subagent-driven-development

Executes implementation plans by dispatching fresh subagents per task with two-stage review.

Updated Jun 5, 2026
One-click install
npx skills add https://github.com/xu1713/openhorse --skill subagent-driven-development-xu1713
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: subagent-driven-development
Source: https://github.com/xu1713/openhorse/tree/main/openhorse/openhorse/skills/software-development/subagent-driven-development
Command: npx skills add https://github.com/xu1713/openhorse --skill subagent-driven-development-xu1713

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve? Executing a multi-task implementation plan in a single session leads to context pollution, inconsistent quality, and missed spec requirements. This Skill orchestrates plan execution by delegating each task to a fresh subagent and enforcing systematic review between tasks. ## Core Features & Use Cases - Per-Task Subagent Dispatch: Each plan task runs in a fresh subagent with complete context, preventing accumulated state from confusing later work. - Two-Stage Review: Every task passes a spec compliance review first, then a code quality review, with fix-and-re-review loops until approved. - Final Integration Review: After all tasks complete, a reviewer checks cross-task consistency, runs the full test suite, and confirms merge readiness. - Use Case: You have a 5-task authentication plan from the writing-plans skill. This Skill dispatches an implementer per task, verifies each against the spec, reviews code quality, and delivers a fully tested feature branch. ## Quick Start Execute the implementation plan in docs/plans/feature-plan.md using subagent-driven development with per-task spec and quality reviews.

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 with AI subagents?

Read the plan once, extract all tasks into a todo list, then dispatch a fresh implementer subagent per task with the full task text in context. Follow each implementation with a spec compliance review and a code quality review before marking the task complete.

What is the two-stage review process for subagent code?

The first stage checks spec compliance: does the implementation match the original task requirements exactly, with no scope creep. The second stage checks code quality: conventions, error handling, test coverage, and security. Spec review always runs before quality review.

Why use a fresh subagent for each task instead of one session?

Fresh subagents prevent context pollution from accumulated state, giving each task clean, focused context without confusion from prior tasks' code or reasoning. The trade-off is more subagent invocations, but issues are caught early instead of compounding.

How big should each task be for subagent delegation?

Each task should represent 2-5 minutes of focused work, such as creating a single model, adding one endpoint, or writing a utility function. Tasks like 'implement the entire authentication system' are too large and should be split during planning.

What happens when a reviewer subagent finds issues?

The implementer subagent (or a new fix subagent) addresses the specific issues, then the reviewer re-reviews the work. This loop repeats until approval, and you never move to the next task while either review has open issues.

When should I not use subagent-driven development?

Avoid it when you have no written implementation plan, when tasks are tightly coupled and touch the same files, or when you would skip the review stages. Dispatching parallel implementers on shared files and skipping reviews are explicit anti-patterns.