Hybrid Ralph + Planning-with-Files

Hybrid Ralph + Planning-with-Files

A hybrid architecture combining the best of three approaches:

Auto-Recovery Protocol (CRITICAL)

At the START of any interaction, perform this check to recover context after compression/​truncation:

1. Check if .hybrid-execution-context.md exists in the current directory

2. If YES:

   • Read the file content using Read tool
   • Display: "Detected ongoing hybrid task execution"
   • Show current batch and pending stories from the file
   • Resume story execution based on the state
   • If unsure of state, suggest: /​plan-cascade:hybrid-resume --auto

3. If NO but prd.json exists:

   • Run: python3 "${CLAUDE_PLUGIN_ROOT}/​skills/​hybrid-ralph/​scripts/​hybrid-context-reminder.py" both
   • This will generate the context file and display current state

This ensures context recovery even after:

• Context compression (AI summarizes old messages)

• Context truncation (old messages deleted)

• New conversation session

• Claude Code restart

• Ralph: Structured PRD format (prd.json), progress tracking patterns, small task philosophy

• Planning-with-Files: 3-file planning pattern (task_plan.md, findings.md, progress.txt), Git Worktree support

• Claude Code Native: Task tool with subagents for parallel story execution

Quick Start

Automatic PRD Generation

Generate a PRD from your task description:

/​hybrid:auto Implement a user authentication system with login, registration, and password reset

This will:

1. Launch a Planning Agent to analyze your task
2. Generate a PRD with user stories
3. Show the PRD for review
4. Wait for your approval

Manual PRD Loading

Load an existing PRD file:

/​hybrid:manual path/​to/​prd.json

Approval and Execution

After reviewing the PRD:

/​approve

This begins parallel execution of stories according to the dependency graph.

Architecture

File Structure

project-root/
├── prd.json                 # Product Requirements Document
├── findings.md              # Research findings (tagged by story)
├── progress.txt             # Progress tracking
├── .current-story           # Currently executing story
├── .locks/                  # File locks for concurrent access
└── .agent-outputs/          # Individual agent logs

The PRD Format

The prd.json file contains:

• metadata: Creation date, version, description
• goal: One-sentence project goal
• objectives: List of specific objectives
• stories: Array of user stories with:
  • id: Unique story identifier (story-001, story-002, etc.)
  • title: Short story title
  • description: Detailed story description
  • priority: high, medium, or low
  • dependencies: Array of story IDs this story depends on
  • status: pending, in_progress, or complete
  • acceptance_criteria: List of completion criteria
  • context_estimate: small, medium, large, or xlarge
  • tags: Array of tags for categorization

Parallel Execution Model

Stories are organized into execution batches:

1. Batch 1: Stories with no dependencies (run in parallel)
2. Batch 2+: Stories whose dependencies are complete (run in parallel)

Batch 1 (Parallel):
  - story-001: Design database schema
  - story-002: Design API endpoints

Batch 2 (After story-001 complete):
  - story-003: Implement database schema

Batch 3 (After story-002, story-003 complete):
  - story-004: Implement API endpoints

Context Filtering

Each agent receives only relevant context:

• Their story description and acceptance criteria
• Summaries of completed dependencies
• Findings tagged with their story ID

This keeps context windows focused and efficient.

Core Python Modules

context_filter.py

Filters and extracts relevant context for specific stories.

# Get story details
python3 context_filter.py get-story story-001

# Get context for a story
python3 context_filter.py get-context story-001

# Get execution batch
python3 context_filter.py get-batch 1

# Show full execution plan
python3 context_filter.py plan-batches

state_manager.py

Thread-safe file operations with platform-specific locking.

# Read PRD
python3 state_manager.py read-prd

# Mark story complete
python3 state_manager.py mark-complete story-001

# Get all story statuses
python3 state_manager.py get-statuses

prd_generator.py

Generates PRD from task descriptions and manages story dependencies.

# Validate PRD
python3 prd_generator.py validate

# Show execution batches
python3 prd_generator.py batches

# Create sample PRD
python3 prd_generator.py sample

orchestrator.py

Manages parallel execution of stories.

