LLM Benchmarking with lm-evaluation-harness
Orchestra-Research/AI-Research-SKILLs
Runs lm-evaluation-harness to benchmark language models on academic suites such as MMLU, GSM8K and HumanEval, compare models and track training checkpoints.
Register a named Hugging Face dataset for Marin by inspecting its schema and adding the appropriate experiments/datasets module.
Install Add Dataset
$ npx skills add marin-community/marin --skill add-dataset -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install marin-community/marin add-dataset --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/marin-community/marin.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.agents/skills/add-dataset .claude/skills/add-dataset && 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 "add-dataset" agent skill from https://github.com/marin-community/marin/tree/main/.agents/skills/add-dataset into .claude/skills/add-dataset/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "add-dataset", 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/marin-community/marin/tree/main/.agents/skills/add-datasetType 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 marin-community/marin --skill add-dataset -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install marin-community/marin add-dataset --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/marin-community/marin.git skills-src && mkdir -p .agents/skills && cp -r skills-src/.agents/skills/add-dataset .agents/skills/add-dataset && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "add-dataset" agent skill from https://github.com/marin-community/marin/tree/main/.agents/skills/add-dataset into .agents/skills/add-dataset/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "add-dataset", 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 marin-community/marin --skill add-dataset -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install marin-community/marin add-dataset --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/marin-community/marin.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/.agents/skills/add-dataset .cursor/skills/add-dataset && 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 "add-dataset" agent skill from https://github.com/marin-community/marin/tree/main/.agents/skills/add-dataset into .cursor/skills/add-dataset/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "add-dataset", 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/marin-community/marin.git --path .agents/skills/add-dataset--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 marin-community/marin --skill add-dataset -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install marin-community/marin add-dataset --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/marin-community/marin.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/.agents/skills/add-dataset .gemini/skills/add-dataset && 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 "add-dataset" agent skill from https://github.com/marin-community/marin/tree/main/.agents/skills/add-dataset into .gemini/skills/add-dataset/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "add-dataset", 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 marin-community/marin add-datasetInstalls 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 marin-community/marin --skill add-dataset -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/marin-community/marin.git skills-src && mkdir -p .github/skills && cp -r skills-src/.agents/skills/add-dataset .github/skills/add-dataset && 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 "add-dataset" agent skill from https://github.com/marin-community/marin/tree/main/.agents/skills/add-dataset into .github/skills/add-dataset/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "add-dataset", 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 marin-community/marin --skill add-dataset -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install marin-community/marin add-dataset --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/marin-community/marin.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/.agents/skills/add-dataset .opencode/skills/add-dataset && 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 "add-dataset" agent skill from https://github.com/marin-community/marin/tree/main/.agents/skills/add-dataset into .opencode/skills/add-dataset/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "add-dataset", 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.
Facts
- Skill name
add-dataset- GitHub stars
- 3.9k
- Token cost
- ~458 tokens
- SKILL.md length
- 193 words
- Files
- 1
- Skills in repo
- 41
- Repo updated
- First seen
- Licence
- Apache-2.0
At a glance
Register a named Hugging Face dataset for Marin by inspecting its schema and adding the appropriate experiments/datasets module.
- Tasks that involve Model hubs and datasets
- Calls uv
What it does
Add Dataset is an agent skill from marin-community/marin. Register a named Hugging Face dataset for Marin by inspecting its schema and adding the appropriate experiments/datasets module.
Its SKILL.md is about 460 tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.
It sits in AI & LLM Engineering, covering Model hubs and datasets. It works with Hugging Face. The repository describes itself as: Open-source framework for the research and development of foundation models. The licence is Apache-2.0.
When your agent uses it
- Tasks that involve Model hubs and datasets
Example prompts
- “/add-dataset”
Requirements
- Python 3
What it can do on your machine
Read from SKILL.md and the folder at commit 61bb85c. 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
Shell commands in SKILL.md call:
uv
From the folder's file list and the shell code blocks in SKILL.md.
Network
No URLs in SKILL.md. Its commands use uv, which can reach the network depending on how they are called.
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
Add Dataset loads about 458 tokens when it runs. Until then it costs about 35 tokens; SKILL.md has 193 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.
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); files beside SKILL.md are not scanned.
SKILL.md
The full file from marin-community/marin at commit 61bb85c, republished under its Apache-2.0 licence (© marin-community). 193 words, ~458 tokens.
Download SKILL.mdSave it as
.claude/skills/add-dataset/SKILL.md (or your agent's skills folder).- name
- add-dataset
- description
- Register a named Hugging Face dataset for Marin by inspecting its schema and adding the appropriate experiments/datasets module.
Register a Hugging Face dataset
Inspect the schema without downloading the full dataset:
uv run lib/marin/tools/get_hf_dataset_schema.py <dataset_name> [options]For programmatic inspection:
from marin.tools.get_hf_dataset_schema import get_schema
schema = get_schema(dataset_name="wikitext", config_name="wikitext-103-v1")Use repo-managed dependencies. For a one-off inspection without a provisioned
environment, add --with datasets --with pyyaml to uv run.
