ralph-autonomous

name	ralph-autonomous
description	Use this skill when Ralph is working autonomously through Brain Dump backlogs. Covers ticket selection, implementation patterns, and autonomous workflow management.
license	MIT
compatibility	opencode
metadata	{"audience":"developers","workflow":"autonomous"}

Ralph Autonomous Workflow

This skill guides Ralph when working autonomously through Brain Dump backlogs without direct user supervision.

Autonomous Mode Principles

Core Philosophy

• No User Input Required: Ralph makes decisions independently
• Context-Driven: Uses PRD and progress files for guidance
• Incremental Progress: One ticket per session, verify completion
• Self-Documenting: Logs all decisions and progress via MCP

Decision Framework

Ralph evaluates tickets based on:

1. Priority (high > medium > low)
2. Dependencies (foundational work first)
3. Complexity (quick wins vs major features)
4. Current Context (progress from previous sessions)

Standard Operating Procedure

Session Start

# 1. Load current context
read('plans/prd.json')           # Get incomplete tickets
read('plans/progress.txt')         # Previous session context

# 2. Analyze ticket landscape
list_tickets()                     # Current state overview
find_project_by_path()            # Verify project context

Ticket Selection Algorithm

// Pseudo-code for Ralph's selection logic
function selectTicket(prdTickets: PrdTicket[]): Ticket {
  // Filter: only tickets Ralph still needs to advance
  const incomplete = prdTickets.filter((t) => !t.passes);

  // plans/prd.json does not include live Brain Dump status. Fetch each
  // incomplete ticket before applying status-aware selection rules.
  const tickets = incomplete.map((t) => ticket.get({ ticketId: t.id }));

  // Resume AI review before starting fresh implementation work.
  const inReview = tickets.filter((t) => t.status === "ai_review");
  if (inReview.length > 0) {
    return inReview[0];
  }

  // Sort by priority, then dependencies
  const runnable = tickets.filter((t) => ["backlog", "ready", "in_progress"].includes(t.status));
  const sorted = runnable.sort((a, b) => {
    if (a.priority !== b.priority) {
      return priorityOrder[a.priority] - priorityOrder[b.priority];
    }
    return dependencyCount(a) - dependencyCount(b);
  });

  // Choose optimal ticket
  return sorted[0]; // Highest priority, least blocked
}

Work Execution Pattern

# 1. Initialize ticket work
workflow "start-work"(selectedTicketId)

# 2. Implementation phase
# - Read existing code patterns
# - Follow project conventions
# - Write minimal, focused changes

# 3. Verification
# Discover validation commands from project docs/config.
# Do not assume pnpm/npm; use the project-standard commands.

# 4. Complete implementation
workflow "complete-work"(ticketId, summary)

# 5. AI review and demo handoff
review "check-complete"(ticketId)
review "generate-demo"(ticketId, steps)

Intelligent Decision Making

When Stuck on Implementation

# Log the issue
comment "add"(ticketId,
  "Blocked: [specific issue]. Will continue with next ticket.",
  "ralph",
  "blocker")

# Move on (don't waste time)
return next_best_ticket()

Handling Dependencies

If selected ticket has unmet dependencies:

1. Check if dependency ticket exists

   dependency_tickets = tickets.filter(t =>
     selectedTicket.dependencies.includes(t.id)
   )
   

2. If dependency exists → Work on dependency first

3. If dependency missing → Create dependency ticket

Scope Creep Prevention

# Before starting implementation
verify_ticket_scope(ticket) {
  estimated_time = estimate_complexity(ticket)
  if (estimated_time > 4_hours) {
    # Break into smaller tickets
    split_ticket(ticket)
    return smallest_piece()
  }
}

Code Implementation Patterns

Read Before Writing

# Always understand existing patterns
find_similar_implementations(ticket.description)
read_existing_components(ticket.related_area)

Minimal Changes

• Only implement what's in acceptance criteria
• No "gold plating" or extra features
• Follow existing conventions exactly

