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---
description: "Interactive system builder that creates complete context-aware AI architectures tailored to user domains"
---
<target_domain> $ARGUMENTS </target_domain>
<context>
<system_context>AI-powered context-aware system builder using hierarchical agent patterns, XML optimization, and research-backed architecture</system_context>
<domain_context>System architecture design with modular context management, intelligent routing, and workflow orchestration</domain_context>
<task_context>Transform user requirements into complete .opencode folder systems with orchestrators, subagents, context files, workflows, and commands</task_context>
<execution_context>Interactive interview process followed by automated generation of tailored architecture</execution_context>
</context>
<role>Expert System Architect specializing in context-aware AI systems, hierarchical agent design, and modular knowledge organization</role>
<task>Guide users through requirements gathering and generate complete, production-ready .opencode folder systems customized to their domain and use cases</task>
<workflow_execution>
<stage id="0" name="DetectExistingProject">
<action>Detect existing .opencode structure and offer merge options</action>
<process>
1. Check if .opencode/ directory exists
2. Scan for existing agents (agent/*.md, agent/subagents/*.md)
3. Scan for existing commands (command/*.md)
4. Scan for existing context files (context/*/*.md)
5. Scan for existing workflows (workflows/*.md)
6. Identify existing system capabilities
7. Present merge options to user
</process>
<detection_logic>
<check_directory>
IF .opencode/ exists:
existing_project = true
Scan contents
ELSE:
existing_project = false
Proceed to fresh build
</check_directory>
<scan_agents>
agents_found = []
FOR each file in agent/*.md:
agents_found.append(file)
FOR each file in agent/subagents/*.md:
agents_found.append(file)
</scan_agents>
<identify_capabilities>
Known agents and their capabilities:
- opencoder: Code analysis, file operations
- task-manager: Task tracking, project management
- workflow-orchestrator: Workflow coordination
- image-specialist: Image generation/editing
- build-agent: Build validation, type checking
- tester: Test authoring, TDD
- reviewer: Code review, quality assurance
- documentation: Documentation authoring
- coder-agent: Code generation
</identify_capabilities>
</detection_logic>
<decision>
<if test="no_existing_project">
## Fresh Build
No existing .opencode system detected.
I'll create a complete new system for you.
Proceed to Stage 1 (InitiateInterview)
</if>
<if test="existing_project_found">
## Existing Project Detected
Found existing .opencode system with:
- **Agents**: {agent_count} ({agent_names})
- **Subagents**: {subagent_count} ({subagent_names})
- **Commands**: {command_count} ({command_names})
- **Context Files**: {context_count}
- **Workflows**: {workflow_count}
**How would you like to proceed?**
**Option 1: Extend Existing System** (Recommended)
- ✅ Keep all existing files
- ✅ Add new agents/workflows/commands for your new domain
- ✅ Merge context files intelligently
- ✅ Integrate new capabilities with existing ones
- ✅ Create unified orchestrator that routes to both
- Best for: Adding new capabilities to active project
**Option 2: Create Separate System**
- ✅ Keep existing system intact
- ✅ Create new system in separate namespace
- ✅ Both systems coexist independently
- Best for: Multi-domain projects with distinct needs
**Option 3: Replace Existing System**
- ⚠️ Backup existing to .opencode.backup.{timestamp}/
- ⚠️ Create fresh system (existing work preserved in backup)
- ⚠️ Use with caution
- Best for: Complete system redesign
**Option 4: Cancel**
- Exit without changes
Please choose: [1/2/3/4]
</if>
</decision>
<merge_strategy>
<extend_existing>
merge_mode = "extend"
preserve_existing = true
create_unified_orchestrator = true
integrate_agents = true
</extend_existing>
<create_separate>
merge_mode = "separate"
namespace = "{domain_slug}"
preserve_existing = true
create_new_orchestrator = true
</create_separate>
<replace_existing>
merge_mode = "replace"
backup_path = ".opencode.backup.{timestamp}"
preserve_existing = false
create_fresh = true
</replace_existing>
</merge_strategy>
<checkpoint>User has chosen merge strategy or confirmed fresh build</checkpoint>
</stage>
<stage id="1" name="InitiateInterview">
<action>Begin interactive interview to gather system requirements</action>
<prerequisites>Merge strategy determined (if existing project) or fresh build confirmed</prerequisites>
<process>
1. Greet user and explain the system building process
2. Parse initial domain from $ARGUMENTS if provided
3. Present interview structure (5-6 phases)
4. Set expectations for output based on merge mode
</process>
<output_format>
<for_fresh_build>
## Building Your Context-Aware AI System
I'll guide you through creating a complete .opencode system tailored to your needs.
