verl-dataset

---
name: workspace-filesystem
description: The virtual filesystem layout of this workspace.
---

# Virtual Filesystem

You work in a terminal over a virtual filesystem. Read files with shell
commands; service operations are listed in SKILL.md.

| Path | Description |
|---|---|
| `/workspace` | Agent workspace; current directory and home (`~`). |
| `/tmp` | Temporary files. |
| `/dev` | Device files: `null` and `zero` (mounted automatically). |

---
name: workspace-commands
description: The shell commands and task tools available in this workspace.
---

# Available commands

Standard Unix commands, among them:

    cat  head  tail  ls  find  grep  wc  sort  uniq  cut  tr  sed  awk
    diff  tee  xargs  jq  unzip  curl

with pipes, `>` redirection, `$(...)` substitution and `$'...'`.

The task CLIs below are registered with this shell rather than installed
as files; do not inspect them with `which`, `file` or `/usr/bin`.

## web-search

Use `web-search <command> '<JSON arguments>'`. Run
`web-search <command> --help` to get more information.

| Command | Arguments | Description |
|---|---|---|
| `web-search web-search` | `{query: str, num_results?: int = 10}` | Search the web using Google Serper API with concurrency control and retry mechanisms. Supports various Google search operators. — `query`: Search query with optional Google search operators.; `num_results`: Number of results to return, default 10, max 50 |

## fetch

Use `fetch <command> '<JSON arguments>'`. Run `fetch <command> --help` to
get more information.

| Command | Arguments | Description |
|---|---|---|
| `fetch html` | `{url: str, headers?: dict}` | Fetch a website and return the content as HTML — `url`: URL of the website to fetch; `headers`: Optional headers to include in the request |
| `fetch markdown` | `{url: str, headers?: dict}` | Fetch a website and return the content as Markdown — `url`: URL of the website to fetch; `headers`: Optional headers to include in the request |
| `fetch txt` | `{url: str, headers?: dict}` | Fetch a website, return the content as plain text (no HTML) — `url`: URL of the website to fetch; `headers`: Optional headers to include in the request |
| `fetch json` | `{url: str, headers?: dict}` | Fetch a JSON file from a URL — `url`: URL of the JSON to fetch; `headers`: Optional headers to include in the request |

## huggingface

Use `huggingface <command> '<JSON arguments>'`. Run
`huggingface <command> --help` to get more information.

