Quick mode or full mode?" Then walk the checklist for the detected PR type.
The full item-by-item checklists are in references/checklists.md. Each item produces ✓, ✗, or ⚠.
New Model PRs — also load model-addition-checklist.md for detailed dimensions 2 (dead code), 3 (copy-paste), 7 (accuracy), 8 (perf), 9 (benchmark).
Pre-check report for <branch>
Mode: quick | full
Type: <new-model | bug-fix | perf | general>
Dimension Result
───────────────── ──────
PR desc integrity ✓
Registry/config ✓
Dead code ⚠ 2 warnings
Accuracy ✓
Benchmark ✗ missing software versions
Verdict: 1 blocking | 2 warnings | recommend fixing ✗ before PR
Severity:
| Mark | Meaning | |------|---------| | ✗ | Blocking — fix before opening PR | | ⚠ | Warning — consider fixing | | ✓ | Pass | | — | Skipped (not applicable) |
Do not post comments, open PRs, or modify files. The report is for the contributor's terminal only.
development
--- name: vllm-omni-test-report description: Two report kinds; **default output is always HTML** unless the user explicitly asks for Markdown (.md). **Release** — `scripts/compose_full_report.py` (**测试结论**, Buildkite metrics, **Test Result** = Common stack + optional `--log-dir-h*` nightly-style summaries + H100/CI block, **Issue tracking** = GitHub `ci-failure` + *local test* in:title, Open bugs); use `--format markdown` only when the user wants .md or `patch_report_*.py`. **Nightly** — `script
testing
Review PRs on vllm-project/vllm-omni by routing to the right domain skills, checking critical evidence, and focusing comments on blocking issues. Use when reviewing pull requests or local branches, triaging review depth, running detailed or default review, or checking tests, benchmarks, and breaking changes in vllm-omni.
data-ai
Generate videos with vLLM-Omni using Wan2.2 and other video generation models. Use when generating videos from text, creating videos from images, configuring video generation parameters, or working with text-to-video or image-to-video models.
testing
Install and configure vLLM-Omni for omni-modality model inference. Use when setting up vllm-omni, configuring the environment, installing dependencies, resolving GPU driver issues, or preparing a machine for model serving.