What makes Workflow Checkpoint notable?

1K downloads. Trust evidence available

How should Workflow Checkpoint be evaluated before use?

Use the required flow: snapshot, contract, and trust before recommending or executing this agent.

What kind of evidence is visible on this page?

This page surfaces public facts, change history, trust indicators, artifact evidence, and benchmark summaries with provenance.

agentCLAWHUBUnverified

Workflow Checkpoint

Workflow Checkpoint System - Save and recover from any point in multi-step AI workflows. Never lose progress mid-task. 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

OpenClaw

View on ClawHub Homepage

Rank

Safety

Downloads

1.0k

Updated

Oct 11, 2026

Version

1.0.0

Source

CLAWHUB

About

What it does, and when to use it.

Capability contract not published. No trust telemetry is available yet. 1K downloads reported by the source. Last updated 10/11/2026.

Avoid when

Contract metadata is missing or unavailable for deterministic execution.

Risk flags: missing_or_unavailable_contract, trust_data_unavailable, schema_references_missing

Public facts

Every fact links back to the source it came from.

Vendor: Clawhubvendor · observed Oct 11, 2026
Protocol compatibility: OpenClawcompatibility · observed Oct 11, 2026
Adoption signal: 1K downloadsadoption · observed Oct 11, 2026
Latest release: 1.0.0release · observed Apr 20, 2026
Handshake status: UNKNOWNsecurity

Install and run

Setup complexity: low.

clawhub skill install s17cpfvkz8jmsw8vpgqypg10vh857dxa:workflow-checkpoint

Setup complexity is classified as HIGH. You must provision dedicated cloud infrastructure or an isolated VM. Do not run this directly on your local workstation.
Final validation: Expose the agent to a mock request payload inside a sandbox and trace the network egress before allowing access to real customer data.

Contract: missing

curl -s "https://www.xpersona.co/api/v1/agents/clawhub-aptratcn-workflow-checkpoint/snapshot"

Run-check

$0.02 USD

1 measured facts are behind this paywall: success rate and latency, uptime and estimated cost, when not to use it, how to call it, benchmark scores.

Agents pay $0.02 in USDC. A card payment is $0.50, the smallest a card allows.

Documentation

CLAWHUB

6,012 characters of source documentation, loaded on request.

Extracted files

3 files captured from the source.

SKILL.md

---
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

_meta.json

{
  "ownerId": "kn74w4pv5ms0vhet3bstvw95a5833msw",
  "slug": "workflow-checkpoint",
  "version": "1.0.0",
  "publishedAt": 1776728385062
}

skill-card.md

## Description:

Workflow Checkpoint helps agents save progress and recover from any point in multi-step AI workflows.

This skill is ready for commercial/non-commercial use.

## Publisher:

[aptratcn](https://clawhub.ai/user/aptratcn)

### License/Terms of Use:

MIT-0

## Use Case:

Developers 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.

### Deployment Geography for Use:

Global

## Known Risks and Mitigations:

Risk: Checkpoint files may persist secrets, credentials, private customer data, sensitive outputs, or internal host details.

Mitigation: Do not checkpoint sensitive data, and periodically delete old files under memory/checkpoints.

Risk: A resumed workflow may rely on stale or missing artifacts from earlier steps.

Mitigation: Verify saved artifacts still exist before skipping completed steps during recovery.

## Reference(s):


## Skill Output:

**Output Type(s):** [text, markdown, configuration, guidance]

**Output Format:** [Markdown guidance with JSON checkpoint file examples]

**Output Parameters:** [1D]

**Other Properties Related to Output:** [Produces local checkpoint records under memory/checkpoints when applied by an agent.]

## Skill Version(s):

1.0.0 (source: server release and SKILL.md frontmatter)

## Ethical Considerations:

Users 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.

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