Execute plans via delegate_task subagents (2-stage review).
Collected from public GitHub. Every version is saved exactly as it was and never changes. Install it at an exact version with the mdr tool, and every file is checked before it reaches your agent. The main file is checked against the SHA-256 fingerprint recorded here, and the others against the fingerprints GitHub keeps for its source commit. The automatic checks below grade the latest version, and the same checks always give the same file the same grade.
What the file says
# Subagent-Driven Development
## Overview
Execute implementation plans by dispatching fresh subagents per task with systematic two-stage review.
**Core principle:** Fresh subagent per task + two-stage review (spec then quality) = high quality, fast iteration.
## When to Use
Use this skill when:
- You have an implementation plan (from writing-plans skill or user requirements)
- Tasks are mostly independent
- Quality and spec compliance are important
- You want automated review between tasks
**vs. manual execution:**
- Fresh context per task (no confusion from accumulated state)
- Automated review process catches issues early
- Consistent quality checks across all tasks
- Subagents can ask questions before starting work
## The Process
### 1. Read and Parse Plan
Read the plan file. Extract ALL tasks with their full text and context upfront. Create a todo list:
```python
# Read the plan
read_file("docs/plans/feature-plan.md")
# Create todo list with all tasks
todo([
{"id": "task-1", "content": "Create User model with email field", "status": "pending"},
{"id": "task-2", "content": "Add password hashing utility", "status": "pending"},
…
The line at the top of this page pins the label v1.1.0, which is what most people want. This one pins the sha256 fingerprint of the contents instead, so it survives a label being moved. Either way the exact version is written to mdr.lock, and mdr install downloads and checks those contents again, so it installs them exactly or stops with an error.
GET https://markdownregistry.com/api/v1/artifacts/art_rfccmi3lqqhafm6d
GET https://markdownregistry.com/api/v1/resolve?ref=mateaix/mateclaw/subagent-driven-development
GET https://markdownregistry.com/api/v1/blob/dacaccb7cbb1859437feb5bed7c4c89960020a22bdee2c08ad2bcc8040e77114
Your AI assistant does the legwork. You hear about the deals worth your word. Hand yours the standing instructions at modelranch.com and it joins the network that reads files like this one.
a5c-ai/babysitter · library/methodologies/superpowers/skills/subagent-driven-development/SKILL.md · Use when executing implementation plans with independent tasks in the current session. Dispatches fresh subagent per…
ganyuanran/aegis · skills/subagent-driven-development/SKILL.md · Use when executing a written implementation plan with independent tasks in the current session where delegation beats…
coco-research/coco · skills/subagent-driven-development/SKILL.md · Use when executing implementation plans with independent tasks in the current session
xu123-bob/baize · agent/skills/superpowers/5.1.0/skills/subagent-driven-development/SKILL.md · Use when executing implementation plans with independent tasks in the current session
jamditis/claude-skills-journalism · superjawn/skills/subagent-driven-development/SKILL.md · Use when executing implementation plans with independent tasks in the current session
ibrahim-3d/orchestrator-supaconductor · skills/subagent-driven-development/SKILL.md · Use when executing implementation plans with independent tasks in the current session
