subagent-driven-development — for Claude Code subagent-driven-development, superpowers, official, for Claude Code, ide skills, subagent-driven development, task automation, independent task execution, two-stage review process, spec compliance review, Claude Code

Verified
v1.0.0

About this Skill

Ideal for Advanced AI Agents like Claude Code, AutoGPT, and LangChain needing efficient task management and code review capabilities. Subagent-driven development is a method of executing implementation plans by dispatching fresh subagents per task, ensuring spec compliance and code quality reviews.

Features

Dispatching implementer subagents for task automation
Executing two-stage reviews for spec compliance and code quality
Utilizing isolated context for subagents to prevent context pollution
Enabling faster iteration through parallel task execution

# Core Topics

obra obra
[113.6k]
[9110]
Updated: 3/26/2026

Killer-Skills Review

Decision support comes first. Repository text comes second.

Reviewed Landing Page Review Score: 11/11

Killer-Skills keeps this page indexable because it adds recommendation, limitations, and review signals beyond the upstream repository text.

Original recommendation layer Concrete use-case guidance Explicit limitations and caution Quality floor passed for review Locale and body language aligned
Review Score
11/11
Quality Score
86
Canonical Locale
en
Detected Body Locale
en

Ideal for Advanced AI Agents like Claude Code, AutoGPT, and LangChain needing efficient task management and code review capabilities. Subagent-driven development is a method of executing implementation plans by dispatching fresh subagents per task, ensuring spec compliance and code quality reviews.

Core Value

Empowers agents to execute implementation plans with precision by dispatching fresh subagents per task, utilizing two-stage review processes for spec compliance and code quality, and leveraging isolated context for focused task execution. This superpower enables fast iteration and high-quality output through the use of specialized subagents and TodoWrite task management.

Ideal Agent Persona

Ideal for Advanced AI Agents like Claude Code, AutoGPT, and LangChain needing efficient task management and code review capabilities.

Capabilities Granted for subagent-driven-development

Automating independent task execution within a single session
Generating high-quality code through two-stage review processes
Debugging spec compliance and code quality issues with isolated subagent context

! Prerequisites & Limits

  • Requires ability to dispatch and manage subagents
  • Needs isolated context for each subagent
  • Dependent on TodoWrite for task management

Source Boundary

The section below is imported from the upstream repository and should be treated as secondary evidence. Use the Killer-Skills review above as the primary layer for fit, risk, and installation decisions.

Curated Collection Review

Reviewed In Curated Collections

This section shows how Killer-Skills has already collected, reviewed, and maintained this skill inside first-party curated paths. For operators and crawlers alike, this is a stronger signal than treating the upstream README as the primary story.

Reviewed Collection

Claude Code Workflow Tools to Install First

Reviewed 2026-04-17

Reviewed on 2026-04-17 for setup clarity, maintainer reliability, review coverage, and operator handoff readiness. We kept the tools that make Claude Code easier to trial and easier to standardize.

People landing here usually already know they want Claude Code. What they need next is a smaller list tied to review, guardrails, and handoff instead of another broad skills roundup.

6 entries Killer-Skills editorial review with monthly collection checks.
Reviewed Collection

Windsurf Workflow Tools to Install First

Reviewed 2026-04-17

Reviewed on 2026-04-17 for setup clarity, maintainer reliability, review support, and handoff readiness. We kept the tools that make Windsurf easier to trial, explain, and standardize.

People landing here usually already know they want Windsurf. What they need next is a smaller list tied to coding speed, review support, rules sync, and handoff instead of another broad skills roundup.

5 entries Killer-Skills editorial review with monthly collection checks.
Reviewed Collection

12 Official AI Agent Skills & Trusted Tools to Install First

Reviewed 2026-04-16

Reviewed on 2026-04-16 for first-party ownership, documentation quality, install clarity, and production relevance. This is the safest collection to use as a default starting point.

We prioritize this page because it lets users verify trust first and then move into one clear installation path instead of bouncing across more repo lists.

12 entries Maintained through Killer-Skills editorial review with trust, install-path, and operator checks.
After The Review

Decide The Next Action Before You Keep Reading Repository Material

Killer-Skills should not stop at opening repository instructions. It should help you decide whether to install this skill, when to cross-check against trusted collections, and when to move into workflow rollout.

Labs Demo

Browser Sandbox Environment

⚡️ Ready to unleash?

Experience this Agent in a zero-setup browser environment powered by WebContainers. No installation required.

Boot Container Sandbox

FAQ & Installation Steps

These questions and steps mirror the structured data on this page for better search understanding.

