Hugging Face LLM Trainer
huggingface/skills
Trains or fine-tunes language and vision models with TRL or Unsloth on Hugging Face Jobs cloud GPUs, then converts the results to GGUF.
Train and optimize AI agents using Microsoft's Agent Lightning framework with reinforcement learning.
$ npx skills add coco-research/coco --skill agent-lightning -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install coco-research/coco agent-lightning --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/coco-research/coco.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/agent-lightning .claude/skills/agent-lightning && rm -rf skills-srcUse ~/.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/
Install the "agent-lightning" agent skill from https://github.com/coco-research/coco/tree/main/skills/agent-lightning into .claude/skills/agent-lightning/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "agent-lightning", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/coco-research/coco/tree/main/skills/agent-lightningType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add coco-research/coco --skill agent-lightning -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install coco-research/coco agent-lightning --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/coco-research/coco.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/agent-lightning .agents/skills/agent-lightning && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "agent-lightning" agent skill from https://github.com/coco-research/coco/tree/main/skills/agent-lightning into .agents/skills/agent-lightning/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "agent-lightning", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add coco-research/coco --skill agent-lightning -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install coco-research/coco agent-lightning --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/coco-research/coco.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/agent-lightning .cursor/skills/agent-lightning && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "agent-lightning" agent skill from https://github.com/coco-research/coco/tree/main/skills/agent-lightning into .cursor/skills/agent-lightning/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "agent-lightning", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/coco-research/coco.git --path skills/agent-lightning--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add coco-research/coco --skill agent-lightning -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install coco-research/coco agent-lightning --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/coco-research/coco.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/agent-lightning .gemini/skills/agent-lightning && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "agent-lightning" agent skill from https://github.com/coco-research/coco/tree/main/skills/agent-lightning into .gemini/skills/agent-lightning/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "agent-lightning", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install coco-research/coco agent-lightningInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add coco-research/coco --skill agent-lightning -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/coco-research/coco.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/agent-lightning .github/skills/agent-lightning && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "agent-lightning" agent skill from https://github.com/coco-research/coco/tree/main/skills/agent-lightning into .github/skills/agent-lightning/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "agent-lightning", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add coco-research/coco --skill agent-lightning -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install coco-research/coco agent-lightning --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/coco-research/coco.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/agent-lightning .opencode/skills/agent-lightning && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "agent-lightning" agent skill from https://github.com/coco-research/coco/tree/main/skills/agent-lightning into .opencode/skills/agent-lightning/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "agent-lightning", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
agent-lightningTrain and optimize AI agents using Microsoft's Agent Lightning framework with reinforcement learning.
Agent Lightning is an agent skill from coco-research/coco. Train and optimize AI agents using Microsoft's Agent Lightning framework with reinforcement learning. Use when setting up agent training, instrumenting agents with tracing, configuring LightningStore, implementing reward functions, or optimizing prompts with RL/APO algorithms.
Its SKILL.md is about 2k tokens, which your agent loads only when the skill is triggered. The skill folder holds 1 other file (for example `reference.md`).
It sits in AI & LLM Engineering, covering Reinforcement learning and Observability. The repository describes itself as: CoCo Super Intelligence is the orchestration layer that turns Claude Code, Cursor, or Codex into an engineering department: a routed advisory board, 226 skills, 386 commands…
4 steps, taken from the first numbered list in SKILL.md.
Read from SKILL.md and the folder at commit 2ddb559. It shows what the files ask for, not the result of running them.
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.
Shell commands in SKILL.md call:
pipFrom the folder's file list and the shell code blocks in SKILL.md.
Hosts in commands or code, which the agent is likely to contact:
test.pypi.orgpypi.orgAlso links to:
microsoft.github.iogithub.comarxiv.orgdiscord.ggFrom URLs in SKILL.md, links to its own repository left out.
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Agent Lightning loads about 2k tokens when it runs. Until then it costs about 73 tokens; SKILL.md has 262 words of instructions outside code blocks.
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.
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); files beside SKILL.md are not scanned.
Its licence (Custom licence) doesn't allow us to republish the file, so here is its outline and opening line. It has 262 words (~2,024 tokens).
“Microsoft's framework for training AI agents with reinforcement learning, automatic prompt optimization, and supervised fine-tuning.”
SKILL.md and 1 other file in skills/agent-lightning of coco-research/coco.
