Agent skill

subagent-driven-development

Use when executing implementation plans with independent tasks in the current session

foryourhealth111-pixelgithub.com/foryourhealth111-pixelGitHub ↗
claude-codecodexApache-2.0
Install
npx skills add foryourhealth111-pixel/Vibe-Skills --skill subagent-driven-development --agent claude-code

Same command for any agent — swap --agent for codex, cursor, copilot.

Facts
Files in the skill folder: 4
SKILL.md size: 10 KB
Bundled scripts: none
Path: bundled/skills/subagent-driven-development/SKILL.md
Open the folder on GitHub →
Where it comes from
Stars: 2,593
Language: Python
Read our review of the source →

Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.

From the SKILL.md

# 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. **Core principle:** Fresh subagent per task + two-stage review (spec then quality) = high quality, fast iteration ## When to Use ```dot digraph when_to_use { "Have implementation plan?" [shape=diamond]; "Tasks mostly independen

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About this skill
What does the subagent-driven-development skill do?

Use when executing implementation plans with independent tasks in the current session

How do I install it?

Run `npx skills add foryourhealth111-pixel/Vibe-Skills --skill subagent-driven-development --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.

Where does this skill come from?

From foryourhealth111-pixel/Vibe-Skills, a repository with 2,593 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.

Is a popular skill a good skill?

Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.

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