project-onboarding-rule

Project Onboarding System

Rule for automatically analyzing existing projects and integrating them into the AI-driven development workflow.

actions:

• type: react conditions:

  • pattern: "onboard project|project onboard" action: |

  Comprehensive onboarding of an existing project

  I'll perform a complete project onboarding by:

  1. Creating the required directory structure:

     • .cursor/specs/ - Requirements and specifications (managed by specification_management rule)
     • .cursor/tasks/ - Task tracking (managed by development_workflow_system rule)
     • .cursor/learnings/ - Knowledge capture (managed by knowledge_management rule)
     • .cursor/docs/ - Documentation (managed by knowledge_management rule)
     • .cursor/rules/ - Cursor rule files
     • .cursor/output/ - Generated reports

  2. Analyzing project structure:

     • Directory structure
     • File types and counts
     • Lines of code statistics

  3. Discovering existing documentation:

     • Finding README, CONTRIBUTING, CHANGELOG files
     • Cataloging documentation into .cursor/docs/existing/
     • Creating a documentation index

  4. Extracting core components:

     • Identifying main modules and components
     • Analyzing component relationships
     • Documenting component purposes

  5. Creating initial specifications:

     • Architecture overview specs
     • Component specifications
     • Feature specifications based on existing code

  6. Generating knowledge base:

     • Project structure learning
     • Component identification learning
     • Documentation assessment learning

  7. Setting up task tracking:

     • Initial onboarding completion task
     • Task index creation

  This process integrates an existing project into the AI-driven workflow without requiring changes to the original codebase.

• type: react conditions:

  • pattern: "analyze existing|existing analyze" action: |

  Analyze an existing codebase without full onboarding

  I'll analyze the existing codebase by:

  1. Examining project overview:

     • Project type detection
     • Repository structure analysis
     • File type distribution

  2. Calculating code statistics:

     • Lines of code by language
     • File counts by type
     • Directory structure

  3. Identifying key components:

     • Main modules and structure
     • Component relationships
     • Entry points

  4. Analyzing test structure:

     • Test directory organization
     • Test coverage assessment
     • Testing approach

  5. Reviewing documentation:

     • Available documentation files
     • Documentation completeness
     • Documentation types

  6. Providing integration recommendations:

     • Suggestions for specification creation (via specification_management rule)
     • Test coverage improvements (via development_workflow_system rule)
     • Documentation enhancements (via knowledge_management rule)

  The analysis report will be saved to .cursor/output/codebase_analysis_[timestamp].md

• type: react conditions:

  • pattern: "setup rules|rules setup" action: |

  Set up default rules for a project

  I'll set up the AI-driven development workflow rules:

  1. Creating the rules directory .cursor/rules/
  2. Setting up the following rule files:
     • development-workflow-rule.mdc - Task tracking, testing, and version control
     • specification-management-rule.mdc - Specification creation and validation
     • knowledge-management-rule.mdc - Knowledge capture and application
     • location-rule.mdc - Rules for organizing rule files
     • command-rules.mdc - AI command system
     • project-onboarding-rule.mdc - Project onboarding
     • on-load-rule.mdc - Critical development principles
  3. Creating required directory structure