execute
Main entry point for hierarchical task execution. Orchestrates layer-by-layer implementation of PRD tasks with parallel worktree execution.
About this skill
This skill acts as the main orchestrator for implementing tasks derived from a Product Requirements Document (PRD). It manages a sophisticated 4-level hierarchy, breaking down the overall execution into layers, batches, individual tasks, and subsequent verification and merging steps. This structured approach ensures a systematic and thorough implementation process. The skill supports parallel execution of tasks using isolated Git worktrees, allowing multiple development efforts to proceed concurrently without direct conflicts. After task completion, it facilitates sequential merges, ensuring code integrity. Users can specify the path to their tasks, define the target project, configure the worktree directory, and set the maximum number of parallel tasks. It also provides options for executing specific layers or tasks, resuming from a previous state, resetting the execution, or performing a dry run to visualize the plan. By leveraging this orchestrator, development teams can streamline the implementation of complex features or products outlined in PRDs. It helps maintain organization, manage dependencies, and accelerate development cycles by automating the coordination of numerous sub-tasks, from coding to verification and integration.
Best use case
This skill is primarily for software development teams and individual developers working on complex projects defined by Product Requirements Documents (PRDs). It's ideal for managing the structured implementation of large features, refactoring efforts, or new product development where tasks can be broken down into hierarchical layers and executed in parallel. Teams benefit from its ability to enforce a systematic workflow, reduce manual orchestration overhead, and ensure consistent verification and merging practices.
Main entry point for hierarchical task execution. Orchestrates layer-by-layer implementation of PRD tasks with parallel worktree execution.
A completed PRD implementation, structured by layers, with all defined tasks executed, verified, and integrated into the target project via sequential merges.
Practical example
Example input
execute --tasks-path ./my_feature_prd/tasks --project-path ./my-main-repo --max-parallel 5 --layer "frontend_ui" --resume
Example output
Execution plan generated for PRD 'my_feature_prd'. Starting layer 'frontend_ui' with 3 parallel tasks. Worktrees created and tasks are being executed in parallel. Monitoring progress and preparing for verification and merge steps. To resume after interruption, use --resume.
When to use this skill
- Implementing complex features or PRDs defined with multiple layers and tasks.
- When a structured, verifiable, and parallel execution process is desired for code changes.
- Automating the coordination of multiple sub-tasks and their subsequent merging.
- Managing development across isolated worktrees to prevent conflicts during parallel work.
When not to use this skill
- For simple, single-file edits or quick fixes that don't require elaborate orchestration.
- When the project structure doesn't involve PRDs, layers, or a hierarchical task breakdown.
- In highly experimental or exploratory coding where a strict plan isn't yet established.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/execute/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How execute Compares
| Feature / Agent | execute | Standard Approach |
|---|---|---|
| Platform Support | Claude | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | easy | N/A |
Frequently Asked Questions
What does this skill do?
Main entry point for hierarchical task execution. Orchestrates layer-by-layer implementation of PRD tasks with parallel worktree execution.
Which AI agents support this skill?
This skill is designed for Claude.
How difficult is it to install?
The installation complexity is rated as easy. You can find the installation instructions above.
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
# Task Execution Orchestrator
You are the main orchestrator for executing PRD implementation tasks. You coordinate layer-by-layer execution through a 4-level hierarchy:
```
/execute (you)
└─► /execute-layer (per layer)
└─► /execute-batch (per batch)
├─► /execute-task (per task, parallel)
│ └─► /execute-verify (verification)
└─► /execute-merge (sequential merges)
```
## Arguments
See `.claude/skills/execute/references/options.md` for complete documentation.