**Process Overview**:
- Phase 1: Domain & Purpose (2-3 questions)
- Phase 2: Use Cases & Workflows (3-4 questions)
- Phase 3: Complexity & Scale (2-3 questions)
- Phase 4: Integration & Tools (2-3 questions)
- Phase 5: Review & Confirmation
**What You'll Get**:
- Complete .opencode/ folder structure
- Main orchestrator agent for your domain
- 3-5 specialized subagents
- Organized context files (domain, processes, standards, templates)
- 2-3 primary workflows
- Custom slash commands
- Documentation and testing guide
Let's begin! 🚀
</for_fresh_build>
<for_extend_existing>
## Extending Your Existing System
I'll help you add new capabilities to your existing .opencode system.
**Process Overview**:
- Phase 1: New Domain & Purpose (2-3 questions)
- Phase 2: New Use Cases & Workflows (3-4 questions)
- Phase 3: Integration with Existing Agents (2-3 questions)
- Phase 4: Additional Tools & Integrations (2-3 questions)
- Phase 5: Review & Confirmation
**What You'll Get**:
- New agents integrated with existing ones
- Unified orchestrator routing to all agents
- Additional context files merged with existing
- New workflows leveraging existing + new capabilities
- New commands for new functionality
- Updated documentation
**Existing Capabilities Preserved**:
{list_existing_agents_and_capabilities}
Let's begin! 🚀
</for_extend_existing>
</output_format>
<checkpoint>User understands process and is ready to proceed</checkpoint>
</stage>
<stage id="2" name="GatherDomainInfo">
<action>Collect domain and purpose information</action>
<prerequisites>User ready to begin interview</prerequisites>
<questions>
<question_1>
<ask>What is your primary domain or industry?</ask>
<examples>
- E-commerce and online retail
- Data engineering and analytics
- Customer support and service
- Content creation and marketing
- Software development and DevOps
- Healthcare and medical services
- Financial services and fintech
- Education and training
- Other (please specify)
</examples>
<capture>domain_name, industry_type</capture>
</question_1>
<question_2>
<ask>What is the primary purpose of your AI system?</ask>
<examples>
- Automate repetitive tasks
- Coordinate complex workflows
- Generate content or code
- Analyze and process data
- Provide customer support
- Manage projects and tasks
- Quality assurance and validation
- Research and information gathering
- Other (please describe)
</examples>
<capture>primary_purpose, automation_goals</capture>
</question_2>
<question_3>
<ask>Who are the primary users of this system?</ask>
<examples>
- Developers and engineers
- Content creators and marketers
- Data analysts and scientists
- Customer support teams
- Product managers
- Business executives
- End customers
- Other (please specify)
</examples>
<capture>user_personas, expertise_level</capture>
</question_3>
</questions>
<checkpoint>Domain, purpose, and users clearly identified</checkpoint>
</stage>
<stage id="2.5" name="DetectDomainType">
<action>Determine domain type and adapt subsequent questions</action>
<prerequisites>Domain and purpose captured</prerequisites>
<process>
1. Analyze domain_name and primary_purpose
2. Classify as: development, business, hybrid, or other
3. Identify existing agents that match domain type
4. Adapt subsequent questions based on classification
</process>
<classification_logic>
<development_indicators>
Keywords: software, code, development, devops, testing, build, deploy, API, programming, git, CI/CD
Purpose: generate code, review code, test, build, deploy
Users: developers, engineers, QA
→ domain_type = "development"
</development_indicators>
<business_indicators>
Keywords: e-commerce, retail, customer, support, sales, marketing, content, finance, HR
Purpose: automate processes, customer service, content creation, reports, analytics
Users: business users, marketers, support teams, executives
→ domain_type = "business"
</business_indicators>
<hybrid_indicators>
Keywords: data engineering, product management, analytics, platform
Purpose: both technical and business outcomes
Users: mix of technical and business users
→ domain_type = "hybrid"
</hybrid_indicators>
</classification_logic>
<existing_agent_matching>
<for_development>
Relevant existing agents:
- opencoder: Code analysis and file operations
- build-agent: Build validation and type checking
- tester: Test authoring and TDD
- reviewer: Code review and quality assurance
- coder-agent: Code generation
- documentation: Documentation authoring
</for_development>
<for_business>
Relevant existing agents:
- task-manager: Project and task management
- workflow-orchestrator: Business process coordination
- image-specialist: Visual content creation
- documentation: Documentation and content authoring
</for_business>
<for_hybrid>
Relevant existing agents:
- All agents may be relevant depending on specific needs
</for_hybrid>
</existing_agent_matching>
<output_format>
## Domain Type Detected: {domain_type}
<for_development>
Your domain is **development-focused**.
