helpers/skills/vllm-backport-check-backported/SKILL.md
Check which candidate PRs have already been cherry-picked into the downstream branch. Use after classify-and-filter to mark already_backported on each PR. Fully deterministic — compares merge SHAs and PR titles.
npx skillsauth add opendatahub-io/ai-helpers vllm-backport-check-backportedInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
3 of 9 scanners reported clean
Some scanners were skipped, did not run, or reported a non-clean status. Review each row below.
Scans the downstream repo's git history and merged PRs to detect which upstream bugfixes have already been backported.
git log --grep="cherry picked from commit" on the downstream branchgh pr list --state merged --base <branch> title contains #<number>bash scripts/check-backported.sh \
--input artifacts/backport-triage/filtered.json \
--downstream /path/to/downstream-repo \
--branch rhai/0.13.0 \
--output artifacts/backport-triage/candidates.json
candidates.json — same as input with already_backported: true/false added
to each PR object. Prints match counts to stderr.
tools
Use this skill to filter a pre-fetched set of Hacker News stories down to those that report supply-chain security threats relevant to software developers — including malicious packages on npm or PyPI, compromised developer tooling, and attacks targeting source code repositories or CI/CD infrastructure. Reads stories from stories.json in the workspace, performs semantic analysis (fetching HN threads when the title alone is ambiguous), and writes the stories worth alerting on to findings.json.
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.