lcbp3/.agents/workflows/107-speckit.implement.md

auto_execution_mode, description

auto_execution_mode	description
0	Execute the implementation plan by processing and executing all tasks defined in tasks.md

Workflow: speckit.implement

1. Context Analysis:

   • The user has provided an input prompt. Treat this as the primary input for the skill.

2. Load Skill:

   • Use the view_file tool to read the skill file at: .agents/skills/speckit-implement/SKILL.md

3. Execute:

   • Follow the instructions in the SKILL.md exactly.
   • Apply the user's prompt as the input arguments/context for the skill's logic.

4. On Error:

   • If tasks.md is missing: Run /speckit.tasks first
   • If plan.md is missing: Run /speckit.plan first
   • If spec.md is missing: Run /speckit.specify first

OCR-Specific Implementation Considerations

When implementing OCR & AI Extraction prompt management features (ADR-037), handle:

Sidecar Integration

• System Prompt Threading: Append system prompt to messages[0]["content"] in sidecar (typhoon OCR single-message format)
• API Key Authentication: Send X-API-Key: $OCR_SIDECAR_API_KEY header to sidecar endpoints
• Path Remapping: Handle backend → sidecar path mapping (e.g., /app/uploads/temp → /mnt/uploads/temp)
• Error Handling: Implement retry logic for sidecar connection failures

Database Implementation

• SQL Deltas: Apply schema changes via SQL deltas per ADR-009 (no TypeORM migrations)
• Version Column: Verify ai_prompts.version column exists and entity has @VersionColumn()
• Seed Data: Apply delta for default OCR system prompt (INSERT with prompt_type='ocr_system')

Service Implementation

• Optimistic Locking: Modify activate() to accept expectedVersion parameter
• 409 Conflict Handling: Return proper HTTP 409 when version mismatch occurs
• Prompt Validation: Extend create() to support ocr_system (free-form) and ocr_extraction ({{ocr_text}} required)
• Prompt Resolution: Use resolveActive() for template placeholder substitution

BullMQ Integration

• Queue Jobs: Implement handlers for sandbox-ocr, sandbox-extract, sandbox-rag-prep
• Sequential Execution: Wire Step 2 output as Step 3 input
• State Tracking: Store pipeline status in Redis
• Error Recovery: Implement rollback mechanisms for failed pipeline steps

Frontend Implementation

• Service Layer: Create adminAiPromptService with optimistic locking support
• Tab Components: Implement PromptManagementTabs, OcrPromptTab, AiExtractionPromptTab
• Version History: Display version list with activation status
• Validation UI: Show inline errors for missing placeholders
• Vector Preview: Display chunk list with first 5 dimensions
• Step Indicators: Implement 3-step status display (pending/processing/completed/failed)

Testing Implementation

• Unit Tests: Test prompt validation, optimistic locking, version conflict scenarios
• Integration Tests: Test full 3-step pipeline end-to-end
• E2E Tests: Test admin UI workflows (create prompt → activate → run sandbox)

For specialized OCR workflows, use /speckit.ocr-prompt-management instead.