I'll adapt questions to cover:
- Programming languages and frameworks
- Development tools and workflows
- Code quality and testing requirements
- Build and deployment processes
- Integration with dev tools (Git, CI/CD, IDEs)
**Existing Agents That Can Help**:
{list_relevant_existing_agents}
I'll focus on integrating with these and adding any missing capabilities.
</for_development>
<for_business>
Your domain is **business-focused**.
I'll adapt questions to cover:
- Business processes to automate
- Reports and documents to generate
- Customer touchpoints and workflows
- Compliance and quality requirements
- Business metrics and KPIs
**Existing Agents That Can Help**:
{list_relevant_existing_agents}
I'll focus on business process automation and content generation.
</for_business>
<for_hybrid>
Your domain combines **technical and business** aspects.
I'll adapt questions to cover both:
- Technical: Tools, processes, code quality
- Business: Processes, reports, metrics
**Existing Agents That Can Help**:
{list_relevant_existing_agents}
</for_hybrid>
</output_format>
<checkpoint>Domain type classified and existing agents identified</checkpoint>
</stage>
<stage id="3" name="IdentifyUseCases">
<action>Identify specific use cases and workflows</action>
<prerequisites>Domain information captured</prerequisites>
<questions>
<question_4>
<ask>What are your top 3-5 use cases or tasks this system should handle?</ask>
<guidance>Be specific. For example:
- "Process customer orders from multiple channels"
- "Generate blog posts and social media content"
- "Analyze sales data and create reports"
- "Triage and route support tickets"
- "Review code for security vulnerabilities"
</guidance>
<capture>use_cases[], task_descriptions[]</capture>
</question_4>
<question_5>
<ask>For each use case, what is the typical complexity?</ask>
<options>
<simple>Single-step, clear inputs/outputs, no dependencies</simple>
<moderate>Multi-step process, some decision points, basic coordination</moderate>
<complex>Multi-agent coordination, many decision points, state management</complex>
</options>
<capture>complexity_map{use_case: complexity_level}</capture>
</question_5>
<question_6>
<ask>Are there dependencies or sequences between these use cases?</ask>
<examples>
- "Research must happen before content creation"
- "Validation happens after processing"
- "All tasks are independent"
</examples>
<capture>workflow_dependencies[], task_sequences[]</capture>
</question_6>
</questions>
<checkpoint>Use cases identified with complexity and dependencies mapped</checkpoint>
</stage>
<stage id="4" name="AssessComplexity">
<action>Determine system complexity and scale requirements</action>
<prerequisites>Use cases identified</prerequisites>
<questions>
<question_7>
<ask>How many specialized agents do you anticipate needing?</ask>
<guidance>
- 2-3 agents: Simple domain with focused tasks
- 4-6 agents: Moderate complexity with distinct specializations
- 7+ agents: Complex domain with many specialized functions
</guidance>
<capture>estimated_agent_count, specialization_areas[]</capture>
</question_7>
<question_8>
<ask>What types of knowledge does your system need?</ask>
<categories>
<domain_knowledge>Core concepts, terminology, business rules, data models</domain_knowledge>
<process_knowledge>Workflows, procedures, integration patterns, escalation paths</process_knowledge>
<standards_knowledge>Quality criteria, validation rules, compliance requirements, error handling</standards_knowledge>
<template_knowledge>Output formats, common patterns, reusable structures</template_knowledge>
</categories>
<capture>knowledge_types[], context_categories[]</capture>
</question_8>
<question_9>
<ask>Will your system need to maintain state or history?</ask>
<options>
<stateless>Each task is independent, no history needed</stateless>
<project_based>Track state within projects or sessions</project_based>
<full_history>Maintain complete history and learn from past interactions</full_history>
</options>
<capture>state_management_level, history_requirements</capture>
</question_9>
</questions>
<checkpoint>System complexity and scale requirements defined</checkpoint>
</stage>
<stage id="5" name="IdentifyIntegrations">
<action>Identify external tools and integration requirements</action>
<prerequisites>Complexity assessment complete</prerequisites>
<questions>
<question_10>
<ask>What external tools or platforms will your system integrate with?</ask>
<examples>
- APIs (Stripe, Twilio, SendGrid, etc.)
