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Never lose progress mid-task.\n\nTags: checkpoint:1.0.0, latest:1.0.0, productivity:1.0.0, recovery:1.0.0, reliability:1.0.0, workflow:1.0.0\n\nVersion history:\n\nv1.0.0 | 2026-04-20T23:39:45.062Z | user\n\nInitial release: Save and recover from any point in multi-step AI workflows\n\nArchive index:\n\nArchive v1.0.0: 3 files, 2873 bytes\n\nFiles: skill-card.md (1642b), SKILL.md (3647b), _meta.json (138b)\n\nFile v1.0.0:SKILL.md\n\n---\nname: workflow-checkpoint\nversion: 1.0.0\ndescription: Workflow Checkpoint System - Save and recover from any point in multi-step AI workflows. Never lose progress mid-task.\nemoji: 💾\ntags: [workflow, checkpoint, recovery, reliability, productivity]\n---\n\n# Workflow Checkpoint System 💾\n\nSave and recover from any point in multi-step AI workflows. Never lose progress mid-task.\n\n## Why This Matters\n\nAI Agents executing multi-step workflows often fail mid-way:\n- Task 3 of 5 fails → all progress lost\n- Session restarts → must start from scratch\n- Token overflow → workflow interrupted\n- Tool errors → uncertain where we left off\n\nThis skill eliminates that problem with automatic checkpointing.\n\n## How It Works\n\n### Core Protocol\n\n```\nFor every multi-step workflow:\n\n1. PLAN → Write steps to checkpoint file\n2. EXECUTE → After each step, save:\n   - Which step completed\n   - What output was produced\n   - What artifacts were created\n   - Current state/data\n3. VERIFY → Check step result\n4. CHECKPOINT → Update progress file\n5. RECOVER → On failure, resume from last checkpoint\n```\n\n### Checkpoint File Format\n\nSave to `memory/checkpoints/<workflow-name>.json`:\n\n```json\n{\n  \"workflow\": \"deploy-website\",\n  \"startedAt\": \"2026-04-21T07:30:00Z\",\n  \"totalSteps\": 5,\n  \"completedSteps\": [1, 2, 3],\n  \"currentStep\": 4,\n  \"status\": \"in_progress\",\n  \"steps\": {\n    \"1\": {\n      \"name\": \"Clone repository\",\n      \"status\": \"done\",\n      \"output\": \"/tmp/myapp cloned successfully\",\n      \"timestamp\": \"2026-04-21T07:31:00Z\"\n    },\n    \"2\": {\n      \"name\": \"Install dependencies\",\n      \"status\": \"done\",\n      \"output\": \"npm install completed\",\n      \"timestamp\": \"2026-04-21T07:33:00Z\"\n    },\n    \"3\": {\n      \"name\": \"Build project\",\n      \"status\": \"done\",\n      \"output\": \"build/ directory created\",\n      \"timestamp\": \"2026-04-21T07:35:00Z\"\n    },\n    \"4\": {\n      \"name\": \"Deploy to server\",\n      \"status\": \"failed\",\n      \"error\": \"Connection timeout\",\n      \"timestamp\": \"2026-04-21T07:38:00Z\"\n    },\n    \"5\": {\n      \"name\": \"Verify deployment\",\n      \"status\": \"pending\"\n    }\n  },\n  \"artifacts\": [\"/tmp/myapp/build/\", \"/tmp/myapp/config/\"],\n  \"lastCheckpoint\": \"2026-04-21T07:38:00Z\"\n}\n```\n\n### Recovery Protocol\n\nWhen resuming a failed workflow:\n\n1. Read checkpoint file\n2. Identify last completed step\n3. Skip completed steps (verify artifacts still exist)\n4. Resume from failed/pending step\n5. Update checkpoint\n\n### Usage Examples\n\n#### Before a complex task:\n```\nI'm about to execute a 5-step workflow: deploy-website.\nSteps: 1) Clone repo 2) Install deps 3) Build 4) Deploy 5) Verify\nSaving checkpoint to memory/checkpoints/deploy-website.json\n```\n\n#### After each step:\n```\nStep 2/5 complete: Install dependencies\nOutput: npm install completed, 142 packages\nCheckpoint updated: completedSteps [1,2]\n```\n\n#### On failure:\n```\nStep 4/5 FAILED: Deploy to server\nError: Connection timeout to 192.168.1.100:22\nCheckpoint saved. Can resume from step 4.