helpers/skills/vllm-backport-classify/SKILL.md
Classify bugfix PRs by type (runtime_bug, platform_specific, unclear, not_bugfix) and filter by file existence at a release tag. Use after fetching raw PRs to produce a filtered candidate list. PRs marked "unclear" need agent review.
npx skillsauth add opendatahub-io/ai-helpers vllm-backport-classifyInstall 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.
Applies deterministic regex rules to classify PRs, checks which files existed at the target release tag, detects subsystems, and filters out PRs that only touch post-release or non-runtime code.
python3 scripts/classify-and-filter.py \
--input artifacts/backport-triage/raw-prs.json \
--repo /path/to/vllm \
--tag v0.13.0 \
--output artifacts/backport-triage/filtered.json
raw-prs.json — output of the vllm-backport-fetch-prs skill.
filtered.json — same PR objects enriched with:
classification: runtime_bug, platform_specific, unclear, not_bugfixverdict: CANDIDATE or SKIPskip_reason: why skipped (if applicable)files, files_in_release, files_new, files_in_release_count, files_totalsubsystems: list of detected vLLM subsystem namesAfter running this skill, review PRs with classification: "unclear". Read
each PR's description and decide if it's a real bugfix. Override the
classification in the JSON if needed.
Bugfix PRs in vLLM often have misleading titles — always check the actual diff and description, not just the title.
development
Run hexora static analysis on a Python package repository to detect suspicious code patterns, then triage findings with deterministic rules and AI reasoning to produce a structured risk report section.
development
Inspect recent git history of a Python package repository for suspicious commits touching supply-chain-sensitive files, then triage findings with AI reasoning to produce a structured risk report section.
development
Scan a Python package repository for compiled/binary files using Fromager-style detection and malcontent YARA analysis, then triage findings with deterministic rules and AI reasoning to produce a structured risk report section.
testing
Use this skill to identify non-Red Hat RPM packages installed in container images or on the local machine. For containers, pulls images across multiple architectures and release tags; for local scans, inspects the host directly. Extracts RPM signing metadata and reports packages not signed with the Red Hat GPG key as CSV output. Use when auditing compliance, checking supply-chain provenance, or scanning for third-party RPMs in RHOAI component images.