{
"event": "PreToolUse",
"tool_name": "Task",
"tool_input": {
"description": "Explore CRUD patterns",
"prompt": "Find examples of how CRUD operations and table views are implemented in this project:\n1. Look at a simple Controller + UseCase + Repository pattern example\n2. Find how tables are rendered in views (likely in \/src\/View\/ or \/app\/View\/)\n3. Check the services.php file for DI registration patterns\n4. Look for any existing \"scan\" or \"index\" functionality that lists files\n\nFocus on understanding the architectural patterns used.",
"subagent_type": "Explore"
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{
"tool_response": {
"status": "completed",
"prompt": "Check the ki_dev database schema for any existing code_analysis table or similar tables. Use the MCP tools:\n1. mcp__mcp-db__db_tables to list all tables in ki_dev\n2. mcp__mcp-db__db_describe for any code_analysis or similar table if it exists\n3. Look for patterns of how other \"analysis\" or \"scan\" features store data\n\nAlso search the codebase for any existing file scanning functionality.",
"agentId": "aa9b933",
"content": [
{
"type": "text",
"text": "I've completed a comprehensive exploration of the ki_dev database schema and existing code analysis functionality. Here's my detailed report:\n\n## Database Schema Analysis - ki_dev\n\n### Summary\nThe ki_dev database contains **21 tables** with no existing `code_analysis` table. However, I found several related analysis and validation patterns already in use.\n\n### Key Tables Found\n\n**Analysis-Related Tables:**\n\n1. **contract_validations** (34 rows)\n - Stores validation results for contract compliance\n - Schema includes:\n - `result` (enum: passed\/failed)\n - `critical_count`, `major_count`, `minor_count` (violation counts)\n - `violations` (JSON blob with detailed issues)\n - `triggered_by` (enum: sync, manual, hook, mcp)\n - `target_path` (specific path being validated)\n - `duration_ms` (performance metric)\n\n2. **dokumentation_chunks** (734 rows)\n - Stores document chunks with analysis metadata\n - Analysis fields include:\n - `taxonomy_category` (string)\n - `taxonomy_path` (JSON array)\n - `entities` (JSON array with name\/type)\n - `keywords` (JSON array)\n - `glossary_terms` (JSON array)\n - `analysis_status` (enum: pending, processing, completed, failed)\n - `analysis_error` (text)\n - `analyzed_at` (datetime)\n - `analysis_model` (the model used)\n - `embedding_model` (default: mxbai-embed-large)\n\n3. **audit_log** (0 rows)\n - Stores audit events with structured context\n - Fields: correlation_id, event, entity_type, entity_id, context (JSON), level, user_id, ip_address\n - Good for tracking analysis operations\n\n4. **tasks** (231 rows)\n - Task management with metadata (JSON)\n - Can store task results via `task_results` table\n\n5. **mcp_log** (2,526 rows) & **pipeline_log** (2,541 rows)\n - Logging infrastructure for tracking operations\n\n### Existing Code Analysis Patterns\n\n**Found 4 files with analysis functionality:**\n\n1. **ChunkAnalysisService.php** (`\/var\/www\/dev.campus.systemische-tools.de\/src\/Infrastructure\/Docs\/`)\n - Analyzes documentation chunks via LLM\n - Extracts: taxonomy (3-level hierarchy), entities (name\/type), keywords\n - Stores results directly in `dokumentation_chunks` table\n - Uses Ollama with model `gemma3:4b-it-qat`\n - Implements retry logic (3 attempts) and batch processing\n\n2. **AuditLogger.php** (`\/var\/www\/dev.campus.systemische-tools.de\/src\/Infrastructure\/Logging\/`)\n - Provides structured audit logging\n - Tracks: event name, entity type\/id, context (JSON), level (debug\/info\/warning\/error)\n - Uses correlation IDs for tracing related operations\n\n3. **ContentQualityValidator.php** (`\/var\/www\/dev.campus.systemische-tools.de\/src\/Infrastructure\/AI\/`)\n - Validates content quality via LLM\n - Returns: passed (bool), score (float), issues (array), details (string)\n - Uses Ollama with `mistral` model at temperature 0.1\n\n4. **php-check.sh** (`\/opt\/scripts\/`)\n - Quality check script with 5 checks:\n 1. PHPStan (static analysis with strict rules)\n 2. PHP-CS-Fixer (code style PSR-12)\n 3. Composer Audit (dependency vulnerabilities)\n 4. Semgrep (OWASP security scan)\n 5. DI Check (dependency resolution)\n\n### Storage Patterns Identified\n\n**Pattern 1: Inline Analysis in Domain Tables**\n- Data stored directly in the table being analyzed (dokumentation_chunks)\n- Pros: Single query, no joins needed\n- Used for: Document chunk analysis\n\n**Pattern 2: Separate Validation Table**\n- Validation results stored separately (contract_validations)\n- Tracks validation history, multiple runs per entity\n- Pros: Audit trail, change tracking\n- Used for: Contract compliance\n\n**Pattern 3: Task-Based Results**\n- Analysis results can be stored via task_results table\n- Linked to tasks via task_id\n- Pros: Workflow integration, progress tracking\n\n**Pattern 4: Audit Log**\n- Generic event logging with JSON context\n- Pros: Cross-entity tracing via correlation ID\n- Used for: Operation tracking\n\n### Relevant Database Tables for Code Analysis\n\nIf implementing file scanning, you could leverage:\n\n```\ntasks - Track scan jobs\ntask_results - Store scan results\naudit_log - Log scan events\nmcp_log - Log MCP operations\npipeline_log - Track pipeline execution\n```\n\n### Key Architecture Notes\n\n1. **No existing code_analysis table** - Would need to be created\n2. **JSON storage pattern** - Used extensively for complex data (violations, entities, keywords)\n3. **Status enums** - Standard pattern: pending → processing → completed\/failed\n4. **Timestamps** - Both datetime and datetime(6) with microseconds used\n5. **Foreign keys** - CASCADE delete used for related data\n6. **Indexing** - Status and timestamps indexed for filtering\/sorting\n7. **Audit trail** - Separate history tables used (contract_history, dokumentation_history)\n\n### Conclusion\n\nThe database already has well-established patterns for storing analysis results through:\n- Direct table columns (dokumentation_chunks)\n- Dedicated validation tables (contract_validations)\n- Task results linking (task_results)\n\nFor a new file\/code analysis feature, you could either:\n1. Create a dedicated `code_analysis` table following the `contract_validations` pattern\n2. Use the task system with `task_results` for integration\n3. Store analysis in `audit_log` with rich JSON context\n\nAll findings are from **read-only database inspection and existing source code analysis** - no system state has been modified."
}
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"service_tier": "standard"
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