\nRetrying... (attempt 1/3)\n```\n\n#### On recovery:\n```\nResuming workflow: deploy-website\nLast checkpoint: Step 3 completed at 07:35\nSkipping steps 1-3 (verified artifacts exist)\nResuming from step 4: Deploy to server\n```\n\n## Integration with Other Skills\n\nWorks great with:\n- **EVR** - Verify each step before checkpointing\n- **Error Recovery** - Auto-retry failed steps from checkpoint\n- **Memory Guard** - Checkpoints persist across sessions\n\n## Anti-Patterns\n\n❌ Don't save checkpoints for single-step tasks\n❌ Don't save sensitive data in checkpoint files\n❌ Don't skip verification when resuming\n❌ Don't forget to clean up old checkpoints\n\n## License\n\nMIT\n\nFile v1.0.0:_meta.json\n\n{\n  \"ownerId\": \"kn74w4pv5ms0vhet3bstvw95a5833msw\",\n  \"slug\": \"workflow-checkpoint\",\n  \"version\": \"1.0.0\",\n  \"publishedAt\": 1776728385062\n}\n\nFile v1.0.0:skill-card.md\n\n## Description:\n\nWorkflow Checkpoint helps agents save progress and recover from any point in multi-step AI workflows.\n\nThis skill is ready for commercial/non-commercial use.\n\n## Publisher:\n\n[aptratcn](https://clawhub.ai/user/aptratcn)\n\n### License/Terms of Use:\n\nMIT-0\n\n## Use Case:\n\nDevelopers and agent operators use this skill to checkpoint multi-step AI workflows, record progress and artifacts, and resume from the last verified step after failures or interruptions.\n\n### Deployment Geography for Use:\n\nGlobal\n\n## Known Risks and Mitigations:\n\nRisk: Checkpoint files may persist secrets, credentials, private customer data, sensitive outputs, or internal host details.\n\nMitigation: Do not checkpoint sensitive data, and periodically delete old files under memory/checkpoints.\n\nRisk: A resumed workflow may rely on stale or missing artifacts from earlier steps.\n\nMitigation: Verify saved artifacts still exist before skipping completed steps during recovery.\n\n## Reference(s):\n\n\n## Skill Output:\n\n**Output Type(s):** [text, markdown, configuration, guidance]\n\n**Output Format:** [Markdown guidance with JSON checkpoint file examples]\n\n**Output Parameters:** [1D]\n\n**Other Properties Related to Output:** [Produces local checkpoint records under memory/checkpoints when applied by an agent.]\n\n## Skill Version(s):\n\n1.0.0 (source: server release and SKILL.md frontmatter)\n\n## Ethical Considerations:\n\nUsers should evaluate whether this skill is appropriate for their environment, review any generated or modified files before relying on them, and apply their organization's safety, security, and compliance requirements before deployment.","readmeExcerpt":"Skill: Workflow Checkpoint Owner: aptratcn Summary: Workflow Checkpoint System - Save and recover from any point in multi-step AI workflows. Never lose progress mid-task. Tags: checkpoint:1.0.0, latest:1.0.0, productivity:1.0.0, recovery:1.0.0, reliability:1.0.0, workflow:1.0.0 Version history: v1.0.0 | 2026-04-20T23:39:45.062Z | user Initial release: Save and recover from any point in multi-step AI workflows Archive","codeSnippets":[],"executableExamples":[{"language":"text","snippet":"For every multi-step workflow:\n\n1. PLAN → Write steps to checkpoint file\n2. EXECUTE → After each step, save:\n   - Which step completed\n   - What output was produced\n   - What artifacts were created\n   - Current state/data\n3. VERIFY → Check step result\n4. CHECKPOINT → Update progress file\n5. RECOVER → On failure, resume from last checkpoint"},{"language":"json","snippet":"{\n  \"workflow\": \"deploy-website\",\n  \"startedAt\": \"2026-04-21T07:30:00Z\",\n  \"totalSteps\": 5,\n  \"completedSteps\": [1, 2, 3],\n  \"currentStep\": 4,\n  \"status\": \"in_progress\",\n  \"steps\": {\n    \"1\": {\n      \"name\": \"Clone repository\",\n      \"status\": \"done\",\n      \"output\": \"/tmp/myapp cloned successfully\",\n      \"timestamp\": \"2026-04-21T07:31:00Z\"\n    },\n    \"2\": {\n      \"name\": \"Install dependencies\",\n      \"status\": \"done\",\n      \"output\": \"npm install completed\",\n      \"timestamp\": \"2026-04-21T07:33:00Z\"\n    },\n    \"3\": {\n      \"name\": \"Build project\",\n      \"status\": \"done\",\n      \"output\": \"build/ directory created\",\n      \"timestamp\": \"2026-04-21T07:35:00Z\"\n    },\n    \"4\": {\n      \"name\": \"Deploy to server\",\n      \"status\": \"failed\",\n      \"error\": \"Connection timeout\",\n      \"timestamp\": \"2026-04-21T07:38:00Z\"\n    },\n    \"5\": {\n      \"name\": \"Verify deployment\",\n      \"status\": \"pending\"\n    }\n  },\n  \"artifacts\": [\"/tmp/myapp/build/\", \"/tmp/myapp/config/\"],\n  \"lastCheckpoint\": \"2026-04-21T07:38:00Z\"\n}"},{"language":"text","snippet":"I'm about to execute a 5-step workflow: deploy-website.\nSteps: 1) Clone repo 2) Install deps 3) Build 4) Deploy 5) Verify\nSaving checkpoint to memory/checkpoints/deploy-website.json"},{"language":"text","snippet":"Step 2/5 complete: Install dependencies\nOutput: npm install completed, 142 packages\nCheckpoint updated: completedSteps [1,2]"},{"language":"text","snippet":"Step 4/5 FAILED: Deploy to server\nError: Connection timeout to 192.168.1.100:22\nCheckpoint saved. Can resume from step 4.\nRetrying... (attempt 1/3)"},{"language":"text","snippet":"Resuming workflow: deploy-website\nLast checkpoint: Step 3 completed at 07:35\nSkipping steps 1-3 (verified artifacts exist)\nResuming from step 4: Deploy to server"}],"parameters":null,"dependencies":[],"permissions":[],"extractedFiles":[{"path":"SKILL.md","content":"---\nname: workflow-checkpoint\nversion: 1.0.0\ndescription: Workflow Checkpoint System - Save and recover from any point in multi-step AI workflows. Never lose progress mid-task.\nemoji: 💾\ntags: [workflow, checkpoint, recovery, reliability, productivity]\n---\n\n# Workflow Checkpoint System 💾\n\nSave and recover from any point in multi-step AI workflows. Never lose progress mid-task.\n\n## Why This Matters\n\nAI Agents executing multi-step workflows often fail mid-way:\n- Task 3 of 5 fails → all progress lost\n- Session restarts → must start from scratch\n- Token overflow → workflow interrupted\n- Tool errors → uncertain where we left off\n\nThis skill eliminates that problem with automatic checkpointing.\n\n## How It Works\n\n### Core Protocol\n\n```\nFor every multi-step workflow:\n\n1. PLAN → Write steps to checkpoint file\n2. EXECUTE → After each step, save:\n   - Which step completed\n   - What output was produced\n   - What artifacts were created\n   - Current state/data\n3. VERIFY → Check step result\n4. CHECKPOINT → Update progress file\n5. RECOVER → On failure, resume from last checkpoint\n```\n\n### Checkpoint File Format\n\nSave to `memory/checkpoints/<workflow-name>.json`:\n\n```json\n{\n  \"workflow\": \"deploy-website\",\n  \"startedAt\": \"2026-04-21T07:30:00Z\",\n  \"totalSteps\": 5,\n  \"completedSteps\": [1, 2, 3],\n  \"currentStep\": 4,\n  \"status\": \"in_progress\",\n  \"steps\": {\n    \"1\": {\n      \"name\": \"Clone repository\",\n      \"status\": \"done\",\n      \"output\": \"/tmp/myapp cloned successfully\",\n      \"timestamp\": \"2026-04-21T07:31:00Z\"\n    },\n    \"2\": {\n      \"name\": \"Install dependencies\",\n      \"status\": \"done\",\n      \"output\": \"npm