What happens if my CCS CLI is not configured?

The skill will detect the missing configuration and provide an error message instructing you to run 'ccs doctor' to set up your profiles.

How does the skill decide which model to use?

The skill scans your task for keywords. It selects 'Kimi' for tasks requiring deep reasoning or long context, and 'GLM' for deterministic tasks like bug fixes, typos, and unit tests.

Can I manually choose a profile instead of using auto-select?

Yes, you can use override flags such as '--glm' or '--kimi' in your command to force the skill to use a specific profile from your configuration.

What is the primary benefit of CCS Delegation?

It allows you to save costs and optimize performance by automatically routing simple or specialized tasks to cheaper or higher-context models like GLM and Kimi instead of using your main Claude instance for everything.

Does it support continuing a previous conversation?

Yes, by using the 'ccs:continue' pattern, the skill identifies the most recent session and maintains context for follow-up tasks.

CCS Delegation

Name: CCS Delegation
Author: kaitranntt

bykaitranntt

•

323

Productivity & Workflow

Automates task delegation to cost-optimized or high-reasoning AI models using the CCS CLI directly within your workflow.

About

CCS Delegation optimizes your Claude Code experience by intelligently offloading deterministic and specialized tasks to alternative models like GLM and Kimi. By analyzing your input for keywords related to reasoning, context length, or cost-sensitivity, the skill automatically selects the most efficient profile from your local configuration. It handles prompt enhancement, context gathering, and CLI execution, allowing you to reserve primary model capacity for complex architecture while automating routine refactoring, testing, and documentation tasks through the CCS ecosystem.

Key Features

Real-time execution reporting including cost (USD), duration, and session IDs
Manual profile overrides via simple CLI flags like --glm or --kimi
323 GitHub stars
Intelligent auto-selection of GLM, Kimi, or custom profiles based on task requirements
Context-aware prompt enhancement that automatically includes relevant file data and success criteria
Session continuation support for multi-step tasks across delegated models

Use Cases

Delegating routine unit test generation and documentation updates to cost-effective models
Executing repetitive refactoring tasks across multiple files using deterministic CLI-based workflows
Offloading deep architectural analysis or large codebase reasoning to long-context models like Kimi

About

Key Features

Real-time execution reporting including cost (USD), duration, and session IDs
Manual profile overrides via simple CLI flags like --glm or --kimi
323 GitHub stars
Intelligent auto-selection of GLM, Kimi, or custom profiles based on task requirements
Context-aware prompt enhancement that automatically includes relevant file data and success criteria
Session continuation support for multi-step tasks across delegated models

Use Cases

Delegating routine unit test generation and documentation updates to cost-effective models
Executing repetitive refactoring tasks across multiple files using deterministic CLI-based workflows
Offloading deep architectural analysis or large codebase reasoning to long-context models like Kimi