Best practices for using kimi-cc in team collaboration
Complete workflow for realizing efficient team use of kimi-cc:
- Environmental standardization::
- Creating a docker-compose.yml template for team sharing
- Harmonized configuration of multiplexed tokens (each member is assigned a separate token)
- Create a lexicon of public prompts (e.g., Confluence template)
- Development Process Integration::
- Git pre-commit hooks automatically review generated code
- Integration with CI/CD pipelines (e.g. test case generation)
- Create a code review checklist (specifically checking AI-generated sections)
- Performance Monitoring::
- Viewing member-by-member API usage via kimi-cc stats
- Regularly analyze the merge pass rate of generated codes
- Record time savings data for typical scenarios
Recommended team collaboration toolchain:
- Dual model validation in conjunction with GitHub Copilot
- Marking up AI-generated paragraphs with the Code Review plugin
- Integrate Jira to automatically generate technical solution documentation
Special Note: A copyright compliance review process for AI-generated code needs to be established
This answer comes from the articleKimi CC: An Open Source Tool for Driving Claude Code with Kimi ModelsThe
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