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Hugging Face

作者 OOMOL · GitHub ↗ · v1.0.0 · MIT-0
cross-platform ✓ 安全检测通过
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在 OpenClaw 中安装
/install oo-huggingface
功能描述
Hugging Face (huggingface.co). Use this skill for ANY Hugging Face request — searching and reading data. Whenever a task involves Hugging Face, use this skil...
使用说明 (SKILL.md)

Hugging Face

Operate Hugging Face through your OOMOL-connected account. This skill calls the huggingface connector with the oo CLI; OOMOL injects credentials server-side, so you never handle raw tokens.

Category: AI, Developer Tools. Exposes 14 action(s).

Running an action

Assume the user has already installed the oo CLI, signed in, and connected Hugging Face. Do not run oo auth login or open the connection URL proactively — just run the action. Fall back to First-time setup only when a command actually fails with an auth or connection error.

1. Inspect the contract to get the authoritative input/output schema before building a payload:

oo connector schema "huggingface" --action "\x3Caction_name>"

2. Run the action with a JSON payload that matches the input schema:

oo connector run "huggingface" --action "\x3Caction_name>" --data '\x3Cjson>' --json
  • --data takes a JSON object string or @path/to/file.json; omit it to send {}.
  • The response is { "data": ..., "meta": { "executionId": "..." } }; the execution id lives under meta.executionId.

Each action below links to a reference file with its purpose and exact commands. Read the linked file, then fetch the live schema with oo connector schema before constructing --data.

Available actions

  • generate_chat_completion — Generate a chat completion with Hugging Face Inference Providers.
  • generate_embeddings — Generate text embeddings with Hugging Face inference.
  • get_current_user — Get the current authenticated Hugging Face user profile.
  • get_dataset_first_rows — Preview the first rows of a dataset split from the Hugging Face Dataset Viewer.
  • get_dataset_info — Get detailed metadata for a Hugging Face dataset by dataset id.
  • get_dataset_statistics — Get column statistics for a dataset split from the Hugging Face Dataset Viewer.
  • get_model_info — Get detailed metadata for a Hugging Face model by modelId.
  • get_space_info — Get detailed metadata for a Hugging Face Space by repo id.
  • get_trending — Get trending Hugging Face repositories across models, datasets, and Spaces.
  • list_datasets — List Hugging Face datasets using user-friendly search filters.
  • list_endpoints — List Hugging Face Inference Endpoints for a namespace.
  • list_models — List Hugging Face models using user-friendly search filters.
  • list_repo_files — List files in a Hugging Face repository tree.
  • list_spaces — List Hugging Face Spaces using user-friendly discovery filters.

Safety

  • Read actions (get / list / search) are safe to run directly.
  • Create, update, send, or post actions change Hugging Face state — confirm the exact payload and effect with the user before running.
  • Delete or remove actions are destructive — always confirm the target and get explicit approval first.

First-time setup

These are one-time steps — do not repeat them on every call. Run a step only when a command fails for the matching reason.

  • oo: command not found — install the oo CLI (other platforms: \x3Chttps://cli.oomol.com/install-guide.md>):

    curl -fsSL https://cli.oomol.com/install.sh | bash    # macOS / Linux
    
    irm https://cli.oomol.com/install.ps1 | iex           # Windows PowerShell
    
  • Not signed in / authentication error — sign in to your OOMOL account once:

    oo auth login
    
  • scope_missing / credential_expired / app_not_ready / app_not_found — Hugging Face is not connected, or the connection expired or lacks a scope. Connect once (auth type: OAuth2) at:

    https://console.oomol.com/app-connections?provider=huggingface
    
  • HTTP 402 / OOMOL_INSUFFICIENT_CREDIT — billing stop. Recharge at https://console.oomol.com/billing/token-recharge before retrying.

Resources

安全使用建议
Install this only if you trust OOMOL as the intermediary for your Hugging Face connection. Review the requested Hugging Face scopes when connecting, and be aware that inference prompts, embeddings input, dataset queries, and account/profile lookups may be sent through the OOMOL connector to Hugging Face.
能力评估
Purpose & Capability
The stated purpose is operating Hugging Face through an OOMOL-connected account, and the listed actions match that purpose: model, dataset, Space, repository-file, endpoint, profile, trending, and inference operations.
Instruction Scope
Runtime authority is scoped to Bash commands matching `oo *`; the instructions require fetching the live connector schema before running actions and include explicit confirmation guidance for any state-changing or destructive operations.
Install Mechanism
The skill includes fallback first-time setup commands to install the oo CLI and authenticate with OOMOL, including remote installer commands, but it says not to run them proactively and only to use them after relevant failures.
Credentials
Use of Hugging Face account scopes such as account read, repo read, and inference is proportionate to the connector purpose, though user prompts, dataset queries, and account metadata may pass through OOMOL/Hugging Face services.
Persistence & Privilege
The artifact describes persistent OOMOL/Hugging Face account connection as normal setup, but does not instruct local token handling, background workers, privilege escalation, hidden persistence, or broad filesystem access.
如何使用
  1. 确保已安装 OpenClaw(本地或 Docker 部署)
  2. 在对话框中输入安装命令:/install oo-huggingface
  3. 安装完成后,直接呼叫该 Skill 的名称或使用 /oo-huggingface 触发
  4. 根据 Skill 的参数说明提供必要输入,即可获得结构化输出
版本历史
v1.0.0
- Initial release of the `oo-huggingface` skill for operating Hugging Face through an OOMOL-connected account via the `huggingface` connector. - Adds discovery actions for models, datasets, Spaces, trending repositories, repository files, and inference endpoints. - Supports detailed metadata lookup for Hugging Face models, datasets, Spaces, and the current authenticated user. - Provides dataset inspection utilities for previewing first rows and retrieving split-level column statistics from the Dataset Viewer. - Enables Hugging Face inference workflows, including chat completions and text embeddings through Inference Providers. - Documents a schema-first execution flow using `oo connector schema` and `oo connector run`, with credential handling delegated to OOMOL.
元数据
Slug oo-huggingface
版本 1.0.0
许可证 MIT-0
累计安装 0
当前安装数 0
历史版本数 1
常见问题

Hugging Face 是什么?

Hugging Face (huggingface.co). Use this skill for ANY Hugging Face request — searching and reading data. Whenever a task involves Hugging Face, use this skil... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 29 次。

如何安装 Hugging Face?

在 OpenClaw 或 Claude Code 对话框中运行命令「/install oo-huggingface」即可一键安装,无需额外配置。

Hugging Face 是免费的吗?

是的,Hugging Face 完全免费,采用 MIT-0 许可证,可自由下载、安装和使用。

Hugging Face 支持哪些平台?

Hugging Face 跨平台运行,可在任意部署了 OpenClaw / Claude Code 的环境中使用(cross-platform)。

谁开发了 Hugging Face?

由 OOMOL(@oomol)开发并维护,当前版本 v1.0.0。

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