subagent-driven-development
Fresh-subagent-per-task execution with two-stage review gates.
Best use case
subagent-driven-development is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Fresh-subagent-per-task execution with two-stage review gates.
Teams using subagent-driven-development should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/subagent-driven-development/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How subagent-driven-development Compares
| Feature / Agent | subagent-driven-development | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Fresh-subagent-per-task execution with two-stage review gates.
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
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SKILL.md Source
# Subagent-Driven Development Skill ## Instructions ### Phase 1: SETUP **Goal**: Extract all tasks and establish project context before any implementation begins. **Step 1: Read plan and extract tasks** Read the plan file ONCE. Extract every task with full text: ```markdown ## Tasks Extracted from Plan **Task 1: [Title]** Full text: [Complete task description from plan] Files: [List of files to create/modify] Verification: [How to verify this task] **Task 2: [Title]** ... ``` **Why**: Providing complete task text inline prevents subagents from burning tokens reading files and pollutes their context if they need to refer back to the plan. This isolation is critical for clean review cycles. **Step 2: Create TodoWrite** Create TodoWrite with ALL tasks: ``` 1. [pending] Task 1: [Title] 2. [pending] Task 2: [Title] 3. [pending] Task 3: [Title] ``` **Why**: TodoWrite gives the operator visibility and prevents task slip. **Step 3: Gather scene-setting context** Before dispatching any implementer, capture: - Current branch status (`git status`) - Capture BASE_SHA: `git rev-parse HEAD` -- required for final integration review - Relevant existing code patterns (naming conventions, error handling style) - Project conventions from CLAUDE.md - Dependencies and setup requirements This context gets passed to EVERY subagent to prevent repeated discovery and question loops. **Why**: Early context capture answers 80% of subagent questions before they ask, unblocks implementation immediately, and must be collected once (not rediscovered per task). BASE_SHA must be captured BEFORE the first implementer runs because subsequent edits will move HEAD forward. **Gate**: All tasks extracted with full text. BASE_SHA captured. Scene-setting context gathered. Proceed only when gate passes. ### Phase 2: EXECUTE (Per-Task Loop) **Goal**: Implement each task with a fresh subagent, then verify through two-stage review. **Step 1: Mark task in_progress** Update TodoWrite status for the current task. **Step 2: Dispatch implementer subagent** Use the Task tool with the prompt template from `./implementer-prompt.md`. Include: - Full task text (Replace with "see plan" -- subagents must have complete context) - Scene-setting context - Clear deliverables - Permission to ask questions **Implementation constraints** (enforced inline): - Implementer must understand task fully before coding begins. If they ask questions: answer clearly and completely, provide additional context, re-dispatch with answers. Give them time to fully understand the task. - Tasks must run sequentially. dispatch implementers sequentially because overlapping file edits cause conflicts that are expensive to resolve. - Implementer MUST follow these steps in order: 1. Understand the task fully 2. Ask questions if unclear (BEFORE implementing) 3. Implement following TDD where appropriate 4. Run tests 5. Self-review code 6. Commit changes **Why sequential execution**: Each task's output becomes the next task's input. Parallel execution breaks file locking semantics and requires complex merge handling. Sequential is simpler, safer, and conflicts are rare when each subagent gets full context. **Step 3: Dispatch ADR compliance reviewer subagent** Use the prompt template from `./adr-reviewer-prompt.md`. The ADR compliance reviewer checks: - Does implementation match the ADR EXACTLY? - Is anything MISSING from requirements? - Is anything EXTRA that was not requested? **Two-stage review constraint** (enforced inline): run ADR compliance review first, then code quality review. ADR compliance gates code quality because code that doesn't match requirements is wrong, regardless of how well-written. Reviewing code quality on functionally wrong code wastes the quality reviewer's effort. If ADR compliance reviewer finds issues: dispatch new implementer subagent with fix instructions. ADR compliance reviewer reviews