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Agent skill

Areno Tune Capacity

by inclusionAI in inclusionAI/AReno

Fit an AReno training or rollout workload to available GPUs by tuning TP, mini-batch, batch, sample count, and rollout concurrency.

Apache-2.0Auto-check passedAI & LLM Engineering

Install Areno Tune Capacity

skills CLI
$ npx skills add inclusionAI/AReno --skill areno-tune-capacity -a claude-code

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

GitHub CLI
$ gh skill install inclusionAI/AReno areno-tune-capacity --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-tune-capacity .claude/skills/areno-tune-capacity && 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-tune-capacity
GitHub stars
323
Token cost
~353 tokens
SKILL.md length
117 words
Files
4 (incl. scripts, references)
Skills in repo
10
Repo updated
First seen
Licence
Apache-2.0

At a glance

Fit an AReno training or rollout workload to available GPUs by tuning TP, mini-batch, batch, sample count, and rollout concurrency.

  • Works in 6 steps: Record GPU count/memory, model config,… → Measure rollout with --smoke-infer when… → Measure train with --smoke-train; it… → …
  • Memory headroom
  • Runs Python scripts from its folder; calls python
  • Tune-params requests

What it does

Areno Tune Capacity is an agent skill from inclusionAI/AReno. Fit an AReno training or rollout workload to available GPUs by tuning TP, mini-batch, batch, sample count, and rollout concurrency. Use for OOM prevention, memory headroom, smoke-infer, smoke-train, or tune-params requests. Do not change semantic token limits unless requested.

Its SKILL.md is about 350 tokens, which your agent loads only when the skill is triggered. The skill folder holds 6 other files, including scripts and reference files (for example `agents/openai.yaml`, `references/parameter-relations.md` and `scripts/check_capacity.py`).

It sits in AI & LLM Engineering. 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

  • Memory headroom
  • Tune-params requests

Example prompts

  • “/areno-tune-capacity”

Requirements

  • Python 3

Workflow steps

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

  1. Record GPU count/memory, model config, dtype, TP constraints, optimizer, and semantic token lengths.
  2. Measure rollout with --smoke-infer when useful; it must allocate cache and capture decode graphs.
  3. Measure train with --smoke-train; it skips rollout/prefill and uses the candidate microbatch.
  4. Use --tune-params when requested. Keep peak memory at or below the requested fraction, never above 0.9 when selecting a default safety…
  5. Avoid excessive probes. Probe to make a decision, then confirm the chosen setting.
  6. Run a bounded real workload if the overall user goal is a working task.

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 1 file 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 Tune Capacity loads about 353 tokens when it runs, and up to ~554 if it reads all its reference files. Until then it costs about 74 tokens; SKILL.md has 117 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~74
When it runs · the whole SKILL.md, loaded when a task matches
~353
With references · SKILL.md plus every file in references/, read only if the agent opens them
~554

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). 117 words, ~353 tokens.

Download SKILL.mdSave it as .claude/skills/areno-tune-capacity/SKILL.md (or your agent's skills folder). This skill also uses 3 other files; get the full folder from GitHub.
name
areno-tune-capacity
description
Fit an AReno training or rollout workload to available GPUs by tuning TP, mini-batch, batch, sample count, and rollout concurrency. Use for OOM prevention, memory headroom, smoke-infer, smoke-train, or tune-params requests. Do not change semantic token limits unless requested.

Tune AReno Capacity

Inspect current train help and areno/cli/auto_tune.py. Validate relationships first:

bash
python .agents/skills/areno-tune-capacity/scripts/check_capacity.py \
  --batch-size N --n-samples N --max-running-prompts N \
  --mini-bs N --world-size N --tp-size N

Workflow

  1. Record GPU count/memory, model config, dtype, TP constraints, optimizer, and semantic token lengths.
  2. Measure rollout with --smoke-infer when useful; it must allocate cache and capture decode graphs.
  3. Measure train with --smoke-train; it skips rollout/prefill and uses the candidate microbatch.
  4. Use --tune-params when requested. Keep peak memory at or below the requested fraction, never above 0.9 when selecting a default safety target.
  5. Avoid excessive probes. Probe to make a decision, then confirm the chosen setting.
  6. Run a bounded real workload if the overall user goal is a working task.

Preserve max_new_tokens and max_context_len. Read references/parameter-relations.md before adjusting multiple dimensions.

© 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 3 other files (scripts, references) in .agents/skills/areno-tune-capacity of inclusionAI/AReno.

  • SKILL.md
  • agents/openai.yaml
  • references/parameter-relations.md
  • scripts/check_capacity.py

Open the folder on GitHubat commit 25f5fed

Compare with similar skills

Areno Tune Capacity 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 Tune Capacity compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Areno Tune Capacity this skillinclusionAI/AReno323—~353Automated safety check: PassApache-2.0
Agent BuildershareAI-lab/learn-claude-code78k4 repos~1.2kAutomated safety check: PassMIT
Add Uint Supportpytorch/pytorch104k2 repos~2.3kAutomated safety check: PassCustom licence
LLM Benchmarking with lm-evaluation-harnessOrchestra-Research/AI-Research-SKILLs13k8 repos~3kAutomated safety check: PassMIT
Segment Anything Model GuideOrchestra-Research/AI-Research-SKILLs13k8 repos~3.3kAutomated safety check: PassMIT
1passwordtrpc-group/trpc-agent-go1.9k14 repos~656Automated safety check: PassApache-2.0

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All 10 skills in this repo

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  • Areno Profile Performance

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Categories

Questions about Areno Tune Capacity

What does Areno Tune Capacity do?

Fit an AReno training or rollout workload to available GPUs by tuning TP, mini-batch, batch, sample count, and rollout concurrency. Areno Tune Capacity is an agent skill from inclusionAI/AReno. Fit an AReno training or rollout workload to available GPUs by tuning TP, mini-batch, batch, sample count, and rollout concurrency.

When should I use Areno Tune Capacity?

Areno Tune Capacity fits situations like: memory headroom; tune-params requests.

How do I install Areno Tune Capacity in Claude Code?

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

How do I install Areno Tune Capacity in Codex?

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

Can I use Areno Tune Capacity 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-tune-capacity -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-tune-capacity, .gemini/skills/areno-tune-capacity, .github/skills/areno-tune-capacity and .opencode/skills/areno-tune-capacity in your project.

What does Areno Tune Capacity need to run?

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

Does Areno Tune Capacity 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 Tune Capacity 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 Tune Capacity use?

Areno Tune Capacity 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 Tune Capacity use?

About 353 tokens (SKILL.md is roughly 1.4k 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 201 tokens, read only when the agent opens those files.

What are the alternatives to Areno Tune Capacity?

Skills that share tags, products or a category with Areno Tune Capacity: Agent Builder (shareAI-lab/learn-claude-code, 78k stars), Add Uint Support (pytorch/pytorch, 104k stars), LLM Benchmarking with lm-evaluation-harness (Orchestra-Research/AI-Research-SKILLs, 13k stars) and Segment Anything Model Guide (Orchestra-Research/AI-Research-SKILLs, 13k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Areno Tune Capacity?

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.