Run multiple Ralph loops concurrently for independent tasks. Supports all 6 ralph-* teammates (coder, reviewer, tester, researcher, frontend, security). Manages parallel agent execution with proper isolation and result aggregation. Use when: (1) multiple independent fixes needed, (2) parallel reviews required, (3) batch processing tasks. Triggers: /parallel, 'parallel loops', 'concurrent execution', 'run in parallel', 'batch'.
Scanned 9/12/2026
Install to Claude Code
npx -y skills add aibot88/sec_skill_store --skill parallel --agent claude-codeInstalls into .claude/skills of the current project.
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---
# VERSION: 3.0.0
name: parallel
description: "Run multiple Ralph loops concurrently for independent tasks. Supports all 6 ralph-* teammates (coder, reviewer, tester, researcher, frontend, security). Manages parallel agent execution with proper isolation and result aggregation. Use when: (1) multiple independent fixes needed, (2) parallel reviews required, (3) batch processing tasks. Triggers: /parallel, 'parallel loops', 'concurrent execution', 'run in parallel', 'batch'."
context: fork
user-invocable: true
allowed-tools:
- LSP
- Task
- TaskOutput
- Read
- Edit
- Write
- Bash
---
# Parallel - Concurrent Execution (v3.0)
Run multiple Ralph loops concurrently for independent tasks.
## v2.88 Key Changes (MODEL-AGNOSTIC)
- **Model-agnostic**: Uses model configured in `~/.claude/settings.json` or CLI/env vars
- **No flags required**: All parallel tasks use the configured default model
- **Flexible**: Works with GLM-5, Claude, Minimax, or any configured model
- **Settings-driven**: Model selection via `ANTHROPIC_DEFAULT_*_MODEL` env vars
## Agent Teams Integration (v2.88)
**Optimal Scenario**: Integrated (Agent Teams + Custom Subagents)
Parallel execution combines Agent Teams coordination with ralph-coder specialization for optimal parallel file processing.
### Why Scenario C for Parallel Execution
- Multiple files require coordinated distribution
- Quality gates essential for result validation
- Specialized ralph-coder agents for implementation
- Shared task list tracks all parallel work
### Automatic Team Creation
When the parallel skill is invoked, automatically create a team:
```yaml
# Automatically create team on skill invocation
TeamCreate:
team_name: "parallel-execution-{timestamp}"
description: "Parallel execution of independent tasks"
```
### Spawning Parallel Agents
Create multiple ralph-coder instances for parallel tasks:
```yaml
# Spawn 3 parallel ralph-coder agents
Task:
subagent_type: "ralph-coder"
team_name: "parallel-execution-{timestamp}"
prompt: "Fix auth errors in src/auth/"
Task:
subagent_type: "ralph-coder"
team_name: "parallel-execution-{timestamp}"
prompt: "Fix API errors in src/api/"
Task:
subagent_type: "ralph-coder"
team_name: "parallel-execution-{timestamp}"
prompt: "Fix UI errors in src/ui/"
```
### Task Coordination Pattern
Use the shared task list for coordination:
```yaml
# Create master task list
TaskCreate:
subject: "Parallel fixes batch"
description: "Execute auth, API, and UI fixes in parallel"
# Create subtasks with dependencies
TaskCreate:
subject: "Fix auth errors"
activeForm: "Fixing auth errors"
TaskCreate:
subject: "Fix API errors"
activeForm: "Fixing API errors"
TaskCreate:
subject: "Fix UI errors"
activeForm: "Fixing UI errors"
```
### Quality Gates
Quality validation via Agent Teams hooks:
| Hook | Purpose | Behavior |
|------|---------|----------|
| `TeammateIdle` | Pre-idle validation | Keep working + feedback if issues found |
| `TaskCompleted` | Pre-completion validation | Block completion + feedback if issues found |
Quality standards enforced:
1. **CORRECTNESS**: Valid syntax, sound logic
2. **QUALITY**: No console.log, proper types, no TODOs
3. **SECURITY**: No hardcoded secrets, proper validation
4. **CONSISTENCY**: Follow project style guides
### Result Aggregation
After all parallel agents complete:
```yaml
# Aggregate results
TaskUpdate:
taskId: "<master-task>"
status: "completed"
# Report summary
- All subtasks completed
- Quality gates passed
- Changes ready for commit
```
## Quick Start
```bash
/parallel "fix auth errors" "fix api errors" "fix ui errors"
ralph parallel task1 task2 task3
```
## When to Use
### Good for Parallel
- Independent file changes
- Multiple module fixes
- Batch reviews
- Different analysis types
### Must Be Sequential
- Dependent changes
- Same file modifications
- Order-dependent operations
- Shared state changes
## Workflow
### 1. Create Team and Spawn Agents
```yaml
# Auto-create team for coordination
TeamCreate:
team_name: "parallel-{task-name}"
description: "Parallel execution of {task-name}"
# Launch multiple ralph-coder background agents
Task:
subagent_type: "ralph-coder"
team_name: "parallel-{task-name}"
prompt: "Execute task 1"
Task:
subagent_type: "ralph-coder"
team_name: "parallel-{task-name}"
prompt: "Execute task 2"
Task:
subagent_type: "ralph-coder"
team_name: "parallel-{task-name}"
prompt: "Execute task 3"
```
### 2. Monitor Progress
```yaml
# Check task list for all subtask status
TaskList:
# Returns all tasks with status, owner, blockedBy
# Monitor specific subtask
TaskGet:
taskId: "<subtask-id>"
```
### 3. Aggregate Results
```yaml
# Mark master task as completed
TaskUpdate:
taskId: "<master-task>"
status: "completed"
# Report summary
- All subtasks completed
- Quality gates passed
- Changes ready for commit
```
## Parallel Patterns
### Review Pattern
```bash
# Parallel reviews with different focus
/parallel "security review src/" "performance review src/" "quality review src/"
```
### Fix Pattern
```bash
# Parallel fixes for different modules
/parallel "fix auth errors" "fix api errors" "fix db errors"
```
### Analysis Pattern
```bash
# Parallel analysis tasks
/parallel "analyze complexity" "analyze coverage" "analyze dependencies"
```
## Isolation
Each parallel task runs with:
- Separate context (`context: fork`)
- Independent iteration counter
- Own quality gates
- Isolated file access
## Result Aggregation
### All Succeed
- Aggregate changes
- Run global gates
- VERIFIED_DONE
### Partial Success
- Report failures
- Keep successful changes
- Retry failed tasks
### All Fail
- Report all errors
- Analyze patterns
- Sequential retry
## Integration
- Used for independent sub-tasks
- Each parallel task follows Ralph Loop
- Results feed back to orchestrator
## Anti-Patterns
- Never run parallel on same files
- Never exceed 5 concurrent agents
- Never ignore partial failures
- Never skip aggregation step
## Action Reporting (v2.93.0)
**Esta skill genera reportes automáticos completos** para trazabilidad:
### Reporte Automático
Cuando esta skill completa, se genera automáticamente:
1. **En la conversación de Claude**: Resultados visibles
2. **En el repositorio**: `docs/actions/parallel/{timestamp}.md`
3. **Metadatos JSON**: `.claude/metadata/actions/parallel/{timestamp}.json`
### Contenido del Reporte
Cada reporte incluye:
- ✅ **Summary**: Descripción de la tarea ejecutada
- ✅ **Execution Details**: Duración, iteraciones, archivos modificados
- ✅ **Results**: Errores encontrados, recomendaciones
- ✅ **Next Steps**: Próximas acciones sugeridas
### Ver Reportes Anteriores
```bash
# Listar todos los reportes de esta skill
ls -lt docs/actions/parallel/
# Ver el reporte más reciente
cat $(ls -t docs/actions/parallel/*.md | head -1)
# Buscar reportes fallidos
grep -l "Status: FAILED" docs/actions/parallel/*.md
```
### Generación Manual (Opcional)
```bash
source .claude/lib/action-report-lib.sh
start_action_report "parallel" "Task description"
# ... ejecución ...
complete_action_report "success" "Summary" "Recommendations"
```
### Referencias del Sistema
- [Action Reports System](docs/actions/README.md) - Documentación completa
- [action-report-lib.sh](.claude/lib/action-report-lib.sh) - Librería helper
- [action-report-generator.sh](.claude/lib/action-report-generator.sh) - Generador
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