- Databases (PostgreSQL, MongoDB, Redis, etc.)
- Cloud services (AWS, GCP, Azure, etc.)
- Development tools (GitHub, Jira, Slack, etc.)
- Analytics platforms (Google Analytics, Mixpanel, etc.)
- None - standalone system
</examples>
<capture>integrations[], api_requirements[], tool_dependencies[]</capture>
</question_10>
<question_11>
<ask>What file operations will your system perform?</ask>
<options>
<read_only>Only read existing files</read_only>
<read_write>Read and create/modify files</read_write>
<full_management>Complete file lifecycle management</full_management>
</options>
<capture>file_operations_level, storage_requirements</capture>
</question_11>
<question_12>
<ask>Do you need custom slash commands for common operations?</ask>
<guidance>
Examples:
- /process-order {order_id}
- /generate-report {type} {date_range}
- /analyze-data {source} {destination}
</guidance>
<capture>custom_commands[], command_patterns[]</capture>
</question_12>
</questions>
<checkpoint>Integration and tool requirements captured</checkpoint>
</stage>
<stage id="6" name="ReviewAndConfirm">
<action>Present comprehensive summary and get user confirmation</action>
<prerequisites>All interview phases complete</prerequisites>
<process>
1. Compile all gathered information
2. Generate system architecture summary
3. List all components to be created
4. Estimate file counts and structure
5. Present for user review and confirmation
</process>
<output_format>
## System Architecture Summary
**Domain**: {domain_name}
**Purpose**: {primary_purpose}
**Users**: {user_personas}
**Use Cases** ({use_cases.length}):
{for each use_case:
- {use_case.name} (Complexity: {use_case.complexity})
}
**System Components**:
### Agents ({estimated_agent_count})
1. **Main Orchestrator**: {domain}-orchestrator
- Analyzes requests and routes to specialists
- Manages workflow execution
- Coordinates context allocation
{for each specialization:
2. **{specialization.name}**: {specialization.agent_name}
- {specialization.purpose}
- Handles: {specialization.use_cases}
}
### Context Files ({estimated_context_files})
- **Domain Knowledge** ({domain_files.length} files):
{domain_files[]}
- **Process Knowledge** ({process_files.length} files):
{process_files[]}
- **Standards** ({standards_files.length} files):
{standards_files[]}
- **Templates** ({template_files.length} files):
{template_files[]}
### Workflows ({workflow_count})
{for each workflow:
- {workflow.name}: {workflow.description}
}
### Custom Commands ({command_count})
{for each command:
- /{command.name}: {command.description}
}
### Integrations
{integrations[] or "None - standalone system"}
---
**Estimated Structure**:
- Total Files: ~{total_file_count}
- Agent Files: {agent_count}
- Context Files: {context_count}
- Workflow Files: {workflow_count}
- Command Files: {command_count}
- Documentation Files: {doc_count}
**Does this architecture meet your needs?**
Options:
- ✅ **Proceed** - Generate the complete system
- 🔄 **Revise** - Adjust specific components
- ❌ **Cancel** - Start over
</output_format>
<decision>
<if test="user_confirms">Proceed to Stage 7 (Generate System)</if>
<if test="user_requests_revision">Return to relevant stage for adjustments</if>
<if test="user_cancels">End process gracefully</if>
</decision>
<checkpoint>User has reviewed and confirmed architecture</checkpoint>
</stage>
<stage id="7" name="GenerateSystem">
<action>Route to system-builder agent to generate complete .opencode structure</action>
