Subagent-Driven Development
About
This skill executes implementation plans by creating a fresh Claude subagent for each independent task, followed by a code review before proceeding. It maintains high quality through review gates while enabling fast, continuous progress within a single session. Use it when working on modular tasks in your current session without needing human intervention between steps.
Quick Install
Claude Code
Recommendednpx skills add obra/superpowers-skills -a claude-code/plugin add https://github.com/obra/superpowers-skillsgit clone https://github.com/obra/superpowers-skills.git ~/.claude/skills/Subagent-Driven DevelopmentCopy and paste this command in Claude Code to install this skill
Documentation
Subagent-Driven Development
Execute plan by dispatching fresh subagent per task, with code review after each.
Core principle: Fresh subagent per task + review between tasks = high quality, fast iteration
Overview
vs. Executing Plans (parallel session):
- Same session (no context switch)
- Fresh subagent per task (no context pollution)
- Code review after each task (catch issues early)
- Faster iteration (no human-in-loop between tasks)
When to use:
- Staying in this session
- Tasks are mostly independent
- Want continuous progress with quality gates
When NOT to use:
- Need to review plan first (use executing-plans)
- Tasks are tightly coupled (manual execution better)
- Plan needs revision (brainstorm first)
The Process
1. Load Plan
Read plan file, create TodoWrite with all tasks.
2. Execute Task with Subagent
For each task:
Dispatch fresh subagent:
Task tool (general-purpose):
description: "Implement Task N: [task name]"
prompt: |
You are implementing Task N from [plan-file].
Read that task carefully. Your job is to:
1. Implement exactly what the task specifies
2. Write tests (following TDD if task says to)
3. Verify implementation works
4. Commit your work
5. Report back
Work from: [directory]
Report: What you implemented, what you tested, test results, files changed, any issues
Subagent reports back with summary of work.
3. Review Subagent's Work
Dispatch code-reviewer subagent:
Task tool (code-reviewer):
Use template at skills/collaboration/requesting-code-review/code-reviewer.md
WHAT_WAS_IMPLEMENTED: [from subagent's report]
PLAN_OR_REQUIREMENTS: Task N from [plan-file]
BASE_SHA: [commit before task]
HEAD_SHA: [current commit]
DESCRIPTION: [task summary]
Code reviewer returns: Strengths, Issues (Critical/Important/Minor), Assessment
4. Apply Review Feedback
If issues found:
- Fix Critical issues immediately
- Fix Important issues before next task
- Note Minor issues
Dispatch follow-up subagent if needed:
"Fix issues from code review: [list issues]"
5. Mark Complete, Next Task
- Mark task as completed in TodoWrite
- Move to next task
- Repeat steps 2-5
6. Final Review
After all tasks complete, dispatch final code-reviewer:
- Reviews entire implementation
- Checks all plan requirements met
- Validates overall architecture
7. Complete Development
After final review passes:
- Announce: "I'm using the Finishing a Development Branch skill to complete this work."
- Switch to skills/collaboration/finishing-a-development-branch
- Follow that skill to verify tests, present options, execute choice
Example Workflow
You: I'm using Subagent-Driven Development to execute this plan.
[Load plan, create TodoWrite]
Task 1: Hook installation script
[Dispatch implementation subagent]
Subagent: Implemented install-hook with tests, 5/5 passing
[Get git SHAs, dispatch code-reviewer]
Reviewer: Strengths: Good test coverage. Issues: None. Ready.
[Mark Task 1 complete]
Task 2: Recovery modes
[Dispatch implementation subagent]
Subagent: Added verify/repair, 8/8 tests passing
[Dispatch code-reviewer]
Reviewer: Strengths: Solid. Issues (Important): Missing progress reporting
[Dispatch fix subagent]
Fix subagent: Added progress every 100 conversations
[Verify fix, mark Task 2 complete]
...
[After all tasks]
[Dispatch final code-reviewer]
Final reviewer: All requirements met, ready to merge
Done!
Advantages
vs. Manual execution:
- Subagents follow TDD naturally
- Fresh context per task (no confusion)
- Parallel-safe (subagents don't interfere)
vs. Executing Plans:
- Same session (no handoff)
- Continuous progress (no waiting)
- Review checkpoints automatic
Cost:
- More subagent invocations
- But catches issues early (cheaper than debugging later)
Red Flags
Never:
- Skip code review between tasks
- Proceed with unfixed Critical issues
- Dispatch multiple implementation subagents in parallel (conflicts)
- Implement without reading plan task
If subagent fails task:
- Dispatch fix subagent with specific instructions
- Don't try to fix manually (context pollution)
Integration
Pairs with:
- skills/collaboration/writing-plans (creates the plan)
- skills/collaboration/requesting-code-review (review template)
- skills/testing/test-driven-development (subagents follow this)
Alternative to:
- skills/collaboration/executing-plans (parallel session)
See code-reviewer template: skills/collaboration/requesting-code-review/code-reviewer.md
GitHub Repository
Frequently asked questions
What is the Subagent-Driven Development skill?
Subagent-Driven Development is a Claude Skill by obra. Skills package instructions and resources that Claude loads on demand, so Claude can perform Subagent-Driven Development-related tasks without extra prompting.
How do I install Subagent-Driven Development?
Use the install commands on this page: add Subagent-Driven Development to Claude Code as a plugin, or clone its repository into your skills directory, then restart Claude so it picks up the skill.
What category does Subagent-Driven Development belong to?
Subagent-Driven Development is in the Development category, tagged general.
Is Subagent-Driven Development free to use?
Yes. Subagent-Driven Development is listed on AIMCP and free to install.
Related Skills
qmd is a local search and indexing CLI tool that enables developers to index and search through local files using hybrid search combining BM25, vector embeddings, and reranking. It supports both command-line usage and MCP (Model Context Protocol) mode for integration with Claude. The tool uses Ollama for embeddings and stores indexes locally, making it ideal for searching documentation or codebases directly from the terminal.
This skill executes implementation plans by dispatching a fresh subagent for each independent task, with code review between tasks. It enables fast iteration while maintaining quality gates through this review process. Use it when working on mostly independent tasks within the same session to ensure continuous progress with built-in quality checks.
The mcporter skill enables developers to manage and call Model Context Protocol (MCP) servers directly from Claude. It provides commands to list available servers, call their tools with arguments, and handle authentication and daemon lifecycle. Use this skill for integrating and testing MCP server functionality in your development workflow.
This skill deploys and orchestrates Vertex AI ADK agents using A2A protocol, managing AgentCard discovery, task submission, and supporting tools like Code Execution Sandbox and Memory Bank. It enables building multi-agent systems with sequential, parallel, or loop orchestration patterns in Python, Java, or Go. Use it when asked to deploy ADK agents or orchestrate agent workflows on Google Cloud.