# Show execution plan
python3 orchestrator.py plan

# Show execution status
python3 orchestrator.py status

# Execute a batch
python3 orchestrator.py execute-batch 1

Commands Reference

/​hybrid:auto

Generate PRD from task description.

/​hybrid:auto <task description>

/​hybrid:manual

Load existing PRD file.

/​hybrid:manual [path/​to/​prd.json]

/​hybrid:worktree

Create a new Git worktree with isolated environment and initialize Hybrid Ralph mode. This is the primary command for multi-task parallel development.

/​hybrid:worktree <task-name> <target-branch> <task-description-or-prd-path>

Arguments:

• task-name: Name for the worktree (e.g., "feature-auth", "fix-api-bug")
• target-branch: Branch to merge into (default: auto-detect main/​master)
• task-description-or-prd-path: Either a task description to generate PRD, or path to existing PRD file

Execution Steps:

When /​hybrid:worktree is invoked, execute the following:

1. Parse Parameters: Extract task-name, target-branch, and PRD argument

2. Verify Git Repository: Ensure we're in a git repository

3. Detect Default Branch: Auto-detect main/​master branch

4. Set Variables:

TASK_BRANCH="$TASK_NAME"
ORIGINAL_BRANCH=$(git branch --show-current)
ROOT_DIR=$(pwd)
WORKTREE_DIR="$ROOT_DIR/​.worktree/​$(basename $TASK_NAME)"

1. Determine PRD Mode: Check if third argument is existing file or task description

2. Check for Existing Worktree: If worktree exists, navigate to it; otherwise create new worktree

3. Create Git Worktree (if new):

git worktree add -b "$TASK_BRANCH" "$WORKTREE_DIR" "$TARGET_BRANCH"

1. Create Planning Configuration in worktree:

cat > "$WORKTREE_DIR/​.planning-config.json" << EOF
{
  "mode": "hybrid",
  "task_name": "$TASK_NAME",
  "task_branch": "$TASK_BRANCH",
  "target_branch": "$TARGET_BRANCH",
  "worktree_dir": "$WORKTREE_DIR",
  "original_branch": "$ORIGINAL_BRANCH",
  "root_dir": "$ROOT_DIR",
  "created_at": "$(date -u +%Y-%m-%dT%H:%M:%SZ)"
}
EOF

1. Create Initial Files in worktree (findings.md, progress.txt)

2. Navigate to Worktree:

cd "$WORKTREE_DIR"

1. Handle PRD:

   • If PRD_MODE is "load": Copy PRD file to worktree
   • If PRD_MODE is "generate": Use Task tool with run_in_background=true to generate PRD
     • IMPORTANT: After launching Task, immediately use TaskOutput with block=true to wait for completion
     • DO NOT use sleep loops

2. Validate and Display PRD: Show the generated/​loaded PRD with review

3. Show Ready Summary with next steps

Smart PRD Detection:

• If third argument is an existing file → Load that PRD
• If third argument is not a file → Use as task description to generate PRD

/​approve

Approve PRD and begin parallel story execution with batch progression.

/​approve

Execution Steps:

1. Verify PRD Exists: Check if prd.json exists in current directory

2. Read and Validate PRD: Validate structure and required fields

3. Calculate Execution Batches: Analyze dependencies and create parallel execution batches

   • Batch 1: Stories with no dependencies (can run in parallel)
   • Batch 2+: Stories whose dependencies are complete

4. Choose Execution Mode: Ask user to select execution mode:

   ==========================================
   Select Execution Mode
   ==========================================
   
     [1] Auto Mode  - Automatically progress through batches
                         Pause only on errors
   
     [2] Manual Mode - Require approval before each batch
                         Full control and review
   
   ==========================================
   Enter choice [1/​2] (default: 1):
   

5. Initialize Progress Tracking: Create/​initialize progress.txt with execution mode

6. Launch Batch 1 Agents: For each story in Batch 1, launch a background Task agent with this prompt:

   You are executing story {story_id}: {title}
   
   Description: {description}
   Acceptance Criteria: {criteria}
   
   Your task:
   1. Read relevant code and documentation
   2. Implement the story according to acceptance criteria
   3. Test your implementation
   4. Update findings.md with discoveries (use <!-- @tags: {story_id} -->)
   5. Mark complete by appending to progress.txt: [COMPLETE] {story_id}
   
   Execute all necessary bash/​powershell commands directly to complete the story.
   Work methodically and document your progress.
   

