Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add opendatahub-io/ai-helpers --skill vllm-backport-score-rankgit clone --depth 1 https://github.com/opendatahub-io/ai-helpersWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/opendatahub-io/ai-helpers/vllm-backport-score-rank)<a href="https://agentmods.dev/skills/opendatahub-io/ai-helpers/vllm-backport-score-rank"><img src="https://agentmods.dev/badge/skills/opendatahub-io/ai-helpers/vllm-backport-score-rank/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/opendatahub-io/ai-helpers/vllm-backport-score-rank"><img src="https://agentmods.dev/badge/skills/opendatahub-io/ai-helpers/vllm-backport-score-rank.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00048 | $0.00412 |
| Opus 5 | $0.00024 | $0.00206 |
| Sonnet 5 | $0.00010 | $0.00082 |
| Haiku 4.5 | $0.00005 | $0.00041 |
Grade A, and why
vllm-backport-score-rank scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 9d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
What it actually says
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.
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 9d ago First seen · 50 lines · 48 tokens per session scan A 917aeef7f4cb
vllm-backport-score-rank is a skill published in the GitHub repository opendatahub-io/ai-helpers (37 stars, last pushed 5d ago), licensed Apache-2.0. It adds 48 tokens to every session and 412 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
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