If the result says a config is required, select one of available_configs and
retry with --config_name. Add --trust_remote_code only after inspecting the
dataset repository and accepting its code-execution boundary. The tool streams;
do not replace it with a full dataset download.
If the dataset cannot be found, stop and report the identifier, path, or access failure instead of guessing a replacement.
Choose the text field from the reported schema. Prefer an exact text field,
then a field containing text, then another string field. Inspect sample_row
to verify the content; it may be empty for some datasets. The result also
reports splits, text_field_candidates, and features.
Add a leaf module under experiments/datasets/ using the lazy builders in
marin.experiment.data:
- expose
<name>_dataset()for one corpus; - expose
<name>_datasets() -> dict[str, ...]for a keyed family; - for Hugging Face subsets, follow
experiments/datasets/nemotron.pyand return one keyed handle per subset.
Validate the selected config, splits, text mapping, and one sample before adding tokenization or downstream experiment configuration.
© marin-community, 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
Just SKILL.md in .agents/skills/add-dataset of marin-community/marin.
Open the folder on GitHubat commit 61bb85c
Compare with similar skills
Add Dataset 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 |
|---|---|---|---|---|---|---|
| Add Dataset this skillmarin-community/marin | 3.9k | — | ~458 | Automated safety check: Pass | Apache-2.0 | |
| LLM Benchmarking with lm-evaluation-harnessOrchestra-Research/AI-Research-SKILLs | 13k | 8 repos | ~3k | Automated safety check: Pass | MIT | |
| SageMaker Serving Image Selectionhuggingface/skills | 11k | 1 repos | ~4.6k | Automated safety check: Pass | Apache-2.0 | |
| Hugging Face Local Model Evalshuggingface/skills | 11k | 2 repos | ~1.6k | Automated safety check: Pass | Apache-2.0 | |
| Upload Post Imagehuggingface/blog | 3.5k | — | ~1.1k | Automated safety check: Pass | None | |
| Add Archon Modelareal-project/AReaL | 5.8k | — | ~4.9k | Automated safety check: Pass | Apache-2.0 |
Similar skills
- Official
SageMaker Serving Image Selection
huggingface/skills
Chooses the right serving container and current image URI for deploying a Hugging Face model to a SageMaker endpoint, preferring Hugging Face images over generic ones.
- Official
Hugging Face Local Model Evals
huggingface/skills
Runs evaluations of Hugging Face Hub models on local hardware with inspect-ai or lighteval, and helps choose between vLLM, Transformers and accelerate backends.
- Official
Upload Post Image
huggingface/blog
A skill your agent uses when adding or migrating non-thumbnail images for a Hugging Face Blog post.
Add Archon Model
areal-project/AReaL
Guide for adding a new model to the Archon engine. An agent skill from areal-project/AReaL.
Esmfold2
JimLiu/science-skills
Biohub ESMFold2 / ESMFold2-Fast all-atom co-folding (Candido et al.
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Related
Works with
Categories
Questions about Add Dataset
What does Add Dataset do?
Register a named Hugging Face dataset for Marin by inspecting its schema and adding the appropriate experiments/datasets module. Add Dataset is an agent skill from marin-community/marin. Register a named Hugging Face dataset for Marin by inspecting its schema and adding the appropriate experiments/datasets module.
When should I use Add Dataset?
Add Dataset fits situations like: tasks that involve Model hubs and datasets.
How do I install Add Dataset in Claude Code?
Run `npx skills add marin-community/marin --skill add-dataset -a claude-code`. Or copy the skill folder (.agents/skills/add-dataset in marin-community/marin) into .claude/skills/add-dataset in your project. Claude Code loads it when a task matches its description.
How do I install Add Dataset in Codex?
Run `npx skills add marin-community/marin --skill add-dataset -a codex`. Or copy the skill folder (.agents/skills/add-dataset in marin-community/marin) into .agents/skills/add-dataset in your project. Codex loads it when a task matches its description.
Can I use Add Dataset 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 marin-community/marin --skill add-dataset -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/add-dataset, .gemini/skills/add-dataset, .github/skills/add-dataset and .opencode/skills/add-dataset in your project.
What does Add Dataset need to run?
Going by SKILL.md and its folder, Add Dataset needs the command-line tools its instructions call (uv). Our summary lists: Python 3.
Does Add Dataset access the network?
SKILL.md contains no URLs. Its commands use uv, which can reach the network depending on how they are called. This is read from the text; nothing was executed.
Is Add Dataset 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. Review the folder before installing.
What licence does Add Dataset use?
Add Dataset 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 Add Dataset use?
About 458 tokens (SKILL.md is roughly 1.8k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
What are the alternatives to Add Dataset?
Skills that share tags, products or a category with Add Dataset: LLM Benchmarking with lm-evaluation-harness (Orchestra-Research/AI-Research-SKILLs, 13k stars), SageMaker Serving Image Selection (huggingface/skills, 11k stars), Hugging Face Local Model Evals (huggingface/skills, 11k stars) and Upload Post Image (huggingface/blog, 3.5k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Add Dataset?
marin-community (a GitHub organization) maintains it in marin-community/marin, which has 3,920 GitHub stars. The repository holds 41 skills in this directory. The repository was last updated on October 9, 2026.
Source: marin-community/marin on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.