serving-runtime-config

A tool for defining custom ServingRuntime resources in OpenShift AI. A serving runtime is the container and settings used to run a machine-learning model for requests.

In plain words
What is it for?
Create runtimes for ONNX, Triton, or other custom frameworks, choose a container image, customise vLLM parameters, and view available runtimes.
Why use it?
It lets you configure model-serving frameworks that OpenShift AI does not provide as built-in runtimes, or adjust runtime settings for a specific deployment.

Skill for Claude CodeCodex

Install

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.

agentmods
npx agentmods add skills/rhecosystemappeng/agentic-plugins/serving-runtime-config
Any agent
npx skills add RHEcosystemAppEng/agentic-plugins --skill serving-runtime-config
Clone the repo
git clone --depth 1 https://github.com/RHEcosystemAppEng/agentic-plugins

Made for: Claude Code, Codex.

Per session 131 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 3,222 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin unknown No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5 $0.00131 $0.03222
Opus 5 $0.00066 $0.01611
Sonnet 5 $0.00026 $0.00644
Haiku 4.5 $0.00013 $0.00322

Measured 2d ago against content hash 95d9fc73f1c0, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

serving-runtime-config 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 2d 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.

rh-ai-engineer/skills/serving-runtime-config/SKILL.md · 306 lines

The source is not reproduced here

No licence file

A repository with no LICENSE is all rights reserved by default, so the body is not copied here. The metadata, the measurements and the link are.

Read it on GitHub

Files

What ships with it

5 files 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.

Changes

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.

  1. 2d ago First seen · 306 lines · 131 tokens per session scan A 95d9fc73f1c0

Subscribe to this mod's changes

serving-runtime-config is a skill published in the GitHub repository RHEcosystemAppEng/agentic-plugins (50 stars, last pushed 8d ago), with no licence file. It adds 131 tokens to every session and 3,222 once invoked, about $0.0007 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 2026-08-30.

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