kimi-supervisor
CommunityToken-efficient multi-agent orchestration.
Software Engineering#research#multi-agent#orchestration#token efficiency#cost optimization#codebase exploration
AuthorOpenSourceSam
Version1.0.0
Installs0
System Documentation
What problem does it solve?
This Skill drastically reduces the token costs associated with complex research and exploration tasks by offloading the bulk of the work to more cost-effective AI models like Kimi and MiniMax, while Claude retains strategic control.
Core Features & Use Cases
- Token Savings: Achieves 85-93% token savings on exploration tasks compared to direct Claude usage.
- Multi-Agent Orchestration: Claude delegates research to Kimi, which synthesizes findings, and then uses MiniMax for verification before Claude consumes the summarized output.
- Use Case: When Claude needs to research a large codebase for specific patterns or information, it can use Kimi to perform the deep dive and MiniMax to validate the findings, providing Claude with a concise, verified summary instead of raw, expensive output.
Quick Start
Use the kimi-supervisor skill to research codebase patterns by having Claude delegate tasks to Kimi for research and MiniMax for review.
Dependency Matrix
Required Modules
None requiredComponents
scriptsreferences
💻 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: kimi-supervisor Download link: https://github.com/OpenSourceSam/v2_heras_garden/archive/main.zip#kimi-supervisor Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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