### Required
- `<tasks-path>`: Path to tasks directory (contains manifest.json, layer_plan.json)
### Common Options
```
--project-path <path> Target project (optional if in manifest)
--worktree-dir <path> Worktree directory (default: {project}/../.worktrees)
--max-parallel <N> Max concurrent tasks (default: 3)
--layer <name> Execute specific layer only
--task <id> Execute specific task only
--resume Resume from existing state
--reset Delete state and start fresh
--dry-run Show plan without executing
```
## Execution Flow
### Step 1: Parse Arguments
Extract all arguments from the prompt:
```python
tasks_path = required
project_path = optional # from args or manifest
worktree_dir = optional # default derived from project_path
max_parallel = 3
layer_filter = None
task_filter = None
resume = False
reset = False
dry_run = False
```
### Step 2: Load Manifest
Read `manifest.json`:
```bash
cat {tasks_path}/manifest.json
```
Extract:
- `prd.slug`: PRD identifier
- `prd.project_path`: Default project path (if not specified in args)
- `layers`: Layer definitions
- `summary.total_tasks`: Total task count
**Project path resolution:**
1. Use `--project-path` if provided
2. Fall back to `manifest.prd.project_path` if exists
3. Error if neither available
### Step 3: Validate Inputs
Check:
- Tasks path exists
- `manifest.json` exists
- `layer_plan.json` exists
- Project path exists (or will be created for greenfield)
- Git repository initialized in project
```bash
test -d {tasks_path}
test -f {tasks_path}/manifest.json
test -f {tasks_path}/layer_plan.json
test -d {project_path}
test -d {project_path}/.git
```
### Step 4: Handle State
**If `--reset`:**
```bash
rm -f {tasks_path}/execute-state.json
```
**If `--resume`:**
```python
if state_file_exists:
state = load_state()
validate_state_schema()
else:
error("No state file to resume from")
```
**If new execution:**
```python
if state_file_exists:
ask_user("State file exists. Resume or start fresh?")
else:
state = init_state()
```
### Step 5: Dry Run (if requested)
If `--dry-run`:
```
Execution Plan: {prd_slug}
Project: {project_path}
Worktrees: {worktree_dir}
Layer 0-setup (4 tasks):
Batch 1: L0-001 → L0-002 → L0-003 → L0-004 (sequential)
Layer 1-foundation (6 tasks):
Batch 1: L1-001, L1-002, L1-006 (parallel, 3 tasks)
Batch 2: L1-003 (depends on L1-002)
Batch 3: L1-004, L1-005 (depends on L1-003)
Layer 2-backend (9 tasks):
Batch 1: L2-001, L2-002, L2-003 (parallel)
...
Total: 48 tasks
Estimated batches: 15
Max parallelism: 3
```
Exit after dry run output.
### Step 6: Execute Layers
For each layer in order:
```python
layers = ["0-setup", "1-foundation", "2-backend", "3-frontend", "4-integration"]
for layer in layers:
# Skip if filter doesn't match
if layer_filter and layer != layer_filter:
continue
# Skip if already completed
if state["layers"].get(layer, {}).get("status") == "completed":
print(f"[EXEC] Skipping {layer} (already completed)")
continue
# Execute layer
print(f"[EXEC] Starting {layer}")
result = invoke_layer(layer)
# Check for stop condition
if result["should_stop"]:
print(f"[EXEC] STOPPED: {result['stop_reason']}")
update_state(status="stopped")
report_final_status()
return
print(f"[EXEC] {layer} complete ({result['tasks_completed']}/{result['tasks_total']})")
```
### Step 7: Invoke Layer Agent
For each layer, call `/execute-layer`:
```
/execute-layer --tasks-path {tasks_path} --layer {layer} --project-path {project_path} --worktree-dir {worktree_dir} --max-parallel {max_parallel}
```
Wait for layer completion and parse `LAYER_RESULT`.
### Step 8: Handle Stop Condition
If any layer returns `should_stop: true`:
- A task was abandoned (5 failed attempts)
- Update state to `stopped`
- Output clear message with:
- Which task failed
- Path to preserved worktree
- How to resume
```
STOPPED: Task L2-006 abandoned after 5 attempts
Completed: 15/48 tasks
Abandoned: L2-006
Blocked: 32 tasks (dependencies not met)
Worktree preserved: {worktree_dir}/L2-006
Review errors and fix issues, then run:
/execute {tasks_path} --resume
```
### Step 9: Report Final Status
On completion:
```
Execution Complete: {prd_slug}
Layers:
0-setup: 4/4 completed
1-foundation: 6/6 completed
2-backend: 9/9 completed
3-frontend: 13/13 completed
4-integration: 12/12 completed
Total: 44/44 tasks completed
Duration: 2h 15m
Retries: 3 (all succeeded)
```
### Step 10: Finalize Context (CRD Projects)
If PROJECT.md exists in the project root, update it with implemented features.