? Frequently Asked Questions

What is subagent-driven-development?

Ideal for Advanced AI Agents like Claude Code, AutoGPT, and LangChain needing efficient task management and code review capabilities. Subagent-driven development is a method of executing implementation plans by dispatching fresh subagents per task, ensuring spec compliance and code quality reviews.

How do I install subagent-driven-development?

Run the command: npx killer-skills add obra/superpowers/subagent-driven-development. It works with Cursor, Windsurf, VS Code, Claude Code, and 19+ other IDEs.

What are the use cases for subagent-driven-development?

Key use cases include: Automating independent task execution within a single session, Generating high-quality code through two-stage review processes, Debugging spec compliance and code quality issues with isolated subagent context.

Which IDEs are compatible with subagent-driven-development?

This skill is compatible with Cursor, Windsurf, VS Code, Trae, Claude Code, OpenClaw, Aider, Codex, OpenCode, Goose, Cline, Roo Code, Kiro, Augment Code, Continue, GitHub Copilot, Sourcegraph Cody, and Amazon Q Developer. Use the Killer-Skills CLI for universal one-command installation.

Are there any limitations for subagent-driven-development?

Requires ability to dispatch and manage subagents. Needs isolated context for each subagent. Dependent on TodoWrite for task management.

How To Install

  1. 1. Open your terminal

    Open the terminal or command line in your project directory.

  2. 2. Run the install command

    Run: npx killer-skills add obra/superpowers/subagent-driven-development. The CLI will automatically detect your IDE or AI agent and configure the skill.

  3. 3. Start using the skill

    The skill is now active. Your AI agent can use subagent-driven-development immediately in the current project.

Upstream Repository Material

The section below is imported from the upstream repository and should be treated as secondary evidence. Use the Killer-Skills review above as the primary layer for fit, risk, and installation decisions.

Upstream Source

subagent-driven-development

Boost development speed with subagent-driven development, an AI agent skill for independent task automation. Discover how it benefits developers and try it...

SKILL.md
Readonly
Upstream Repository Material
The section below is imported from the upstream repository and should be treated as secondary evidence. Use the Killer-Skills review above as the primary layer for fit, risk, and installation decisions.
Supporting Evidence

Subagent-Driven Development

Execute plan by dispatching fresh subagent per task, with two-stage review after each: spec compliance review first, then code quality review.

Why subagents: You delegate tasks to specialized agents with isolated context. By precisely crafting their instructions and context, you ensure they stay focused and succeed at their task. They should never inherit your session's context or history — you construct exactly what they need. This also preserves your own context for coordination work.

Core principle: Fresh subagent per task + two-stage review (spec then quality) = high quality, fast iteration

When to Use

dot
1digraph when_to_use { 2 "Have implementation plan?" [shape=diamond]; 3 "Tasks mostly independent?" [shape=diamond]; 4 "Stay in this session?" [shape=diamond]; 5 "subagent-driven-development" [shape=box]; 6 "executing-plans" [shape=box]; 7 "Manual execution or brainstorm first" [shape=box]; 8 9 "Have implementation plan?" -> "Tasks mostly independent?" [label="yes"]; 10 "Have implementation plan?" -> "Manual execution or brainstorm first" [label="no"]; 11 "Tasks mostly independent?" -> "Stay in this session?" [label="yes"]; 12 "Tasks mostly independent?" -> "Manual execution or brainstorm first" [label="no - tightly coupled"]; 13 "Stay in this session?" -> "subagent-driven-development" [label="yes"]; 14 "Stay in this session?" -> "executing-plans" [label="no - parallel session"]; 15}

vs. Executing Plans (parallel session):

  • Same session (no context switch)
  • Fresh subagent per task (no context pollution)
  • Two-stage review after each task: spec compliance first, then code quality
  • Faster iteration (no human-in-loop between tasks)

