Setup & Installation
Or with the ClawHub CLI, for registry-managed skill folders outside a full OpenClaw workspace:
Version History
cirf 0.1.2 Changelog - Added README.md and SECURITY.md for improved project documentation and security guidelines. - Removed _meta.json file. - Updated SKILL.md with clarified AI agent instructions, collaborative research philosophy, activation protocol, and detailed agent workflow guidance. - Enhanced workspace management documentation and file structure explanations.
What This Skill Does
CIRF is a file-based framework for conducting crypto research through human-AI collaboration. It defines agent personas, structured workflows, and workspace management to guide analysis of crypto projects, sectors, and market dynamics. Supports both collaborative check-in mode and autonomous execution.
Pre-built agent personas and methodology-driven workflows produce more consistent, citable research than open-ended AI prompting.
When to use it
- Analyzing tokenomics of a new DeFi protocol
- Running competitive landscape research on a crypto sector
- Evaluating blockchain architecture and security tradeoffs
- Transforming research findings into platform-ready content
- QA review of an existing crypto research report
Example Workflow
Here's how your AI assistant might use this skill in practice.
User asks: Run tokenomics-analysis for a new DeFi lending protocol
- 1Read framework/agents/research-analyst.yaml to embody the research analyst persona
- 2Read framework/core-config.yaml for user preferences and registered workflows
- 3Load framework/workflows/tokenomics-analysis/objectives.md and template.md
- 4Present initial findings and check in with user for validation before proceeding
- 5Generate output following the template and save to workspaces/{project-id}/outputs/
Structured tokenomics report saved to workspace outputs folder, with sourced claims and identified risks