Testing Requirements

// Every ticket must pass these checks
interface TicketCompletion {
  validation_run: boolean; // project-specific validation was run or explicitly unavailable
  validation_summary: string; // exact pass/fail/skipped results
  acceptance_met: boolean; // All AC items verified
  no_regressions: boolean; // No existing functionality broken
}

Progress Tracking

Session Logging

Ralph automatically logs:

# Start of session
comment "add"("session-start",
  `Ralph session started. Available tickets: ${count}`,
  "ralph",
  "session")

# Ticket decisions
comment "add"(ticketId,
  `Selected ticket: ${ticket.title}. Reason: ${reason}`,
  "ralph",
  "decision")

# Implementation progress
comment "add"(ticketId,
  `Completed: ${component}. Next: ${next_step}`,
  "ralph",
  "progress")

# Blockers and issues
comment "add"(ticketId,
  `Issue: ${problem}. Solution: ${approach}`,
  "ralph",
  "issue-resolution")

Progress Updates in File

# plans/progress.txt - persistent context
echo "$(date): Ralph completed ticket ${ticketId}" >> plans/progress.txt
echo "Next session context: ${next_priorities}" >> plans/progress.txt

Quality Assurance

Pre-Completion Checklist

Before calling workflow "complete-work"():

const completion_checklist = {
  code_quality: verify_style_conventions(),
  error_handling: verify_error_boundaries(),
  performance: no_performance_regressions(),
  documentation: updated_docs_if_needed(),
  testing: all_tests_passing(),
  acceptance: all_criteria_met(),
};

if (!completion_checklist.all_true()) {
  fix_remaining_issues();
}

Self-Correction

If Ralph makes mistakes:

1. Detect through testing or review
2. Log the issue transparently
3. Correct immediately
4. Document lessons learned

Emergency Procedures

MCP Server Down

# Fallback to manual workflow
if (!mcp_tools_available()) {
  git checkout -b "feature/ralph-manual"
  # Work without ticket tracking
  # Update PRD manually when done
}

Database Issues

# Work offline if needed
if (!database_accessible()) {
  create_local_branch()
  implement_changes()
  # Sync tickets when database recovers
}

Optimization Patterns

Learning from History

Ralph improves over time by analyzing:

• Previous implementation choices
• Common blockers and patterns
• Estimation accuracy
• Code quality feedback

Batch Operations

When multiple similar tickets exist:

// Batch similar work for efficiency
similar_tickets = find_similar_tickets(current);
if (similar_tickets.length > 1) {
  implement_common_base();
  complete_individual_variants();
}

Communication Style

Autonomous Updates

Ralph provides updates without being asked:

• Every 30 minutes during long tasks
• When major decisions are made
• When blockers are encountered
• Before moving to next ticket

Transparency

All decision-making is documented:

comment "add"(ticketId,
  `Decision: Chose approach X over Y because:
  1. Performance: 50% faster
  2. Maintainability: Less code
  3. Compatibility: Works with existing system`,
  "ralph",
  "decision")

Session Completion

Final Status Report

When all tickets are complete:

echo "PRD_COMPLETE"  # Signal completion

# Generate summary
comment "add"("project-complete",
  `All ${total_tickets} tickets completed.
  Total time: ${elapsed_time}.
  Key achievements: ${highlights}`,
  "ralph",
  "summary")

Handoff Preparation

# Prepare for next session
update_progress_file_with_next_steps()
identify_remaining_dependencies()
suggest_priorities_for_next_session()

Troubleshooting

Common Issues

1. Ticket selection conflicts → Use priority matrix
2. Implementation ambiguity → Choose simplest approach that meets AC
3. Test failures → Fix before proceeding
4. Scope creep → Split ticket or defer features

Recovery Patterns

• Never skip a ticket without logging why
• Always leave the codebase in a working state
• Document any temporary workarounds

This skill ensures Ralph works effectively and autonomously while maintaining high code quality and transparency.