cc2-research-framework
CommunityCategory-driven, reproducible research workflow.
Authormanutej
Version1.0.0
Installs0
System Documentation
What problem does it solve?
This Skill provides a formal CC2.0 seven-function research workflow to organize and coordinate AI research tasks, enabling reproducible, structure-driven inquiry across multiple streams.
Core Features & Use Cases
- OBSERVE: Capture workspace state and external sources to seed structured reasoning.
- REASON: Derive insights and identify gaps from observed data.
- CREATE: Generate artifacts (prompts, code, docs) shaped by reasoning outcomes.
- ORCHESTRATE: Coordinate parallel research streams for coordinated progress.
- LEARN: Extract patterns and adaptations to guide subsequent cycles.
- VERIFY: Apply property-testing to validate categorical assumptions and laws.
- DEPLOY: Integrate findings into the broader research framework and workflows.
Quick Start
Clone the repository, set up a Python environment, and run the CC2.0 research cycle to trigger OBSERVE → REASON → CREATE → ORCHESTRATE → LEARN → VERIFY → DEPLOY.
Dependency Matrix
Required Modules
None requiredComponents
Standard package💻 Claude Code Installation
Recommended: Let Claude install automatically. Simply copy and paste the text below to Claude Code.
Please help me install this Skill: Name: cc2-research-framework Download link: https://github.com/manutej/categorical-meta-prompting/archive/main.zip#cc2-research-framework Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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