Agent Skills: Score and Rank

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UncategorizedID: opendatahub-io/ai-helpers/vllm-backport-score-rank

Repository

opendatahub-ioLicense: Apache-2.0
3674

Install this agent skill to your local

pnpm dlx add-skill https://github.com/opendatahub-io/ai-helpers/tree/HEAD/helpers/skills/vllm-backport-score-rank

Skill Files

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helpers/skills/vllm-backport-score-rank/SKILL.md

Skill Metadata

Name
vllm-backport-score-rank
Description
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Score and Rank

Applies a deterministic scoring formula to produce reproducible rankings.

Scoring Formula

| Field | Values and Points | |---|---| | verdict | must_backport=30, likely_relevant=20, needs_review=10, likely_skip/skip=0 | | severity | critical=25, moderate=15, low=5 | | affected_scope | all_users=20, specific_models=12, specific_feature=8, edge_case=3 | | backport_risk | safe=15, moderate=8, risky=0 | | self_contained | true=10, false=0 |

Max score: 100. Sorted by score desc, then files_in_release desc, then change_size asc.

Each PR also gets backport_ease: ai-fixable if self_contained AND risk is safe/moderate.

Usage

python3 scripts/score-and-rank.py \
  --input artifacts/backport-triage/analyzed.json \
  --output artifacts/backport-triage/ranked.json

Input

analyzed.json — candidates with agent-added fields: verdict, severity, affected_scope, backport_risk, self_contained.

Output

ranked.json — filtered (removes SKIP/already_backported), scored, sorted, with rank, score, change_size, backport_ease added.