subagent-driven-development

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

Updated May 28, 2026
One-click install
npx skills add https://github.com/mpmf/SDD_Base --skill subagent-driven-development-mpmf
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: subagent-driven-development
Source: https://github.com/mpmf/SDD_Base/tree/main/.opencode/skills/superpowers/subagent-driven-development
Command: npx skills add https://github.com/mpmf/SDD_Base --skill subagent-driven-development-mpmf

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve? Executing a multi-task implementation plan in a single AI session leads to context pollution, skipped reviews, and inconsistent quality. This Skill orchestrates plan execution by dispatching a fresh subagent for each task and enforcing spec compliance and code quality reviews after every task. ## Core Features & Use Cases - Fresh Subagent Per Task: Each task runs in an isolated subagent context with exactly the instructions and context it needs, preserving the controller's context for coordination. - Two-Stage Review Gates: Every task passes a spec compliance review first, then a code quality review, with fix-and-re-review loops until approved. - Status-Based Escalation Handling: Implementer subagents report DONE, DONE_WITH_CONCERNS, NEEDS_CONTEXT, or BLOCKED, and the controller responds with more context, a more capable model, or task decomposition. - Use Case: You have a written implementation plan with 5 mostly independent tasks. This Skill extracts all tasks, dispatches implementer and reviewer subagents for each, and finishes with a final whole-implementation code review before merging the branch. ## Quick Start Use subagent-driven development to execute the implementation plan in docs/plans/feature-plan.md task by task with reviews after each task.

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 with full text into a todo list, then dispatch a fresh implementer subagent per task with the complete task text and context. After each task, run a spec compliance review followed by a code quality review before marking it complete.

What is the difference between subagent-driven development and executing plans in a parallel session?▼

Subagent-driven development stays in the current session with fresh subagents per task and no human-in-loop between tasks, enabling faster iteration. Executing plans uses a separate parallel session, which involves a context switch and handoff.

When should I not use subagent-driven development?▼

Avoid it when tasks are tightly coupled and cannot be implemented independently, when there is no written implementation plan, or when you have not yet brainstormed the approach. Tightly coupled work is better done manually or in a single continuous session.

What should I do when an implementer subagent reports BLOCKED?▼

Assess the blocker: provide more context and re-dispatch if it is a context problem, use a more capable model if the task needs more reasoning, break the task into smaller pieces if it is too large, or escalate to the human if the plan itself is wrong. Never force the same model to retry unchanged.

Why must spec compliance review come before code quality review?▼

Spec compliance verifies the implementer built exactly what was requested, nothing more or less, by reading the actual code rather than trusting the report. Reviewing code quality first wastes effort on code that may need to change to meet the spec.

Can I dispatch multiple implementer subagents in parallel?▼

No. Dispatching multiple implementation subagents in parallel causes conflicts between their changes. Tasks are executed sequentially, with each task completing both review stages before the next implementer is dispatched.