Open the folder on GitHubat commit 2ddb559
Agent Lightning 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.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Agent Lightning this skillcoco-research/coco | 482 | — | ~2k | Automated safety check: Pass | Custom licence | |
| Hugging Face LLM Trainerhuggingface/skills | 11k | 3 repos | ~7.2k | Automated safety check: Pass | Apache-2.0 | |
| Train RlOpenPipe/ART | 11k | — | ~2.4k | Automated safety check: Pass | Apache-2.0 | |
| Qwopus27b Rl TrainingR6410418/Jackrong-llm-finetuning-guide | 1.7k | — | ~830 | Automated safety check: Pass | Apache-2.0 | |
| Looperksimback/looper | 710 | — | ~2.7k | Automated safety check: Notes | MIT | |
| Fine Tuning With TrlOrchestra-Research/AI-Research-SKILLs | 13k | 7 repos | ~2.9k | Automated safety check: Pass | MIT |
huggingface/skills
Trains or fine-tunes language and vision models with TRL or Unsloth on Hugging Face Jobs cloud GPUs, then converts the results to GGUF.
OpenPipe/ART
RL training reference for the ART framework. An agent skill from OpenPipe/ART.
R6410418/Jackrong-llm-finetuning-guide
Prepare, validate, launch-plan, monitor, resume, and stop configurable Qwopus 27B reinforcement-learning workflows for GRPO or GSPO.
ksimback/looper
Scaffold a well-designed agent loop with best-practice coaching and a cross-model review council.
Orchestra-Research/AI-Research-SKILLs
Fine-tune LLMs using reinforcement learning with TRL - SFT for instruction tuning, DPO for preference alignment, PPO/GRPO for reward optimization, and reward model training.
Optim-Agent/optim-agent
A skill your agent uses when the user wants to optimize configurable system parameters against a measurable scalar objective, especially for model training, inference, quantitative strategies…
coco-research/coco
Build and validate .arch/index.json — a committed map from each architectural component of this repository to the real directories and files that implement it, pinned to a git commit, with every…
coco-research/coco
A skill your agent uses when running, reviewing or changing coco's self-evolution cycle: the 30-day loop that observes how skills are actually used, proposes evidence-backed edits to them as one…
coco-research/coco
A skill your agent uses for architecture, current-state, process, data-flow, medallion, or DP diagrams, including redrawing .drawio and Mermaid sources.
coco-research/coco
A skill your agent uses when the user says 'm0', 'm0 status', 'start m0', 'cross-tool memory', 'operational thread', or 'where is my memory stored', or when the M0 daemon or MCP wiring needs…
coco-research/coco
A skill your agent uses when the user wants a GitHub PR (URL, owner/repoN, or 'this PR') made into a code-change explainer video from its diff and commits: changelog, feature reveal, fix, or refactor.
coco-research/coco
A skill your agent uses when the user wants a video of a website (site tour, portfolio, docs or landing-page showcase) captured from a URL.
Categories
Train and optimize AI agents using Microsoft's Agent Lightning framework with reinforcement learning. Agent Lightning is an agent skill from coco-research/coco. Train and optimize AI agents using Microsoft's Agent Lightning framework with reinforcement learning.
Agent Lightning fits situations like: setting up agent training; instrumenting agents with tracing; configuring LightningStore; implementing reward functions.
Run `npx skills add coco-research/coco --skill agent-lightning -a claude-code`. Or copy the skill folder (skills/agent-lightning in coco-research/coco) into .claude/skills/agent-lightning in your project. Claude Code loads it when a task matches its description.
Run `npx skills add coco-research/coco --skill agent-lightning -a codex`. Or copy the skill folder (skills/agent-lightning in coco-research/coco) into .agents/skills/agent-lightning in your project. Codex loads it when a task matches its description.
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add coco-research/coco --skill agent-lightning -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/agent-lightning, .gemini/skills/agent-lightning, .github/skills/agent-lightning and .opencode/skills/agent-lightning in your project.
Going by SKILL.md and its folder, Agent Lightning needs the command-line tools its instructions call (pip). Our summary lists: Python 3.
SKILL.md names 6 domains. In commands or code: test.pypi.org and pypi.org; the agent is likely to contact these when it follows the instructions. As links in the text: microsoft.github.io, github.com, arxiv.org and discord.gg. This is read from the text; nothing was executed.
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. Review the folder before installing.
Agent Lightning has a licence file (the repository's licence) that doesn't match a standard licence. Read it on GitHub before reusing the skill.
About 2k tokens (SKILL.md is roughly 8.1k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
Skills that share tags, products or a category with Agent Lightning: Hugging Face LLM Trainer (huggingface/skills, 11k stars), Train Rl (OpenPipe/ART, 11k stars), Qwopus27b Rl Training (R6410418/Jackrong-llm-finetuning-guide, 1.7k stars) and Looper (ksimback/looper, 710 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
coco-research (a GitHub user) maintains it in coco-research/coco, which has 482 GitHub stars. The repository holds 57 skills in this directory. The repository was last updated on October 8, 2026.
Source: coco-research/coco on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.