install completed\",\n      \"timestamp\": \"2026-04-21T07:33:00Z\"\n    },\n    \"3\": {\n      \"name\": \"Build project\",\n      \"status\": \"done\",\n      \"output\": \"build/ directory created\",\n      \"timestamp\": \"2026-04-21T07:35:00Z\"\n    },\n    \"4\": {\n      \"name\": \"Deploy to server\",\n      \"status\": \"failed\",\n      \"error\": \"Connection timeout\",\n      \"timestamp\": \"2026-04-21T07:38:00Z\"\n    },\n    \"5\": {\n      \"name\": \"Verify deployment\",\n      \"status\": \"pending\"\n    }\n  },\n  \"artifacts\": [\"/tmp/myapp/build/\", \"/tmp/myapp/config/\"],\n  \"lastCheckpoint\": \"2026-04-21T07:38:00Z\"\n}\n```\n\n### Recovery Protocol\n\nWhen resuming a failed workflow:\n\n1. Read checkpoint file\n2. Identify last completed step\n3. Skip completed steps (verify artifacts still exist)\n4. Resume from failed/pending step\n5. Update checkpoint\n\n### Usage Examples\n\n#### Before a complex task:\n```\nI'm about to execute a 5-step workflow: deploy-website.\nSteps: 1) Clone repo 2) Install deps 3) Build 4) Deploy 5) Verify\nSaving checkpoint to memory/checkpoints/deploy-website.json\n```\n\n#### After each step:\n```\nStep 2/5 complete: Install dependencies\nOutput: npm install completed, 142 packages\nCheckpoint updated: completedSteps [1,2]\n```\n\n#### On failure:\n```\nStep 4/5 FAILED: Deploy to server\nError: Connection timeout to 192.168.1.100:22\nCheckpoint saved. Can resume from step 4.\nRetrying... (attempt 1/3)\n```\n\n#### On "},{"path":"_meta.json","content":"{\n  \"ownerId\": \"kn74w4pv5ms0vhet3bstvw95a5833msw\",\n  \"slug\": \"workflow-checkpoint\",\n  \"version\": \"1.0.0\",\n  \"publishedAt\": 1776728385062\n}"},{"path":"skill-card.md","content":"## Description:\n\nWorkflow Checkpoint helps agents save progress and recover from any point in multi-step AI workflows.\n\nThis skill is ready for commercial/non-commercial use.\n\n## Publisher:\n\n[aptratcn](https://clawhub.ai/user/aptratcn)\n\n### License/Terms of Use:\n\nMIT-0\n\n## Use Case:\n\nDevelopers and agent operators use this skill to checkpoint multi-step AI workflows, record progress and artifacts, and resume from the last verified step after failures or interruptions.\n\n### Deployment Geography for Use:\n\nGlobal\n\n## Known Risks and Mitigations:\n\nRisk: Checkpoint files may persist secrets, credentials, private customer data, sensitive outputs, or internal host details.\n\nMitigation: Do not checkpoint sensitive data, and periodically delete old files under memory/checkpoints.\n\nRisk: A resumed workflow may rely on stale or missing artifacts from earlier steps.\n\nMitigation: Verify saved artifacts still exist before skipping completed steps during recovery.\n\n## Reference(s):\n\n\n## Skill Output:\n\n**Output Type(s):** [text, markdown, configuration, guidance]\n\n**Output Format:** [Markdown guidance with JSON checkpoint file examples]\n\n**Output Parameters:** [1D]\n\n**Other Properties Related to Output:** [Produces local checkpoint records under memory/checkpoints when applied by an agent.]\n\n## Skill Version(s):\n\n1.0.0 (source: server release and SKILL.md frontmatter)\n\n## Ethical Considerations:\n\nUsers should evaluate whether this skill is appropriate for their environment, review any generated or modified files before relying on them, and apply their organization's safety, security, and compliance requirements before deployment."}],"languages":[],"docsSourceLabel":"CLAWHUB","editorialOverview":"Workflow Checkpoint System - Save and recover from any point in multi-step AI workflows. 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