The Process

dot
1digraph process { 2 rankdir=TB; 3 4 subgraph cluster_per_task { 5 label="Per Task"; 6 "Dispatch implementer subagent (./implementer-prompt.md)" [shape=box]; 7 "Implementer subagent asks questions?" [shape=diamond]; 8 "Answer questions, provide context" [shape=box]; 9 "Implementer subagent implements, tests, commits, self-reviews" [shape=box]; 10 "Dispatch spec reviewer subagent (./spec-reviewer-prompt.md)" [shape=box]; 11 "Spec reviewer subagent confirms code matches spec?" [shape=diamond]; 12 "Implementer subagent fixes spec gaps" [shape=box]; 13 "Dispatch code quality reviewer subagent (./code-quality-reviewer-prompt.md)" [shape=box]; 14 "Code quality reviewer subagent approves?" [shape=diamond]; 15 "Implementer subagent fixes quality issues" [shape=box]; 16 "Mark task complete in TodoWrite" [shape=box]; 17 } 18 19 "Read plan, extract all tasks with full text, note context, create TodoWrite" [shape=box]; 20 "More tasks remain?" [shape=diamond]; 21 "Dispatch final code reviewer subagent for entire implementation" [shape=box]; 22 "Use superpowers:finishing-a-development-branch" [shape=box style=filled fillcolor=lightgreen]; 23 24 "Read plan, extract all tasks with full text, note context, create TodoWrite" -> "Dispatch implementer subagent (./implementer-prompt.md)"; 25 "Dispatch implementer subagent (./implementer-prompt.md)" -> "Implementer subagent asks questions?"; 26 "Implementer subagent asks questions?" -> "Answer questions, provide context" [label="yes"]; 27 "Answer questions, provide context" -> "Dispatch implementer subagent (./implementer-prompt.md)"; 28 "Implementer subagent asks questions?" -> "Implementer subagent implements, tests, commits, self-reviews" [label="no"]; 29 "Implementer subagent implements, tests, commits, self-reviews" -> "Dispatch spec reviewer subagent (./spec-reviewer-prompt.md)"; 30 "Dispatch spec reviewer subagent (./spec-reviewer-prompt.md)" -> "Spec reviewer subagent confirms code matches spec?"; 31 "Spec reviewer subagent confirms code matches spec?" -> "Implementer subagent fixes spec gaps" [label="no"]; 32 "Implementer subagent fixes spec gaps" -> "Dispatch spec reviewer subagent (./spec-reviewer-prompt.md)" [label="re-review"]; 33 "Spec reviewer subagent confirms code matches spec?" -> "Dispatch code quality reviewer subagent (./code-quality-reviewer-prompt.md)" [label="yes"]; 34 "Dispatch code quality reviewer subagent (./code-quality-reviewer-prompt.md)" -> "Code quality reviewer subagent approves?"; 35 "Code quality reviewer subagent approves?" -> "Implementer subagent fixes quality issues" [label="no"]; 36 "Implementer subagent fixes quality issues" -> "Dispatch code quality reviewer subagent (./code-quality-reviewer-prompt.md)" [label="re-review"]; 37 "Code quality reviewer subagent approves?" -> "Mark task complete in TodoWrite" [label="yes"]; 38 "Mark task complete in TodoWrite" -> "More tasks remain?"; 39 "More tasks remain?" -> "Dispatch implementer subagent (./implementer-prompt.md)" [label="yes"]; 40 "More tasks remain?" -> "Dispatch final code reviewer subagent for entire implementation" [label="no"]; 41 "Dispatch final code reviewer subagent for entire implementation" -> "Use superpowers:finishing-a-development-branch"; 42}

Model Selection

Use the least powerful model that can handle each role to conserve cost and increase speed.

Mechanical implementation tasks (isolated functions, clear specs, 1-2 files): use a fast, cheap model. Most implementation tasks are mechanical when the plan is well-specified.

Integration and judgment tasks (multi-file coordination, pattern matching, debugging): use a standard model.

Architecture, design, and review tasks: use the most capable available model.

Task complexity signals:

  • Touches 1-2 files with a complete spec → cheap model
  • Touches multiple files with integration concerns → standard model
  • Requires design judgment or broad codebase understanding → most capable model

Handling Implementer Status

Implementer subagents report one of four statuses. Handle each appropriately:

DONE: Proceed to spec compliance review.

DONE_WITH_CONCERNS: The implementer completed the work but flagged doubts. Read the concerns before proceeding. If the concerns are about correctness or scope, address them before review. If they're observations (e.g., "this file is getting large"), note them and proceed to review.

NEEDS_CONTEXT: The implementer needs information that wasn't provided. Provide the missing context and re-dispatch.

BLOCKED: The implementer cannot complete the task. Assess the blocker:

  1. If it's a context problem, provide more context and re-dispatch with the same model
  2. If the task requires more reasoning, re-dispatch with a more capable model
  3. If the task is too large, break it into smaller pieces
  4. If the plan itself is wrong, escalate to the human

Never ignore an escalation or force the same model to retry without changes. If the implementer said it's stuck, something needs to change.

