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How to add a durable task ledger with resume instructions with Agent Workflow Platform

Track tasks, heartbeats, and checkpoints in a file-backed ledger that a new session can resume from.

Short answer: Clone the repository with git clone https://github.com/primorLee/agent-workflow-platform.git and enter it with cd agent-workflow-platform; then add a task with python workflows/runtime/scheduler.py add "Create a deterministic smoke test" 2 --group reliability; Record progress with python workflows/runtime/scheduler.py heartbeat. All steps.

Authorization notice. Agent Workflow Platform is dual-use. Only use it on software, sites and systems you own or have explicit permission to test.

Who it is forA developer or agent running long multi-step work in a repository who loses progress when a chat or process stops.

The problemWork stopped mid-task has no durable record, so the next session must rebuild context from memory.

The outcomeA ledger in the ignored .agent-workflow/ directory holds the task, its checkpoint, and a rebuilt resume instruction that a new session can follow.

What you need first

  • Docker Engine or Docker Desktop with Compose, and Python 3.12, for the local round trip
  • Node.js 22.12 or newer, for the desktop workbench
  • A compatible Agent CLI or model endpoint, such as a local Ollama-compatible endpoint, for real model responses
  • Python 3.10 or newer, for the standalone workflow runtime

Steps

  1. Clone the repository with git clone https://github.com/primorLee/agent-workflow-platform.git and enter it with cd agent-workflow-platform.
  2. Add a task with python workflows/runtime/scheduler.py add "Create a deterministic smoke test" 2 --group reliability.
  3. Record progress with python workflows/runtime/scheduler.py heartbeat.
  4. Save a checkpoint with python workflows/runtime/scheduler.py checkpoint "Run the regression and attach its output".
  5. Stop the process, then in a new terminal or agent session run python workflows/runtime/guardian.py resume.

Prompt for your agent

In the agent-workflow-platform repository, add a task to the scheduler, send a heartbeat, and save a checkpoint with the status of <your-task>. Then run guardian.py resume in a new session and report the rebuilt resume instruction, confirming it comes from the durable state under .agent-workflow/.

Caveat. The README says the scheduler does not spawn Agents or execute tasks, and Guardian does not restart a process, so you must run the work yourself and only use the ledger to record and resume it.

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