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Agent skill

Areno Run Serving

by inclusionAI in inclusionAI/AReno

Start, validate, debug, and stop an AReno OpenAI-compatible serving endpoint.

Apache-2.0Auto-check passedAI & LLM Engineering

Install Areno Run Serving

skills CLI
$ npx skills add inclusionAI/AReno --skill areno-run-serving -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install inclusionAI/AReno areno-run-serving --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/inclusionAI/AReno.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.agents/skills/areno-run-serving .claude/skills/areno-run-serving && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
areno-run-serving
GitHub stars
323
Token cost
~409 tokens
SKILL.md length
154 words
Files
5 (incl. scripts, references)
Skills in repo
10
Repo updated
First seen
Licence
Apache-2.0

At a glance

Start, validate, debug, and stop an AReno OpenAI-compatible serving endpoint.

  • Works in 7 steps: Record commit and inspect areno env… → Validate TP/world-size constraints from… → Start with requested cache/context,… → …
  • Areno serve commands
  • Runs Python scripts from its folder; calls python
  • CUDA graph issues

What it does

Areno Run Serving is an agent skill from inclusionAI/AReno. Start, validate, debug, and stop an AReno OpenAI-compatible serving endpoint. Use for areno serve commands, API probes, streaming, cancellation, cache or CUDA graph issues, and supported image or tool-call requests. Do not use for training jobs.

Its SKILL.md is about 410 tokens, which your agent loads only when the skill is triggered. The skill folder holds 7 other files, including scripts and reference files (for example `agents/openai.yaml`, `references/request-contracts.md` and `scripts/build_image_request.py`).

It sits in AI & LLM Engineering. It works with CUDA and OpenAI. The repository describes itself as: An easy-to-use, fast toolkit to scale up RL post-training on a single node. The licence is Apache-2.0.

When your agent uses it

  • Areno serve commands
  • CUDA graph issues
  • Supported image
  • Tool-call requests

Example prompts

  • “/areno-run-serving”

Requirements

  • Python 3

Workflow steps

7 steps, taken from the first numbered list in SKILL.md.

  1. Record commit and inspect areno env --json, areno check, GPUs, model config, and adapter registration.
  2. Validate TP/world-size constraints from current model code.
  3. Start with requested cache/context, attention backend, and CUDA graph policy. Do not disable graphs merely to hide capture failures.
  4. Probe model listing and chat
  5. Build image requests with scripts/build_image_request.py, piping JSON to the HTTP client rather than shell argv.
  6. When relevant, validate streaming, cancellation followed by a clean request, image input, and tool calls. Read…
  7. Classify request, processor, model, cache, scheduler, or transport ownership before editing.

What it can do on your machine

Read from SKILL.md and the folder at commit 25f5fed. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Ships 2 files in scripts/ (Python), which the agent can run.

    Shell commands in SKILL.md call:

    • python

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Areno Run Serving loads about 409 tokens when it runs, and up to ~557 if it reads all its reference files. Until then it costs about 66 tokens; SKILL.md has 154 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~66
When it runs · the whole SKILL.md, loaded when a task matches
~409
With references · SKILL.md plus every file in references/, read only if the agent opens them
~557

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.

SKILL.md

The full file from inclusionAI/AReno at commit 25f5fed, republished under its Apache-2.0 licence (© inclusionAI). 154 words, ~409 tokens.

Download SKILL.mdSave it as .claude/skills/areno-run-serving/SKILL.md (or your agent's skills folder). This skill also uses 4 other files; get the full folder from GitHub.
name
areno-run-serving
description
Start, validate, debug, and stop an AReno OpenAI-compatible serving endpoint. Use for areno serve commands, API probes, streaming, cancellation, cache or CUDA graph issues, and supported image or tool-call requests. Do not use for training jobs.

Run AReno Serving

Read AGENTS.md, CODEMAP.md, and current areno serve --help. Serving uses --model-path, not training's --ckpt.

For a remote model reference, pass --model-hub modelscope. If ModelScope cannot resolve it, report that failure or request a local model path instead of silently changing hubs.