Prompt Templates

  • ./implementer-prompt.md - Dispatch implementer subagent
  • ./spec-reviewer-prompt.md - Dispatch spec compliance reviewer subagent
  • ./code-quality-reviewer-prompt.md - Dispatch code quality reviewer subagent

Example Workflow

You: I'm using Subagent-Driven Development to execute this plan.

[Read plan file once: docs/superpowers/plans/feature-plan.md]
[Extract all 5 tasks with full text and context]
[Create TodoWrite with all tasks]

Task 1: Hook installation script

[Get Task 1 text and context (already extracted)]
[Dispatch implementation subagent with full task text + context]

Implementer: "Before I begin - should the hook be installed at user or system level?"

You: "User level (~/.config/superpowers/hooks/)"

Implementer: "Got it. Implementing now..."
[Later] Implementer:
  - Implemented install-hook command
  - Added tests, 5/5 passing
  - Self-review: Found I missed --force flag, added it
  - Committed

[Dispatch spec compliance reviewer]
Spec reviewer: ✅ Spec compliant - all requirements met, nothing extra

[Get git SHAs, dispatch code quality reviewer]
Code reviewer: Strengths: Good test coverage, clean. Issues: None. Approved.

[Mark Task 1 complete]

Task 2: Recovery modes

[Get Task 2 text and context (already extracted)]
[Dispatch implementation subagent with full task text + context]

Implementer: [No questions, proceeds]
Implementer:
  - Added verify/repair modes
  - 8/8 tests passing
  - Self-review: All good
  - Committed

[Dispatch spec compliance reviewer]
Spec reviewer: ❌ Issues:
  - Missing: Progress reporting (spec says "report every 100 items")
  - Extra: Added --json flag (not requested)

[Implementer fixes issues]
Implementer: Removed --json flag, added progress reporting

[Spec reviewer reviews again]
Spec reviewer: ✅ Spec compliant now

[Dispatch code quality reviewer]
Code reviewer: Strengths: Solid. Issues (Important): Magic number (100)

[Implementer fixes]
Implementer: Extracted PROGRESS_INTERVAL constant

[Code reviewer reviews again]
Code reviewer: ✅ Approved

[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)
  • Subagent can ask questions (before AND during work)

vs. Executing Plans:

  • Same session (no handoff)
  • Continuous progress (no waiting)
  • Review checkpoints automatic

Efficiency gains:

  • No file reading overhead (controller provides full text)
  • Controller curates exactly what context is needed
  • Subagent gets complete information upfront
  • Questions surfaced before work begins (not after)

Quality gates:

  • Self-review catches issues before handoff
  • Two-stage review: spec compliance, then code quality
  • Review loops ensure fixes actually work
  • Spec compliance prevents over/under-building
  • Code quality ensures implementation is well-built

Cost:

  • More subagent invocations (implementer + 2 reviewers per task)
  • Controller does more prep work (extracting all tasks upfront)
  • Review loops add iterations
  • But catches issues early (cheaper than debugging later)

Red Flags

Never:

  • Start implementation on main/master branch without explicit user consent
  • Skip reviews (spec compliance OR code quality)
  • Proceed with unfixed issues
  • Dispatch multiple implementation subagents in parallel (conflicts)
  • Make subagent read plan file (provide full text instead)
  • Skip scene-setting context (subagent needs to understand where task fits)
  • Ignore subagent questions (answer before letting them proceed)
  • Accept "close enough" on spec compliance (spec reviewer found issues = not done)
  • Skip review loops (reviewer found issues = implementer fixes = review again)
  • Let implementer self-review replace actual review (both are needed)
  • Start code quality review before spec compliance is ✅ (wrong order)
  • Move to next task while either review has open issues

If subagent asks questions:

  • Answer clearly and completely
  • Provide additional context if needed
  • Don't rush them into implementation

If reviewer finds issues:

  • Implementer (same subagent) fixes them
  • Reviewer reviews again
  • Repeat until approved
  • Don't skip the re-review

If subagent fails task:

  • Dispatch fix subagent with specific instructions
  • Don't try to fix manually (context pollution)

Integration

Required workflow skills:

  • superpowers:using-git-worktrees - REQUIRED: Set up isolated workspace before starting
  • superpowers:writing-plans - Creates the plan this skill executes
  • superpowers:requesting-code-review - Code review template for reviewer subagents
  • superpowers:finishing-a-development-branch - Complete development after all tasks

Subagents should use:

  • superpowers:test-driven-development - Subagents follow TDD for each task

Alternative workflow:

  • superpowers:executing-plans - Use for parallel session instead of same-session execution

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