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cc-feedback-loop

Route tasks to commands and teams, then log outcomes for future routing.

Updated Aug 27, 2026
Search Tags:#automation#workflow#routing#learning#task-management#team-collaboration#cc-flow
One-click install
npx skills add https://github.com/z23cc/cc-code --skill cc-feedback-loop
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: cc-feedback-loop
Source: https://github.com/z23cc/cc-code/tree/main/skills/cc-feedback-loop
Command: npx skills add https://github.com/z23cc/cc-code --skill cc-feedback-loop

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Route tasks to the right command and team, execute, record outcomes, and learn for future routing to improve overall productivity.

Core Features & Use Cases

  • Routing suggestions via cc-flow route to pair tasks with appropriate team templates.
  • Guided execution using the suggested commands and cross-team collaboration.
  • Learning and persistence via cc-flow learn to optimize future routing decisions.
  • Integration with other skills (cc-teams, cc-debugging, cc-context-tips) to close the loop.

Quick Start

Describe a task and run cc-flow route to see the recommended command, team, and past learnings.

Frequently Asked Questions about cc-feedback-loop

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I automate task routing to the right team for project planning and bug fixes?▼

Automate task routing by describing the task to receive recommendations for appropriate team templates and commands, execute the work, and log outcomes to optimize future routing decisions for project planning and bug fixes.

What is a closed-loop workflow for task management and team collaboration?▼

A closed-loop workflow for task management routes tasks to appropriate teams, guides execution, logs outcomes, and persists learnings to continuously improve future routing quality and team collaboration.

Can I use this routing approach for multi-agent collaborations?▼

Yes, you can use this routing approach for multi-agent collaborations where routing quality matters, applying guided execution and outcome logging to coordinate complex feature work across different teams.

How do I get started with task routing suggestions for my feature work?▼

Start with task routing by describing your feature work task and running the route command to see the recommended command, appropriate team, and any past learnings logged from similar previous tasks.

How does learning persistence improve future task routing decisions?▼

Learning persistence improves future task routing by recording past execution outcomes and applying those learnings to refine subsequent routing suggestions, ensuring tasks are matched with better team templates over time.

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