7.8 KiB

Raw Blame History

Step 3: Context Completion & Finalization

MANDATORY EXECUTION RULES (READ FIRST):

🛑 NEVER generate content without user input
✅ ALWAYS treat this as collaborative completion between technical peers
📋 YOU ARE A FACILITATOR, not a content generator
💬 FOCUS on finalizing a lean, LLM-optimized project context
🎯 ENSURE all critical rules are captured and actionable
⚠️ ABSOLUTELY NO TIME ESTIMATES - AI development speed has fundamentally changed

EXECUTION PROTOCOLS:

🎯 Show your analysis before taking any action
📝 Review and optimize content for LLM context efficiency
📖 Update frontmatter with completion status
🚫 NO MORE STEPS - this is the final step

CONTEXT BOUNDARIES:

All rule categories from step-2 are complete
Technology stack and versions are documented
Focus on final review, optimization, and completion
Ensure the context file is ready for AI agent consumption

YOUR TASK:

Complete the project context file, optimize it for LLM efficiency, and provide guidance for usage and maintenance.

COMPLETION SEQUENCE:

1. Review Complete Context File

Read the entire project context file and analyze:

Content Analysis:

Total length and readability for LLMs
Clarity and specificity of rules
Coverage of all critical areas
Actionability of each rule

Structure Analysis:

Logical organization of sections
Consistency of formatting
Absence of redundant or obvious information
Optimization for quick scanning

2. Optimize for LLM Context

Ensure the file is lean and efficient:

Content Optimization:

Remove any redundant rules or obvious information
Combine related rules into concise bullet points
Use specific, actionable language
Ensure each rule provides unique value

Formatting Optimization:

Use consistent markdown formatting
Implement clear section hierarchy
Ensure scannability with strategic use of bolding
Maintain readability while maximizing information density

3. Final Content Structure

Ensure the final structure follows this optimized format:

# Project Context for AI Agents

_This file contains critical rules and patterns that AI agents must follow when implementing code in this project. Focus on unobvious details that agents might otherwise miss._

---

## Technology Stack & Versions

{{concise_technology_list}}

## Critical Implementation Rules

### Language-Specific Rules

{{specific_language_rules}}

### Framework-Specific Rules

{{framework_patterns}}

### Testing Rules

{{testing_requirements}}

### Code Quality & Style Rules

{{style_and_quality_patterns}}

### Development Workflow Rules

{{workflow_patterns}}

### Critical Don't-Miss Rules

{{anti_patterns_and_edge_cases}}

---

## Usage Guidelines

**For AI Agents:**

- Read this file before implementing any code
- Follow ALL rules exactly as documented
- When in doubt, prefer the more restrictive option
- Update this file if new patterns emerge

**For Humans:**

- Keep this file lean and focused on agent needs
- Update when technology stack changes
- Review quarterly for outdated rules
- Remove rules that become obvious over time

Last Updated: {{date}}

4. Present Completion Summary

Based on user skill level, present the completion:

Expert Mode: "Project context complete. Optimized for LLM consumption with {{rule_count}} critical rules across {{section_count}} sections.

File saved to: {output_folder}/project-context.md

Ready for AI agent integration."

Intermediate Mode: "Your project context is complete and optimized for AI agents!

What we created:

{{rule_count}} critical implementation rules
Technology stack with exact versions
Framework-specific patterns and conventions
Testing and quality guidelines
Workflow and anti-pattern rules

Key benefits:

AI agents will implement consistently with your standards
Reduced context switching and implementation errors
Clear guidance for unobvious project requirements

Next steps:

AI agents should read this file before implementing
Update as your project evolves
Review periodically for optimization"

Beginner Mode: "Excellent! Your project context guide is ready! 🎉

What this does: Think of this as a 'rules of the road' guide for AI agents working on your project. It ensures they all follow the same patterns and avoid common mistakes.

What's included:

Exact technology versions to use
Critical coding rules they might miss
Testing and quality standards
Workflow patterns to follow

How AI agents use it: They read this file before writing any code, ensuring everything they create follows your project's standards perfectly.

Your project context is saved and ready to help agents implement consistently!"

5. Final File Updates

Update the project context file with completion information:

Frontmatter Update:

---
project_name: '{{project_name}}'
user_name: '{{user_name}}'
date: '{{date}}'
sections_completed:
  ['technology_stack', 'language_rules', 'framework_rules', 'testing_rules', 'quality_rules', 'workflow_rules', 'anti_patterns']
status: 'complete'
rule_count: { { total_rules } }
optimized_for_llm: true
---

Add Usage Section: Append the usage guidelines from step 3 to complete the document.

6. Completion Validation

Final checks before completion:

Content Validation: ✅ All critical technology versions documented ✅ Language-specific rules are specific and actionable ✅ Framework rules cover project conventions ✅ Testing rules ensure consistency ✅ Code quality rules maintain standards ✅ Workflow rules prevent conflicts ✅ Anti-pattern rules prevent common mistakes

Format Validation: ✅ Content is lean and optimized for LLMs ✅ Structure is logical and scannable ✅ No redundant or obvious information ✅ Consistent formatting throughout

7. Completion Message

Present final completion to user:

"✅ Project Context Generation Complete!

Your optimized project context file is ready at: {output_folder}/project-context.md

📊 Context Summary:

{{rule_count}} critical rules for AI agents
{{section_count}} comprehensive sections
Optimized for LLM context efficiency
Ready for immediate agent integration

🎯 Key Benefits:

Consistent implementation across all AI agents
Reduced common mistakes and edge cases
Clear guidance for project-specific patterns
Minimal LLM context usage

📋 Next Steps:

AI agents will automatically read this file when implementing
Update this file when your technology stack or patterns evolve
Review quarterly to optimize and remove outdated rules

Your project context will help ensure high-quality, consistent implementation across all development work. Great work capturing your project's critical implementation requirements!"

SUCCESS METRICS:

✅ Complete project context file with all critical rules ✅ Content optimized for LLM context efficiency ✅ All technology versions and patterns documented ✅ File structure is logical and scannable ✅ Usage guidelines included for agents and humans ✅ Frontmatter properly updated with completion status ✅ User provided with clear next steps and benefits

FAILURE MODES:

❌ Final content is too verbose for LLM consumption ❌ Missing critical implementation rules or patterns ❌ Not optimizing content for agent readability ❌ Not providing clear usage guidelines ❌ Frontmatter not properly updated ❌ Not validating file completion before ending

WORKFLOW COMPLETE:

This is the final step of the Generate Project Context workflow. The user now has a comprehensive, optimized project context file that will ensure consistent, high-quality implementation across all AI agents working on the project.

The project context file serves as the critical "rules of the road" that agents need to implement code consistently with the project's standards and patterns.

7.8 KiB Raw Blame History