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subagent-driven-development

Dispatch AI subagents to implement tasks with spec and code quality reviews.

1|Updated Jan 31, 2026
Search Tags:#code review#task management#prompt engineering#ai development#iterative development#subagent
One-click install
npx skills add https://github.com/allanninal/claude-code-skills --skill subagent-driven-development-allanninal
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: subagent-driven-development
Source: https://github.com/allanninal/claude-code-skills/tree/main/skills/subagent-driven-development
Command: npx skills add https://github.com/allanninal/claude-code-skills --skill subagent-driven-development-allanninal

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill streamlines the implementation of complex plans by breaking them down into independent tasks, each handled by a dedicated AI subagent with rigorous review stages, ensuring high-quality code and adherence to specifications.

Core Features & Use Cases

  • Task Decomposition: Automatically breaks down a development plan into manageable, independent tasks.
  • Subagent Dispatch: Assigns each task to a fresh AI subagent for implementation.
  • Two-Stage Review: Implements a mandatory spec compliance review followed by a code quality review for each task.
  • Iterative Refinement: Manages review feedback loops, ensuring issues are fixed before proceeding.
  • Use Case: Implementing a new feature from a detailed plan, where each part of the feature can be developed and reviewed independently, leading to faster and more reliable development cycles.

Quick Start

Use the subagent-driven-development skill to execute the implementation plan located at /path/to/your/plan.md.

Frequently Asked Questions about subagent-driven-development

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

FAQPage Schema
How do I execute an implementation plan using AI subagents?▼

Executing an implementation plan with AI subagents involves breaking the plan into independent tasks and dispatching a dedicated subagent for each. The process enforces spec compliance and code quality reviews through iterative feedback loops within a single session.

What is subagent-driven development for iterative AI coding?▼

Subagent-driven development is an AI development technique that decomposes complex plans into manageable tasks. It assigns each task to a fresh AI subagent, running two-stage reviews to ensure spec compliance and code quality before proceeding.

How do I automate code review and spec compliance for AI-generated code?▼

Automating code review for AI-generated code requires a two-stage process: first checking spec compliance, then evaluating code quality. The system manages iterative feedback loops, ensuring all issues are fixed before the task advances.

Does subagent-driven development work without external dependencies?▼

Yes, subagent-driven development operates without external dependencies. It manages complex development workflows requiring structured task management and quality assurance entirely within a single session using internal scripts and references.

When should I use task decomposition with AI subagents?▼

Task decomposition with AI subagents is ideal when implementing features from detailed plans where parts can be developed independently. It suits complex workflows requiring structured task management, rigorous spec compliance, and automated code quality reviews.

What is the best way to manage iterative feedback loops for AI task implementation?▼

The best way to manage iterative feedback loops during AI task implementation is to orchestrate subagents that handle review feedback automatically. This ensures issues are fixed iteratively before proceeding, leading to faster and more reliable development cycles.

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