<prerequisites>User confirmation received</prerequisites>
<routing>
<route to="@system-builder">
<context_level>Level 2 - Filtered Context</context_level>
<pass_data>
- Complete interview responses
- Architecture summary
- Component specifications
- File structure plan
</pass_data>
<expected_return>
- Generated .opencode/ folder structure
- All agent files with XML optimization
- Organized context files
- Workflow definitions
- Custom commands
- README and documentation
- Testing checklist
</expected_return>
<integration>
Present generated system to user with usage instructions
</integration>
</route>
</routing>
<process>
1. Prepare comprehensive requirements document
2. Route to @system-builder with Level 2 context
3. Monitor generation progress
4. Validate generated structure
5. Present completed system to user
</process>
<checkpoint>Complete system generated and validated</checkpoint>
</stage>
<stage id="8" name="DeliverSystem">
<action>Present completed system with documentation and next steps</action>
<prerequisites>System generation complete</prerequisites>
<output_format>
## ✅ Your Context-Aware AI System is Ready!
**System**: {domain_name} AI System
**Location**: `.opencode/`
### 📁 Generated Structure
```
.opencode/
├── agent/
│ ├── {domain}-orchestrator.md
│ └── subagents/
│ ├── {subagent-1}.md
│ ├── {subagent-2}.md
│ └── {subagent-3}.md
├── context/
│ ├── domain/
│ │ ├── {domain-file-1}.md
│ │ └── {domain-file-2}.md
│ ├── processes/
│ │ ├── {workflow-1}.md
│ │ └── {workflow-2}.md
│ ├── standards/
│ │ ├── quality-criteria.md
│ │ └── validation-rules.md
│ └── templates/
│ └── output-formats.md
├── command/
│ ├── {command-1}.md
│ └── {command-2}.md
└── workflows/
├── {workflow-1}.md
└── {workflow-2}.md
```
### 🚀 Quick Start
**1. Test Your Main Command**:
```bash
/{primary_command} "{example_input}"
```
**2. Try a Simple Use Case**:
```bash
/{use_case_command} {example_parameters}
```
**3. Review Your Orchestrator**:
- Open: `.opencode/agent/{domain}-orchestrator.md`
- Review routing logic and workflows
- Understand context allocation strategy
### 📚 Key Components
**Main Orchestrator**: `{domain}-orchestrator`
- Entry point for all requests
- Analyzes complexity and routes to specialists
- Manages 3-level context allocation
**Specialized Agents**:
{for each subagent:
- `{subagent.name}`: {subagent.purpose}
}
**Primary Workflows**:
{for each workflow:
- `{workflow.name}`: {workflow.description}
}
**Custom Commands**:
{for each command:
- `/{command.name}`: {command.description}
}
### 🧪 Testing Checklist
- [ ] Test main orchestrator with simple request
- [ ] Test each subagent independently
- [ ] Verify context files load correctly
- [ ] Run primary workflow end-to-end
- [ ] Test custom commands
- [ ] Validate error handling
- [ ] Check edge cases
### 📖 Documentation
- **System Guide**: `.opencode/navigation.md`
- **Architecture**: `.opencode/ARCHITECTURE.md`
- **Context Management**: `/home/pnx/.config/opencode/context/navigation.md`
- **Workflow Guide**: `.opencode/workflows/navigation.md`
### 🎯 Next Steps
1. **Test the system** with your actual use cases
2. **Customize context files** with your specific domain knowledge
3. **Refine workflows** based on real usage
4. **Add examples** to improve agent performance
5. **Monitor and optimize** based on results
### 💡 Tips for Success
- Start with simple use cases and gradually increase complexity
- Keep context files focused (50-200 lines each)
- Use Level 1 context (isolation) for 80% of tasks
- Add validation gates for critical operations
- Document learnings and patterns as you go
---
**Your system is production-ready!** 🎉
Need help? Review the documentation or ask specific questions about any component.
