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cellcog

Deep Research

by CellCog · GitHub ↗ · v1.0.20 · MIT-0
darwinlinuxwindows ✓ Security Clean
7652
Downloads
7
Stars
0
Active Installs
21
Versions
Install in OpenClaw
/install deep-research-cellcog
Description
AI deep research powered by CellCog. Market research, competitive analysis, investment research, academic research, due diligence, literature reviews with citations, financial analysis, crypto research, news intelligence. Multi-source synthesis across hundreds of sources. #1 on DeepResearch Bench (Apr 2026).
Usage Guidance
Before installing, treat CellCog as an external service: only send confidential, regulated, financial, or proprietary material if your organization permits it, and review generated HTML/PDF reports before sharing or rendering them in trusted environments.
Capability Assessment
Credentials
External network/API use is proportionate for a hosted research service, but users may submit sensitive diligence, financial, or business material and should apply their own data-handling rules.
Install Mechanism
The artifact is a single non-executable SKILL.md with disclosed requirements for python3, the cellcog dependency, and CELLCOG_API_KEY setup.
Instruction Scope
The instructions clearly show use of CellCog and an API key, but they do not add an explicit warning that research prompts and inputs are sent to an external provider.
Persistence & Privilege
The skill does not define background persistence, privilege escalation, credential harvesting, automatic file writes, or destructive local actions; report formats are described as outputs only.
Purpose & Capability
The skill's stated purpose is deep research through CellCog, and its examples consistently call the CellCog SDK for research, analysis, and report generation.
How to Use
  1. Make sure OpenClaw is installed (local or Docker)
  2. Run the install command in chat: /install deep-research-cellcog
  3. After installation, invoke the skill by name or use /deep-research-cellcog
  4. Provide required inputs per the skill's parameter spec and get structured output
Version History
v1.0.20
Content updated.
v1.0.19
Content updated.
v1.0.18
Content updated.
v1.0.17
Display title updated.
v1.0.16
Display title updated.
v1.0.15
- Skill has been renamed from "research-cog" to "deep-research-cellcog" for improved clarity and alignment. - Updated DeepResearch Bench ranking reference from April 2026 to July 2026, and clarified that rankings are updated frequently. - Removed the outdated skill-card.md file. - Minor improvements to headings, section naming, and prompts for better consistency. - No changes to API usage or research capability—documentation and naming only.
v1.0.14
- Added explicit requirements for Python 3 and the CELLCOG_API_KEY environment variable in SKILL metadata. - No code or logic changes; documentation/metadata update only.
v1.0.13
- Expanded description to highlight support for financial analysis, crypto research, and news intelligence. - Clarified agent usage instructions: separated examples for OpenClaw and other agents. - Minor documentation improvements for accuracy and clarity.
v1.0.12
- Documentation updated for clarity and completeness, especially on usage instructions and integrations. - Installation and example usage for Cursor and other agents improved, including code imports. - Skill description refined for conciseness and accuracy. - Minor formatting and organizational enhancements throughout the documentation.
v1.0.11
**This update improves clarity, usage instructions, and research focus.** - Simplified and clarified skill description and instructions for faster onboarding. - Separated and streamlined SDK usage examples for OpenClaw and other agents. - Moved detailed SDK and setup references to the start, making first steps clearer. - Improved examples and tips for specifying research prompts and output formats. - Reduced redundancy and removed extraneous information for easier reading. - Retained all use case, feature, and prompt examples while making them more accessible.
v1.0.10
- Major documentation update with detailed research use cases and example prompts. - Added sections covering competitive analysis, market research, investment analysis, academic research, and due diligence examples. - Explained output formats (interactive HTML, PDF, markdown, plain text) with recommendations. - Expanded guidance on chat modes: agent, agent team, and agent team max. - Provided advanced tips for citation handling, structuring analysis, and improving research quality. - Included leaderboard recognition: #1 on DeepResearch Bench (Apr 2026).
