
Subagent Driven Development
- 51 installs
- 7 repo stars
- Updated January 15, 2026
- eyadsibai/ltk
Helps with ai & agent building tasks.
About
subagent-driven-development is a Claude Code skill for ai & agent building. It helps solo builders move faster with AI-assisted development.
- subagent-driven-development
- AI & Agent Building
- AI-coding skill
Subagent Driven Development by the numbers
- 51 all-time installs (skills.sh)
- Ranked #7,219 of 16,546 AI & Agent Building skills by installs in the Skillselion catalog
- Data as of Jul 30, 2026 (Skillselion catalog sync)
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| Installs | 51 |
|---|---|
| repo stars | ★ 7 |
| Last updated | January 15, 2026 |
| Repository | eyadsibai/ltk ↗ |
What it does
Helps with ai & agent building tasks.
Files
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
Use when:
- Have implementation plan
- Tasks are mostly independent
- Want to stay in current session
- Want fast iteration with review checkpoints
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
Setup
1. Read plan, extract all tasks with full text and context 2. Create TodoWrite with all tasks
Per Task
1. Dispatch implementer subagent with full task text + context 2. If subagent asks questions - Answer, provide context 3. Implementer implements, tests, commits, self-reviews 4. Dispatch spec reviewer subagent - Verify code matches spec 5. If spec issues - Implementer fixes, reviewer re-reviews 6. Dispatch code quality reviewer subagent - Review for quality 7. If quality issues - Implementer fixes, reviewer re-reviews 8. Mark task complete in TodoWrite
After All Tasks
1. Dispatch final code reviewer for entire implementation 2. Use ltk:finishing-a-development-branch to complete
Two-Stage Review
Stage 1: Spec Compliance
- Does implementation match spec EXACTLY?
- Nothing missing?
- Nothing extra (over-building)?
Stage 2: Code Quality (only after spec passes)
- Clean code?
- Good test coverage?
- Maintainable?
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)
Quality gates:
- Self-review catches issues before handoff
- Two-stage review: spec compliance, then code quality
- Review loops ensure fixes actually work
Red Flags
Never:
- 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
- Ignore subagent questions
- Accept "close enough" on spec compliance
- Skip review loops
- Start code quality review before spec compliance passes
- 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
Integration
Required workflow skills:
- ltk:writing-plans - Creates the plan this skill executes
- ltk:requesting-code-review - Code review template for reviewer subagents
- ltk:finishing-a-development-branch - Complete development after all tasks
Subagents should use:
- ltk:test-driven-development - Subagents follow TDD for each task
Alternative workflow:
- ltk:executing-plans - Use for parallel session instead of same-session execution