Delegate deterministic tasks to the CCS CLI with auto-profile selection.
npx skills add https://github.com/kaitranntt/ccs --skill ccs-delegation
Please help me install this Agent Skill. Skill: ccs-delegation Source: https://github.com/kaitranntt/ccs/tree/main/.claude/skills/ccs-delegation Command: npx skills add https://github.com/kaitranntt/ccs --skill ccs-delegation
Developers often hit usage limits on powerful AI models for simple, repetitive tasks, leading to interruptions and increased costs. This Skill intelligently delegates these mechanical tasks to more cost-effective models, ensuring continuous productivity and significant token savings.
/ccs:glm "add unit tests for the authentication module" to save costs and maintain your main session's context.Delegate the task of refactoring auth.js to use async/await to the GLM model.
High-intent search queries and answers about installing and using this skill.
Delegation routes deterministic tasks like typo fixes, refactoring, and test additions to cost-effective models (GLM, Kimi) via the CCS CLI. This preserves your primary Claude session for complex problem-solving while reducing token costs by up to 81% on mechanical work.
Yes. Run parallel workflows by delegating specific tasks to GLM or Kimi using ccs {profile} while maintaining your Claude Pro session for strategic design. The Skill auto-selects the appropriate profile from ~/.ccs/config.json based on task complexity.
Delegate well-defined, deterministic tasks: unit test generation, code refactoring, documentation updates, typo corrections, and codebase analysis. These mechanical tasks cost significantly less on GLM and Kimi while freeing premium model capacity for design and reasoning work.
Configure ~/.ccs/config.json with your model profiles, then delegate using ccs {profile} -p task or ccs {profile}:continue syntax. The Skill automatically selects the cost-optimized profile and reports execution metrics including cost, duration, session ID, and exit code.
Delegation returns detailed results: token cost, execution duration, session ID for tracking, and exit code. This transparency helps you measure savings and verify task completion across your multi-model workflow.
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