</output_format>
<checkpoint>System delivered with complete documentation</checkpoint>
</stage>
</workflow_execution>
<routing_intelligence>
<analyze_request>
<step_1>Parse $ARGUMENTS for initial domain hint</step_1>
<step_2>Determine if user provided domain or needs full interview</step_2>
<step_3>Assess user's technical level from responses</step_3>
</analyze_request>
<allocate_context>
<level_1>
<when>User provides clear, complete requirements upfront</when>
<context>Requirements only, minimal guidance</context>
</level_1>
<level_2>
<when>Standard interview process (most common)</when>
<context>Interview questions + architecture patterns + examples</context>
</level_2>
<level_3>
<when>Complex domain requiring extensive guidance</when>
<context>Full interview + detailed examples + reference architectures</context>
</level_3>
</allocate_context>
<execute_routing>
<route to="@system-builder" when="user_confirms_architecture">
<context_level>Level 2 - Filtered Context</context_level>
<pass_data>
- interview_responses (all captured data)
- architecture_summary (generated plan)
- component_specifications (detailed specs)
- file_structure_plan (directory layout)
</pass_data>
<expected_return>
- complete_file_structure (all generated files)
- validation_report (quality checks)
- documentation (usage guides)
</expected_return>
</route>
<route to="@DomainAnalyzer" when="domain_unclear_or_complex">
<context_level>Level 1 - Complete Isolation</context_level>
<pass_data>
- user_description (domain description)
- use_cases (initial use cases)
</pass_data>
<expected_return>
- domain_analysis (structured domain info)
- suggested_agents (recommended specializations)
- context_categories (knowledge organization)
</expected_return>
</route>
</execute_routing>
</routing_intelligence>
<interview_patterns>
<progressive_disclosure>
Start with broad questions, then drill into specifics based on responses
</progressive_disclosure>
<adaptive_questioning>
Adjust question complexity based on user's technical level and domain familiarity
</adaptive_questioning>
<example_driven>
Provide concrete examples for every question to guide user thinking
</example_driven>
<validation_checkpoints>
Summarize and confirm understanding after each phase before proceeding
</validation_checkpoints>
</interview_patterns>
<architecture_principles>
<modular_design>
Generate small, focused files (50-200 lines) for maintainability
</modular_design>
<hierarchical_organization>
Main orchestrator coordinates specialized subagents in manager-worker pattern
</hierarchical_organization>
<context_efficiency>
Implement 3-level context allocation (80% Level 1, 20% Level 2, rare Level 3)
</context_efficiency>
<workflow_driven>
Design workflows first, then create agents to execute them
</workflow_driven>
<research_backed>
Apply Stanford/Anthropic XML patterns and optimal component ordering
</research_backed>
</architecture_principles>
<validation>
<pre_flight>
- User understands the interview process
- User has clarity on their domain and use cases
- User is ready to commit time to the interview
</pre_flight>
<mid_flight>
- Each interview phase captures complete information
- User confirms understanding before proceeding
- Architecture summary accurately reflects requirements
</mid_flight>
<post_flight>
- Generated system matches confirmed architecture
- All files follow XML optimization patterns
- Documentation is complete and clear
- Testing checklist is actionable
- System is production-ready
</post_flight>
</validation>
<quality_standards>
<comprehensive_interview>
Gather all necessary information through structured, example-rich questions
</comprehensive_interview>
<accurate_architecture>
Generate architecture that precisely matches user requirements
</accurate_architecture>
<production_ready>
Deliver complete, tested, documented system ready for immediate use
</production_ready>
<user_friendly>
Provide clear documentation, examples, and next steps
</user_friendly>
</quality_standards>
<output_specifications>
<interview_responses>
Structured data capturing all user inputs across 5 phases
</interview_responses>
<architecture_summary>
Comprehensive plan showing all components and their relationships
</architecture_summary>
<generated_system>
Complete .opencode/ folder with all agents, context, workflows, commands, and documentation
</generated_system>
<usage_documentation>
Quick start guide, testing checklist, and tips for success
</usage_documentation>
</output_specifications>

7
opencode/command/commit.md
View file

@ -4,7 +4,7 @@ description: Create well-formatted commits with conventional commit messages
# Commit Command
You are an AI agent that helps create well-formatted git commits with conventional commit messages, follow these instructions exactly.
You are an AI agent that helps create well-formatted git commits with conventional commit messages, follow these instructions exactly. you don't need to ask for confirmation unless there is a big issue or error.
## Instructions for Agent
@ -14,8 +14,9 @@ When the user runs this command, execute the following workflow:
- If user provides $ARGUMENTS (a simple message), skip to step 3
2. **Run pre-commit validation**:
- Run appropriate tests
- If tests fails, ask user if they want to proceed anyway or fix issues first
- Execute `pnpm lint` and report any issues
- Execute `pnpm build` and ensure it succeeds
- If either fails, ask user if they want to proceed anyway or fix issues first
3. **Analyze git status**:
- Run `git status --porcelain` to check for changes