A durable queue-task helper designed for resumable and idempotent batch processing in task-father environments.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install queue-task
2. Manual Installation
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
3. Prompt Installation
Copy this prompt to OpenClaw to install it automatically.
Help me install queue-task using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Prefer to download?
Get the raw skill files in a ZIP archive.
What is queue-task?
The queue-task skill is a specialized utility designed to handle long-running, asynchronous operations within the Openclaw Skills framework. It addresses the common challenge of maintaining state across distributed or interrupted workflows by providing a structured, file-based queue system. By leveraging the task-father directory layout, it enables developers to build automation that is both reliable and scalable.
At its core, this skill focuses on durability and idempotency. It uses append-only logs to ensure that no data is lost during processing and utilizes lock files to prevent race conditions during concurrent executions. Whether you are processing large datasets or managing multi-step agent workflows, queue-task provides the necessary scaffolding to keep your jobs organized and resumable.
queue-task Use Cases
- Processing high-volume data batches that require resumable state tracking.
- Orchestrating long-running AI agent tasks that may span multiple sessions.
- Implementing idempotent workflows where tasks must not be duplicated upon retry.
- Scheduling recurring maintenance or synchronization jobs via cron integrations within Openclaw Skills.
How queue-task Works
- The user provides a task slug and configuration parameters like batch size and schedule.
- The system initializes a dedicated task directory containing state files (queue, progress, done, failed, and lock).
- Tasks are appended to the queue.jsonl file for sequential or batch processing.
- During execution, the skill checks for an active lock file to ensure mutual exclusion.
- As items are processed, progress.json is updated, and results are moved to done.jsonl or failed.jsonl.
- If a process is interrupted, the skill uses the progress file to resume exactly where it left off.
queue-task Setup
To get started with queue-task in your Openclaw Skills environment, follow these steps:
- Initialize the task structure for your specific slug:
python3 scripts/queue_task.py init <slug>
- (Optional) Manually configure your environment if not using the chat-first initialization:
cp config.env.example config.env
# Edit config.env with your WORKSPACE_DIR and BATCH_SIZE
- Verify the installation and state:
python3 scripts/queue_task.py status <slug>
queue-task Data Schema & Taxonomy
The skill organizes its state using a flat-file database approach within the tasks directory. This ensures portability and transparency across different Openclaw Skills implementations:
| File | Format | Purpose |
|---|---|---|
queue.jsonl |
JSONL | Stores the list of pending tasks to be processed. |
progress.json |
JSON | Tracks the current offset and metadata of the active batch. |
done.jsonl |
JSONL | A permanent log of successfully completed tasks. |
failed.jsonl |
JSONL | Captures task data and error details for failed items. |
lock.json |
JSON | Prevents concurrent execution and stores process PIDs. |
queue-task Advanced Features
- Support for stale lock detection and manual clearing to ensure high availability.
- Generation of supervisor worker templates for process monitoring and automatic restarts.
- Native compatibility with Openclaw Skills cron expressions for automated scheduling.
- Portable configuration through environment variables (config.env) for seamless deployment across machines.
- Append-only JSONL logging for high-performance write operations and auditability.
SKILL.md
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