Skill: aptratcn/workflow-checkpoint (version 1.0.0)

--- name: workflow-checkpoint version: 1.0.0 description: Workflow Checkpoint System - Save and recover from any point in multi-step AI workflows. Never lose progress mid-task. emoji: 💾 tags: [workflow, checkpoint, recovery, reliability, productivity] --- # Workflow Checkpoint System 💾 Save and recover from any point in multi-step AI workflows. Never lose progress mid-task. ## Why This Matters AI Agents executing multi-step workflows often fail mid-way: - Task 3 of 5 fails → all progress lost - Session restarts → must start from scratch - Token overflow → workflow interrupted - Tool errors → uncertain where we left off This skill eliminates that problem with automatic checkpointing. ## How It Works ### Core Protocol ``` For every multi-step workflow: 1. PLAN → Write steps to checkpoint file 2. EXECUTE → After each step, save: - Which step completed - What output was produced - What artifacts were created - Current state/data 3. VERIFY → Check step result 4. CHECKPOINT → Update progress file 5. RECOVER → On failure, resume from last checkpoint ``` ### Checkpoint File Format Save to `memory/checkpoints/<workflow-name>.json`: ```json { "workflow": "deploy-website", "startedAt": "2026-04-21T07:30:00Z", "totalSteps": 5, "completedSteps": [1, 2, 3], "currentStep": 4, "status": "in_progress", "steps": { "1": { "name": "Clone repository", "status": "done", "output": "/tmp/myapp cloned successfully", "timestamp": "2026-04-21T07:31:00Z" }, "2": { "name": "Install dependencies", "status": "done", "output": "npm install completed", "timestamp": "2026-04-21T07:33:00Z" }, "3": { "name": "Build project", "status": "done", "output": "build/ directory created", "timestamp": "2026-04-21T07:35:00Z" }, "4": { "name": "Deploy to server", "status": "failed", "error": "Connection timeout", "timestamp": "2026-04-21T07:38:00Z" }, "5": { "name": "Verify deployment", "status": "pending" } }, "artifacts": ["/tmp/myapp/build/", "/tmp/myapp/config/"], "lastCheckpoint": "2026-04-21T07:38:00Z" } ``` ### Recovery Protocol When resuming a failed workflow: 1. Read checkpoint file 2. Identify last completed step 3. Skip completed steps (verify artifacts still exist) 4. Resume from failed/pending step 5. Update checkpoint ### Usage Examples #### Before a complex task: ``` I'm about to execute a 5-step workflow: deploy-website. Steps: 1) Clone repo 2) Install deps 3) Build 4) Deploy 5) Verify Saving checkpoint to memory/checkpoints/deploy-website.json ``` #### After each step: ``` Step 2/5 complete: Install dependencies Output: npm install completed, 142 packages Checkpoint updated: completedSteps [1,2] ``` #### On failure: ``` Step 4/5 FAILED: Deploy to server Error: Connection timeout to 192.168.1.100:22 Checkpoint saved. Can resume from step 4. Retrying... (attempt 1/3) ``` #### On recovery: ``` Resuming workflow: deploy-website Last checkpoint: Step 3 completed at 07:35 Skipping steps 1-3 (verified artifacts exist) Resuming from step 4: Deploy to server ``` ## Integration with Other Skills Works great with: - **EVR** - Verify each step before checkpointing - **Error Recovery** - Auto-retry failed steps from checkpoint - **Memory Guard** - Checkpoints persist across sessions ## Anti-Patterns ❌ Don't save checkpoints for single-step tasks ❌ Don't save sensitive data in checkpoint files ❌ Don't skip verification when resuming ❌ Don't forget to clean up old checkpoints ## License MIT


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)