7. Monitor and Progress Through Batches:

   Based on selected mode:

   Auto Mode:

   • Poll progress.txt for completion every 10 seconds
   • When Batch 1 completes, automatically launch Batch 2
   • Continue until all batches complete or error detected
   • Pause only on [ERROR] or [FAILED] markers

   Manual Mode:

   • Poll progress.txt for completion every 10 seconds
   • When Batch 1 completes, prompt user for confirmation
   • Ask: "Launch Batch 2? [Y/​n]:"
   • If confirmed, launch Batch 2
   • Continue until all batches complete or error detected
   • Pause only on [ERROR] or [FAILED] markers

8. Show Completion Status: When all batches complete, show summary

Important:

• In both modes, agents execute commands directly without confirmation
• Execution mode ONLY controls batch-to-batch progression
• DO NOT add timeout or iteration limits to polling loops

/​edit

Edit the PRD in your default editor.

/​edit

/​status

Show execution status.

/​status

Workflows

Complete Workflow

1. /​hybrid:auto "Implement feature X"
   ↓
2. Review generated PRD
   ↓
3. /​edit (if needed) or /​approve
   ↓
4. Agents execute stories in parallel batches
   ↓
5. Monitor with /​status
   ↓
6. All stories complete

Manual PRD Workflow

1. Create prd.json (or use template)
   ↓
2. /​hybrid:manual prd.json
   ↓
3. Review and edit as needed
   ↓
4. /​approve
   ↓
5. Execution begins

Findings Tagging

When updating findings.md, tag sections with relevant story IDs:

<!-- @tags: story-001,story-002 -->

## Database Schema Discovery

The existing schema uses UUIDs for primary keys...

This allows agents to receive only relevant findings.

Progress Tracking

Track progress in progress.txt:

[2024-01-15 10:00:00] story-001: [IN_PROGRESS] story-001
[2024-01-15 10:15:00] story-001: [COMPLETE] story-001
[2024-01-15 10:15:00] story-002: [IN_PROGRESS] story-002

File Locking

The state manager uses platform-specific locking:

• Linux/​Mac: fcntl for advisory file locking
• Windows: msvcrt for file locking
• Fallback: PID-based lock files

Lock files are stored in .locks/ directory.

Error Handling

Validation Errors

If PRD validation fails:

1. Check for duplicate story IDs
2. Verify all dependencies exist
3. Ensure required fields are present
4. Use /​edit to fix issues

Execution Failures

If a story fails:

1. Check .agent-outputs/<story-id>.log
2. Review progress.txt for error messages
3. Fix issues manually or with agent help
4. Re-run the story

Dependency Cycles

If dependency cycles are detected:

1. Review /​show-dependencies output
2. Use /​edit to break cycles
3. Re-validate with /​hybrid:manual

Best Practices

1. Write Clear Descriptions: Agents work better with specific, detailed descriptions
2. Use Acceptance Criteria: Define what "done" means for each story
3. Tag Findings: Always tag findings with relevant story IDs
4. Update Progress: Mark stories complete promptly
5. Review Before Approval: Always review the PRD before approving

Integration with Planning-with-Files

This skill integrates seamlessly with planning-with-files:

• Standard Mode: Use alongside existing task_plan.md, findings.md, progress.md
• Worktree Mode: Each worktree can have its own PRD and story execution
• Session Recovery: Resume work after /​clear with /​hybrid:manual

Templates

Use the provided templates as starting points:

• templates/​prd.json.example - Example PRD structure
• templates/​prd_review.md - PRD review display template
• templates/​findings.md - Structured findings template

Troubleshooting

PRD Not Found

Error: No PRD found in current directory

Solution: Use /​hybrid:auto to generate or /​hybrid:manual to load.

Lock Timeout

TimeoutError: Could not acquire lock within 30s

Solution: Run python3 state_manager.py cleanup-locks to remove stale locks.

Dependency Not Found

Validation Error: Unknown dependency 'story-005'

Solution: Edit PRD to fix dependency reference or add missing story.

See Also

• planning-with-files - Base planning skill
• Ralph Loop - Original Ralph concept