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cc-team-builder

Analyzes tasks and codebase to propose optimal agent team compositions for execution.

Updated Aug 27, 2026
Search Tags:#workflow-automation#codebase-analysis#task-analysis#agent-selection#team-building#execution-dispatch
One-click install
npx skills add https://github.com/z23cc/cc-code --skill cc-team-builder
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: cc-team-builder
Source: https://github.com/z23cc/cc-code/tree/main/skills/cc-team-builder
Command: npx skills add https://github.com/z23cc/cc-code --skill cc-team-builder

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Dynamic team composition solves the challenge of assembling the right mix of agents for a task, adapting to codebase signals, language, and past performance data to maximize outcomes.

Core Features & Use Cases

  • Analyze the task description, affected files, and requirements to determine the optimal agent mix.
  • Check past success by querying the wisdom system and adjusting recommendations based on prior outcomes.
  • Recommend a Core team plus Specialists and Optional roles, with a defined execution mode and estimated loops.
  • Output a dispatch command that integrates with cc-teams, cc-work, and related tooling to automate task execution.

Quick Start

Provide a task description and affected files to generate and dispatch the optimal agent team for execution.

Frequently Asked Questions about cc-team-builder

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

FAQPage Schema
How do I assemble the right agent team for a complex codebase task?▼

Agent team composition works by analyzing your task description and affected codebase to recommend an optimal agent mix. It scopes requirements by file types, complexity, and past performance data to maximize execution outcomes.

How can I automate task dispatch using the recommended agent selection?▼

Automate task dispatch by generating a dispatch command integrating with cc-teams and cc-work. This provides a structured plan for post-task execution based on the proposed agent composition and defined execution mode.

What factors are analyzed to determine the optimal agent mix for workflow automation?▼

The optimal agent mix is determined by analyzing task descriptions, affected file types, and task complexity. It also queries the wisdom system to check past success rates and adjusts recommendations based on prior outcomes.

Do I need to provide affected files to generate an execution plan for my codebase?▼

Yes, you need to provide affected files alongside the task description to generate and dispatch the optimal agent team. This allows the system to scope tasks accurately by file types and complexity for execution.

Can past performance data adjust agent selection for task execution?▼

Yes, past performance data adjusts agent selection by querying the wisdom system for prior outcomes. The system modifies its recommended Core team and Specialists based on historical success rates for similar tasks.

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