again. Repeat until ADR compliance passes. **Max retries: 3** -- After 3 failed ADR compliance reviews, STOP and escalate: > "ADR compliance failing after 3 attempts. Issues: [list]. Need human decision." **Why escalation after 3 retries**: 3 retries = ~15-20 min of subagent time. If unresolved by then, the problem is structural (ADR is ambiguous, requirements conflict, or subagent fundamentally misunderstood something). Continuing loops wastes tokens. Human needs to decide: clarify ADR, adjust requirements, or accept the implementation as-is. **Step 4: Dispatch code quality reviewer subagent** Use the prompt template from `./code-quality-reviewer-prompt.md`. The code quality reviewer checks: - Code is well-structured - Tests are meaningful - Error handling is appropriate - No obvious bugs **Quality review sequencing** (enforced inline): Only dispatch quality reviewer AFTER ADR compliance passes. Code quality review focuses on how well requirements are met, not whether wrong things were built. If quality reviewer finds issues: implementer fixes Critical and Important issues (Minor issues are optional). Quality reviewer reviews again. **Max retries: 3** -- After 3 failed quality reviews, STOP and escalate: > "Quality review failing after 3 attempts. Issues: [list]. Need human decision." **Why different retry limits for both stages**: Both stages can get stuck. Both deserve a fair number of attempts (3 each = up to 60 min total per task). Both hitting the limit means something is wrong with the process or the task definition itself. **Step 5: Mark task complete** Only when BOTH reviews pass: ``` Task [N]: [Title] -- COMPLETE ADR compliance: PASS Code quality: PASS ``` Return to Step 1 for the next task. **Gate**: Both ADR compliance and code quality reviews pass. Task marked complete in TodoWrite. Proceed only when gate passes. ### Phase 3: FINALIZE **Goal**: Verify the full implementation works together and complete the workflow. **Step 1: Final integration review** Dispatch a reviewer subagent for the entire changeset (diff from BASE_SHA to HEAD): - All tests pass together - No integration issues between tasks - No conflicting patterns or redundant code **Why final integration review after all tasks**: Per-task reviews ensure each task is correct in isolation. Final integration review catches cross-task problems: Task 1 and Task 3 both define the same utility, tests pass individually but conflict when run together, or Task 2 introduced a breaking change that Task 4 didn't account for. This catch-all review is why BASE_SHA was captured upfront. **Step 2: Complete development workflow** Use the appropriate completion path: - `/pr-workflow` to create PR - Manual merge - Keep branch for further work **Gate**: Final review passes. All tests pass. Integration verified. Proceed only when gate passes. --- ## Error Handling ### Error: "Subagent Asks Questions Mid-Implementation" Cause: Insufficient context in the dispatch prompt Solution: 1. Answer all questions clearly and completely 2. Add the missing context to the scene-setting for future tasks 3. Re-dispatch implementer with answers included **Prevention**: The answer-questions-first constraint prevents this by design. If a subagent still asks questions after full context, they're asking for clarification on the ADR itself, which is valuable signal that requirements are ambiguous. ### Error: "Review Loop Exceeds 3 Retries" Cause: ADR ambiguity, fundamental misunderstanding, or unreasonable review criteria Solution: 1. STOP the loop immediately 2. Summarize all issues and attempted fixes for the user 3. Ask user to clarify ADR or adjust requirements 4. Resume only after user provides direction **Why hard limit**: Review loops that fail to converge are expensive and signal a deeper problem. Continuing them burns tokens without progress. Human judgment is needed to decide whether to clarify, change, or accept. ### Error: "Subagent File Conflicts" Cause: Multiple subagents modifying overlapping files (usually from parallel dispatch) Solution: 1. Resolve conflicts manually 2. Re-run the affected review stage 3. Enforce sequential dispatch going forward -- run implementers sequentially **Why this happens**: The sequential constraint exists to prevent this. If it occurs anyway, it means the constraint was violated. Reassert it. --- ## References ### Prompt Templates - `implementer-prompt.md`: Dispatch template for implementation subagents - `adr-reviewer-prompt.md`: Dispatch template for ADR compliance review - `code-quality-reviewer-prompt.md`: Dispatch template for code quality review
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