v1.0.9
Version 1.0.9 - Major rewrite of documentation for clarity and brevity - Expanded description to highlight more research and output types - Added clear lists of supported research areas and output formats - Presented core multi-source and citation features more prominently - Clarified citation policy and chat mode usage - Added references to related skills for finance, crypto, data, and news analysis
v1.0.8
- Added OpenClaw agent usage instructions and example to the SDK setup section. - Clarified differences between "OpenClaw agents" (fire-and-forget) and other agent invocation methods. - Updated SDK example code blocks for more precise usage guidance. - Minor editorial updates and formatting for improved clarity.
v1.0.7
- Updated the Quick Pattern section to a simplified "Quick start" example, providing a basic usage pattern. - Added clear guidance to refer to the `cellcog` skill for full SDK/API details, including delivery modes and advanced usage. - Removed detailed asynchronous usage instructions to streamline documentation and avoid redundancy with the main CellCog skill. - Clarified separation of research-cog capabilities from the core SDK/API setup.
v1.0.6
- Updated DeepResearch Bench achievement date to April 2026 in all mentions. - No functional or instructional changes; documentation remains consistent except for the updated benchmark recognition.
v1.0.5
- Refined the skill description for clarity and added additional use cases and output formats. - Added a homepage link and specified supported operating systems in metadata. - Updated the description to emphasize multi-source synthesis and broader research capabilities (including due diligence and literature reviews). - No behavioral or functional changes to the skill code; documentation update only.
v1.0.4
Expanded guidance on research chat modes - Added a detailed table describing when to use `"agent"`, `"agent team"`, and the new `"agent team max"` chat modes for different research scenarios. - Provided recommendations for scenarios requiring the highest accuracy, such as high-stakes due diligence or cutting-edge academic research. - Clarified that `"agent team"` remains the default for most research, but `"agent team max"` is available for institutional-grade analysis (requires ≥2,000 credits). - No code or interface changes—documentation update only.
v1.0.3
- Added author information and explicit dependency listing for `cellcog` in the skill metadata. - Minor improvements to the prerequisites section, clarifying that `cellcog` is required for SDK setup. - No functionality changes; documentation and metadata only.
v1.0.2
- Added "#1 on DeepResearch Bench (Feb 2026)" accolade to the description and introduction. - Included leaderboard link for transparency: https://huggingface.co/spaces/muset-ai/DeepResearch-Bench-Leaderboard. - No functionality or API changes; documentation update highlighting recent research benchmark performance.
v1.0.1
- Added OpenClaw metadata with an emoji identifier. - Updated SDK usage instructions for v1.0+, introducing a new fire-and-forget research pattern with notification-based completion (no polling required). - Clarified that citations are not provided automatically and must be explicitly requested in the prompt, detailing how to format/position them. - Improved documentation for data accuracy, output formats, and example prompts. - Minor simplifications to setup instructions and SDK references.
Metadata
Slug deep-research-cellcog
Version 1.0.20
License MIT-0
All-time Installs 0
Active Installs 0
Total Versions 21
Frequently Asked Questions

What is Deep Research?

AI deep research powered by CellCog. Market research, competitive analysis, investment research, academic research, due diligence, literature reviews with citations, financial analysis, crypto research, news intelligence. Multi-source synthesis across hundreds of sources. #1 on DeepResearch Bench (Apr 2026). It is an AI Agent Skill for Claude Code / OpenClaw, with 7652 downloads so far.

How do I install Deep Research?

Run "/install deep-research-cellcog" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.

Is Deep Research free?

Yes, Deep Research is completely free, licensed under MIT-0. You can download, install and use it at no cost.

Which platforms does Deep Research support?

Deep Research is cross-platform and runs anywhere OpenClaw / Claude Code is available (darwin, linux, windows).

Who created Deep Research?

It is built and maintained by CellCog (@cellcog); the current version is v1.0.20.

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