Workflow

  1. Record commit and inspect areno env --json, areno check, GPUs, model config, and adapter registration.
  2. Validate TP/world-size constraints from current model code.
  3. Start with requested cache/context, attention backend, and CUDA graph policy. Do not disable graphs merely to hide capture failures.
  4. Probe model listing and chat:
bash
python .agents/skills/areno-run-serving/scripts/probe_server.py \
  --base-url http://127.0.0.1:8000 [--model <name>]
  1. Build image requests with scripts/build_image_request.py, piping JSON to the HTTP client rather than shell argv.
  2. When relevant, validate streaming, cancellation followed by a clean request, image input, and tool calls. Read references/request-contracts.md.
  3. Classify request, processor, model, cache, scheduler, or transport ownership before editing.

Report command, commit, endpoint, successful probes, and shutdown state. Startup alone is insufficient.

© inclusionAI, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 4 other files (scripts, references) in .agents/skills/areno-run-serving of inclusionAI/AReno.

  • SKILL.md
  • agents/openai.yaml
  • references/request-contracts.md
  • scripts/build_image_request.py
  • scripts/probe_server.py

Open the folder on GitHubat commit 25f5fed

Compare with similar skills

Areno Run Serving next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Areno Run Serving compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Areno Run Serving this skillinclusionAI/AReno323—~409Automated safety check: PassApache-2.0
Model Serving MinefieldBlackwellboy/model-serving-minefield135—~2.1kAutomated safety check: PassMIT
Vllm Deploy Simplevllm-project/vllm-skills102—~1.6kAutomated safety check: PassApache-2.0
Vllm Deploy Dockervllm-project/vllm-skills102—~2.5kAutomated safety check: NotesApache-2.0
Vllm Serversickn33/agentic-awesome-skills47k2 repos~1.7kAutomated safety check: PassMIT
Llama Cppmagnus919/agent-skills115—~2.3kAutomated safety check: PassMIT

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  • Areno Profile Performance

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Works with

Categories

Questions about Areno Run Serving

What does Areno Run Serving do?

Start, validate, debug, and stop an AReno OpenAI-compatible serving endpoint. Areno Run Serving is an agent skill from inclusionAI/AReno. Start, validate, debug, and stop an AReno OpenAI-compatible serving endpoint.

When should I use Areno Run Serving?

Areno Run Serving fits situations like: areno serve commands; CUDA graph issues; supported image; tool-call requests.

How do I install Areno Run Serving in Claude Code?

Run `npx skills add inclusionAI/AReno --skill areno-run-serving -a claude-code`. Or copy the skill folder (.agents/skills/areno-run-serving in inclusionAI/AReno) into .claude/skills/areno-run-serving in your project. Claude Code loads it when a task matches its description.

How do I install Areno Run Serving in Codex?

Run `npx skills add inclusionAI/AReno --skill areno-run-serving -a codex`. Or copy the skill folder (.agents/skills/areno-run-serving in inclusionAI/AReno) into .agents/skills/areno-run-serving in your project. Codex loads it when a task matches its description.

Can I use Areno Run Serving in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add inclusionAI/AReno --skill areno-run-serving -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/areno-run-serving, .gemini/skills/areno-run-serving, .github/skills/areno-run-serving and .opencode/skills/areno-run-serving in your project.

What does Areno Run Serving need to run?

Going by SKILL.md and its folder, Areno Run Serving needs Python for the scripts in its folder and the command-line tools its instructions call (python). Our summary lists: Python 3.

Does Areno Run Serving access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Areno Run Serving safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.

What licence does Areno Run Serving use?

Areno Run Serving is published under the Apache-2.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Areno Run Serving use?

About 409 tokens (SKILL.md is roughly 1.6k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 148 tokens, read only when the agent opens those files.

What are the alternatives to Areno Run Serving?

Skills that share tags, products or a category with Areno Run Serving: Model Serving Minefield (Blackwellboy/model-serving-minefield, 135 stars), Vllm Deploy Simple (vllm-project/vllm-skills, 102 stars), Vllm Deploy Docker (vllm-project/vllm-skills, 102 stars) and Vllm Server (sickn33/agentic-awesome-skills, 47k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Areno Run Serving?

inclusionAI (a GitHub organization) maintains it in inclusionAI/AReno, which has 323 GitHub stars. The repository holds 10 skills in this directory. The repository was last updated on October 10, 2026.

Source: inclusionAI/AReno on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.