| Command | Arguments | Description |
|---|---|---|
| `huggingface hf-whoami` | `{}` | Inspect the current Hugging Face authentication context, including the account, visible organization memberships, and credential access details. Read-only and never returns credential values. |
| `huggingface hub-repo-search` | `{query?: str, repo_types?: list["model" \| "dataset" \| "space"] = ["model", "dataset"], author?: str, filters?: list[str], sort?: "trendingScore" \| "downloads" \| "likes" \| "createdAt" \| "lastModified", limit?: number = 20}` | Search Hugging Face repositories with a shared query interface. You can target models, datasets, spaces, or aggregate across multiple repo types in one call. Include links to repositories in your response. — `query`: Search term. Leave blank and specify sort + limit to browse trending or recent repositories.; `repo_types`: Repository types to search. Defaults to ["model", "dataset"]. space uses keyword search via /api/spaces.; `author`: Organization or user namespace to filter by (e.g. 'google', 'meta-llama', 'huggingface').; `filters`: Optional hub filter tags. Applied to each selected repo type (e.g. ["text-generation"], ["language:en"], ["mcp-server"]).; `sort`: Sort order (descending): trendingScore, downloads, likes, createdAt, lastModified; `limit`: Maximum number of results to return per selected repo type |
| `huggingface hub-repo-details` | `{repo_ids: list[str], repo_type?: "model" \| "dataset" \| "space", operations?: list["overview" \| "dataset_structure" \| "dataset_preview"], config?: str, split?: str, offset?: int, limit?: int}` | Get details for one or more Hugging Face repos (model, dataset, or space). Auto-detects type unless specified. For datasets, use operations: overview, dataset_structure, dataset_preview. Use dataset_structure first to discover configs, splits, sizes, and schema. Use dataset_preview only when config and split are known, unless the dataset has a single config/split. — `repo_ids`: Repo IDs for (models\|dataset/space) - usually in author/name format (e.g. openai/gpt-oss-120b); `repo_type`: Specify lookup type; otherwise auto-detects; `operations`: Details to return. Defaults to ["overview"]. For datasets, prefer ["overview", "dataset_structure"] first; then call ["dataset_preview"] with config and split.; `config`: Dataset Viewer config. Required for dataset_preview when the dataset has multiple config/split options. Discover via dataset_structure.; `split`: Dataset Viewer split. Required for dataset_preview when the dataset has multiple config/split options. Discover via dataset_structure.; `offset`: Row offset for dataset_preview. Defaults to 0.; `limit`: Row count for dataset_preview. Defaults to 5 and is clamped to 1-100. |
| `huggingface hf-fs` | `{operations: list[{cmd: "ls" \| "cat" \| "attach" \| "stat" \| "find" \| "search", args: list[str]}]}` | When to use: Hugging Face Hub models, datasets, Spaces, collections, papers, daily papers, today's trending models, current paper leaderboard, docs, and repository files. Examples: {"operations":[{"cmd":"ls","args":["hf://models/trending","--limit","10"]}]} {"operations":[{"cmd":"ls","args":["hf://papers/trending"]}]} {"operations":[{"cmd":"ls","args":["hf://papers/daily/latest"]}]} Use hf_fs for Hugging Face Hub filesystem operations. Call it with operations, an array of {cmd, args} items; multiple operations may be submitted together. Usage: {"operations":[{"cmd":"ls","args":["hf://models/org/repo"]}]} Grammar; each string below is one args array item: ls URI [--recursive] [--glob GLOB] [--type TYPE] [--sort SORT] [--limit N] cat URI [--offset N] [--max-bytes N] attach URI [--max-bytes N] stat URI find URI [--name GLOB] [--path GLOB] [--type TYPE] [--limit N] search URI [QUERY] [--type TYPE] [--sort SORT] [--tag TAG] [--kind mcp] [--limit N] COMMAND = ls\|cat\|attach\|stat\|find\|search. TYPE = file\|dir\|repo\|bucket\|collection\|paper\|link. SORT = createdAt\|downloads\|likes\|lastModified\|likes30d\|trendingScore\|mainSize\|id\|trending\|upvotes. URI is a canonical hf:// URI. QUERY and GLOB are each one string. Use search for discovery, ls for a known directory, find for recursive matching within a known scope, stat for filesystem metadata or an uncertain target type, cat for text contents, and attach for a complete JPEG, PNG, or WebP image. When the request gives an exact text-file URI, use cat directly; do not add ls or stat first. stat does not read the contents of JSON, Markdown, or other text files. Search scopes: hf://models\|datasets\|spaces[/OWNER], hf://collections[/OWNER], hf://papers, and hf://docs[/...]. Paper and documentation search require QUERY. Repeat --tag only for search hf://spaces; --kind mcp selects MCP Spaces. Use ls hf://models/trending, hf://datasets/trending, hf://spaces/trending, or hf://papers/trending for trending listings. For a named paper.md or metadata.json, use cat directly. Use ls on a paper only to discover an unnamed related VFS. Omit --limit, --sort, and --type unless the request requires them. Limits and path-specific behavior are documented at hf://README.md. Issue one hf_fs call. — `operations.cmd`: Command to execute.; `operations.args`: Command arguments. First item must be an hf:// URI, not a local path or bare filename. One argument per array item. |

## hf

Use `hf --help` for Hugging Face repository, download and upload commands. Repository paths and revisions identify the same files as upstream. Use `huggingface` for the upstream MCP search and Dataset Viewer operations.

## python3

Execute Python code directly under the agent workspace and return stdout
and stderr. Code can be pasted into a `.py` file and run with `python3`.

Python cannot launch subprocesses or make direct network requests. Run the
documented service commands directly in the shell. Use Python for local
file processing and generating JSON arguments.

cat  head  tail  ls  find  grep  wc  sort  uniq  cut  tr  sed  awk
diff  tee  xargs  jq  unzip  curl