**Check for PROJECT.md:**
```bash
test -f {project_path}/PROJECT.md
```
**If exists, update context:**
1. Read all completed task XML files
2. Extract `<exports>` sections from each task
3. Map exports to PROJECT.md sections:
- `<api endpoint>` → `<api-registry>`
- `<interface type="react-component">` → `<features>`
- `<interface type="sqlalchemy-model">` → `<schema-registry>`
4. Update PROJECT.md:
- Add new features to `<features>` section
- Add new endpoints to `<api-registry>` section
- Add new models to `<schema-registry>` section
- Update `<last-context-hash>` to current HEAD
- Update `<last-updated>` timestamp
5. Commit the context update:
```bash
git -C {project_path} add PROJECT.md
git -C {project_path} commit -m "docs: Update PROJECT.md with features from {prd_slug}"
```
6. Update state with context finalization:
```json
{
"context_update": {
"status": "completed",
"project_md_path": "{project_path}/PROJECT.md",
"features_added": ["feature-1", "feature-2"],
"endpoints_added": ["/api/new-endpoint"],
"models_added": ["NewModel"]
}
}
```
**If no PROJECT.md:**
Skip context finalization silently (not a CRD-based project).
### Step 11: Complete
Update state:
```json
{
"status": "completed",
"completed_at": "{now}"
}
```
Output final summary including context update if performed:
```
Execution Complete: {prd_slug}
Total: 44/44 tasks completed
Duration: 2h 15m
Context Update:
- PROJECT.md updated at {project_path}/PROJECT.md
- Features added: 3
- Endpoints added: 5
- Models added: 2
- New context hash: {hash}
```
## State Initialization
```python
def init_state(prd_slug, project_path, worktree_dir, tasks_path, options):
return {
"schema_version": "2.0",
"prd_slug": prd_slug,
"project_path": project_path,
"worktree_dir": worktree_dir,
"tasks_path": tasks_path,
"started_at": now(),
"updated_at": now(),
"completed_at": None,
"status": "in_progress",
"current_layer": None,
"current_batch": None,
"options": options,
"layers": {},
"tasks": {},
"worktrees": {},
"merge_queue": [],
"completed": [],
"failed": [],
"abandoned": [],
"metrics": {
"tasks_total": total_tasks,
"tasks_completed": 0,
"tasks_failed": 0,
"tasks_abandoned": 0,
"tasks_remaining": total_tasks,
"total_attempts": 0,
"total_retries": 0,
"elapsed_seconds": 0
}
}
```
## Resume Behavior
On resume:
1. Load existing state
2. Find current layer (from `current_layer` or first incomplete)
3. Re-evaluate ready queue within layer
4. Continue execution from ready tasks
5. Retry `failed` tasks (if attempts < 5)
6. Skip `completed` and `abandoned` tasks
## Error Handling
### Missing Manifest
```
Error: manifest.json not found at {tasks_path}/manifest.json
Run /breakdown first to generate tasks.
```
### Missing Project
If project path doesn't exist and not greenfield:
```
Error: Project path does not exist: {project_path}
For greenfield projects, Layer 0 will create it.
```
### Git Not Initialized
```
Error: Git repository not initialized at {project_path}
Run: cd {project_path} && git init
```
### Resume Without State
```
Error: No state file found at {tasks_path}/execute-state.json
Cannot resume. Start fresh without --resume flag.
```
## Output Format
### Minimal Mode (default)
```
[EXEC] Starting layer 0-setup (4 tasks)
[EXEC] Layer 0-setup complete (4/4)
[EXEC] Starting layer 1-foundation (6 tasks)
[EXEC] Layer 1-foundation complete (6/6)
...
[EXEC] All layers complete (44/44 tasks)
```
### Verbose Mode
```
[EXEC] Execution Plan:
PRD: voice-prd-generator
Project: /home/user/projects/voice-prd
Worktrees: /home/user/projects/.worktrees
Max parallel: 3
[EXEC] Starting layer 0-setup (4 tasks)
[LAYER 0-setup] Batch 1/1: L0-001, L0-002, L0-003, L0-004
[L0-001] Creating worktree...
[L0-001] Implementing...
[L0-001] Verified (3/3 steps)
...
[LAYER 0-setup] Merged: L0-001, L0-002, L0-003, L0-004
[EXEC] Layer 0-setup complete (4/4)
...
```
## Context Isolation
This skill runs in `context: fork`:
- Fresh context for each execution
- No context bleed from previous runs
- Spawns child skills which also fork
- State file is the persistence mechanism
## Critical Rules
1. **Never skip layers**: Execute in order (0→1→2→3→4)
2. **Respect dependencies**: Only execute tasks with satisfied deps
3. **Stop on abandon**: If task hits 5 failures, STOP immediately
4. **Preserve worktrees**: Never delete worktrees on failure
5. **Sequential merges**: Merge one task at a time to avoid conflicts
6. **Update state**: Write state after every significant eventRelated Skills
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