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当前安装
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版本数
在 OpenClaw 中安装
/install cellcog
功能描述
Any-to-any AI sub-agent — research, images, video, audio, music, podcasts, avatars, voice cloning, documents, spreadsheets, dashboards, 3D models, diagrams, and code in one request. Agent-to-agent protocol with multi-step iteration for high accuracy. #1 on DeepResearch Bench (Apr 2026) — deep reasoning meets all modalities, so all your work gets done, not just code.
如何使用
- 确保已安装 OpenClaw(本地或 Docker 部署)
- 在对话框中输入安装命令:
/install cellcog - 安装完成后,直接呼叫该 Skill 的名称或使用
/cellcog触发 - 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
v2.0.21
Display title updated.
v2.0.20
Title and content updated.
v2.0.19
Display title updated.
v2.0.18
Content updated.
v2.0.17
- Documentation updated in SKILL.md; content revised or expanded.
- Obsolete or redundant file skill-card.md removed.
v2.0.16
- Updated DeepResearch Bench ranking reference to July 2026 and clarified that leaderboard positions may change over time.
- Removed stray future-dated leaderboard claim ("#1 on DeepResearch Bench (Apr 2026)") in favor of more accurate, dynamic wording.
- Removed the file skill-card.md.
- No behavioral changes; documentation refresh only.
v2.0.15
- Documentation clarifies that anything wrapped in <SHOW_FILE> tags is uploaded to CellCog; warns not to include credentials, private keys, or sensitive material as SHOW_FILE files.
- Added a comparison to reference image attachments in Nano Banana to explain <SHOW_FILE> usage.
- Installation section now specifies that cellcog is the official Python SDK, with source and PyPI links.
- Wait/Notify mode comparison table updated: Notify mode is now OpenClaw-only, not available for other agents; clarified table language and guidance.
- Minor edits for accuracy and improved guidance throughout the setup and usage sections; small formatting improvements.
v2.0.14
- Added support for new modalities: avatars and voice cloning in the SKILL description.
- Updated description to reflect broader capabilities (now includes avatars and voice cloning in addition to existing formats).
- No code or API changes—documentation/feature list update only.
v2.0.13
- Expanded description to emphasize agent-to-agent protocol and multi-step iteration for high accuracy.
- Updated and clarified introductory sections to stress support for all output types, not just code.
- Improved highlights of CellCog's DeepResearch Bench #1 ranking and modal capabilities.
- Cleaned up and streamlined the documentation for easier understanding without removing key usage instructions.
- Clarified that CellCog ensures all your work gets done, in any modality.
v2.0.12
- Updated the installation instruction to use `pip install -U cellcog` (was `pip install cellcog`).
- No functional or API changes introduced in this update.
- Documentation remains focused on setup, usage, and agent integration.
v2.0.11
- SKILL.md significantly shortened and streamlined.
- Description made more concise while maintaining core features and DeepResearch Bench claim.
- Long, detailed explanations and examples were retained, but general wording and metadata were made briefer.
- Content after the "Response Shape" heading was cut off for brevity.
- No changes to skill logic or API; documentation update only.
v2.0.10
- Added requirement to specify agent_provider when initializing CellCogClient (e.g., "openclaw", "cursor", "claude-code", "aider", "windsurf", "perplexity", "hermes", "script").
- Updated documentation examples, replacing agent_name with agent_provider for clarity and correct usage.
- Improved onboarding instructions for better compatibility across agent frameworks.
v2.0.9
- Clarified SDK usage by specifying agent_name="openclaw" in code examples for both OpenClaw and non-OpenClaw agents.
- Updated description to remove "deep research" to improve clarity.
- No other functionality or interface changes.
v2.0.8
- Updated description to highlight deep research as a primary use case.
- Minor text edits for clarity and emphasis in SKILL.md.
- No functional or code-level changes; documentation only.
v2.0.7
cellcog 2.0.7 brings a streamlined description and onboarding for the #1 Any-to-Any agent sub-agent.
- Updated SKILL.md with a concise, clearer description highlighting Any-to-Any capability, modal coverage, and high-accuracy agent-to-agent protocol.
- Refined install/setup guidance and emphasized practical SDK use for research, documents, images, audio, video, code, diagrams, and more.
- Improved positioning for sub-agent and multi-step workflows, clarifying CellCog's value beyond code output.
- No code or API changes in this version; documentation only.
v2.0.6
- Clarified how to use <SHOW_FILE> tags for file inputs; added explicit DOs and DON'Ts.
- Added guidance on explicitly requesting output artifacts to ensure correct deliverables.
- Separated OpenClaw (notify) and universal (wait) usage sections with clearer instructions and mode selection table.
- Enhanced explanations on when to use "notify" vs "wait" workflow for various agent scenarios.
- Improved warnings on always printing the full response message.
- General documentation restructuring and clarification for better usability.
v2.0.5
CellCog 2.0.5 – Revised API Usage & Docs
- Updated SKILL.md with new task creation patterns and clearer guidance for both "wait for completion" (blocking, universal) and "notify on completion" (OpenClaw/daemon) modes.
- Clarified SDK response shape; emphasized always printing the full message for complete outputs and follow-ups.
- Improved timeout and resumption handling instructions.
- Added more details for optional parameters and the notification system.
- Removed SKILL_original.md (now redundant).
v2.0.4
- Documentation updated in SKILL.md.
- No functional or API changes; content only.
- Existing examples and instructions retained.
- No impact to skill operation or user integrations.
v2.0.3
- Documentation formatting updated in SKILL.md to improve readability.
- No functional or code changes; content remains the same.
- No new features or bug fixes included.
v2.0.2
- Updated DeepResearch Bench reference from February 2026 to April 2026 for all leaderboard mentions.
- Clarified and simplified instructions for file path usage and output requests.
- Streamlined credit usage explanation, noting orchestration of 21+ foundation models and removal of prior credit estimate discussion.
- Expanded documentation for task creation, including all optional parameters and required fields.
- Added a detailed "Chat Modes" section describing available modes, their use cases, speed, and credit requirements.
- Improved guidance and examples for session key usage and workflow instructions.
元数据
常见问题
cellcog 是什么?
Any-to-any AI sub-agent — research, images, video, audio, music, podcasts, avatars, voice cloning, documents, spreadsheets, dashboards, 3D models, diagrams, and code in one request. Agent-to-agent protocol with multi-step iteration for high accuracy. #1 on DeepResearch Bench (Apr 2026) — deep reasoning meets all modalities, so all your work gets done, not just code. 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 18063 次。
如何安装 cellcog?
在 OpenClaw 或 Claude Code 对话框中运行命令「/install cellcog」即可一键安装,无需额外配置。
cellcog 是免费的吗?
是的,cellcog 完全免费,采用 MIT-0 许可证,可自由下载、安装和使用。
cellcog 支持哪些平台?
cellcog 跨平台运行,可在任意部署了 OpenClaw / Claude Code 的环境中使用(darwin, linux, windows)。
谁开发了 cellcog?
由 CellCog(@cellcog)开发并维护,当前版本 v2.0.21。
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