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在 OpenClaw 中安装
/install gh-taskqueue
功能描述
In-memory priority task queue for AI agents. Create tasks with priorities and tags, claim the next highest-priority task, mark tasks complete or failed, filt...
使用说明 (SKILL.md)
TaskQueue
Priority task queue for agent workflows.
Start the server
uvicorn taskqueue.app:app --port 8014
Create a task
curl -s -X POST http://localhost:8014/v1/tasks \
-H "Content-Type: application/json" \
-d '{"title": "Scan skill", "payload": {"skill": "my-skill"}, "priority": 5, "tags": ["security"]}' | jq
Claim the next task (highest priority first)
curl -s -X POST http://localhost:8014/v1/claim | jq
Returns the task with status changed to running.
Complete or fail a task
curl -s -X POST http://localhost:8014/v1/tasks/TASK_ID/complete \
-H "Content-Type: application/json" \
-d '{"result": {"output": "all clear"}}' | jq
curl -s -X POST http://localhost:8014/v1/tasks/TASK_ID/fail \
-H "Content-Type: application/json" \
-d '{"error": "scan timed out"}' | jq
List and filter tasks
curl -s "http://localhost:8014/v1/tasks?status=pending" | jq
curl -s "http://localhost:8014/v1/tasks?tag=security" | jq
Queue stats
curl -s http://localhost:8014/v1/stats | jq
Returns total, pending, running, completed, failed.
Endpoints
| Method | Path | Description |
|---|---|---|
| POST | /v1/tasks | Create a task |
| GET | /v1/tasks | List tasks (filter: ?status=, ?tag=) |
| GET | /v1/tasks/{id} | Get task by ID |
| POST | /v1/claim | Claim next pending task |
| POST | /v1/tasks/{id}/complete | Mark done with result |
| POST | /v1/tasks/{id}/fail | Mark failed with error |
| GET | /v1/stats | Queue statistics |
安全使用建议
This skill appears to do what it says (an in-memory FastAPI-based task queue). Before installing/running it, consider: (1) The HTTP API has no authentication—only run it on localhost or behind a firewall in a trusted environment; do not expose port 8014 to untrusted networks. (2) It is in-memory only: tasks are ephemeral and lost on process restart. (3) Installation uses common PyPI packages—use a virtual environment and pin package versions if you need reproducible/controlled installs. (4) If you will store any secrets in task payloads, avoid doing so because any process that can reach the server can read them. If you need authenticated or persistent behavior, prefer a queue implementation that supports those features.
功能分析
Type: OpenClaw Skill
Name: gh-taskqueue
Version: 1.0.0
The gh-taskqueue skill is a standard FastAPI-based in-memory task management system. The code in taskqueue/app.py and taskqueue/state.py implements basic CRUD operations for tasks with priority and status tracking, using only legitimate dependencies (fastapi, uvicorn, pydantic) and no risky system or network interactions.
能力评估
Purpose & Capability
Name/description (in-memory priority task queue) align with the included files and required binaries. The code implements task creation, claiming, completion/failure, listing, and stats as documented; required binary is only python and declared pip packages (fastapi/uvicorn/pydantic) are consistent with a FastAPI service.
Instruction Scope
SKILL.md simply instructs running uvicorn on port 8014 and using local HTTP curl endpoints, which matches the code. However, there is no authentication/authorization in the API—endpoints are unauthenticated HTTP—so if the server is reachable from other hosts, anyone who can connect can create/claim/modify tasks.
Install Mechanism
Install metadata indicates pip packages fastapi, uvicorn, pydantic (via the 'uv' pip spec). This is a standard package install from PyPI and proportionate to the service; no downloads from arbitrary URLs or archive extracts are present.
Credentials
The skill requests no environment variables, credentials, or config paths. The code does not access environment variables or external secrets, so requested environment access is minimal and proportional.
Persistence & Privilege
The skill does not request elevated system presence (always:false) and does not change other skills or system configs. Note: running the server opens a network port (8014) with no auth; that is a runtime exposure (not a declared privilege) and should be considered when deciding where to run it.
如何使用
- 确保已安装 OpenClaw（本地或 Docker 部署）
- 在对话框中输入安装命令：
/install gh-taskqueue - 安装完成后，直接呼叫该 Skill 的名称或使用
/gh-taskqueue触发 - 根据 Skill 的参数说明提供必要输入，即可获得结构化输出
版本历史
v1.0.0
- Initial release of gh-taskqueue: an in-memory priority task queue for AI agent workflows.
- Supports creating tasks with priorities and tags.
- Allows claiming the highest-priority pending task.
- Tasks can be marked as complete or failed.
- Filter tasks by status or tag and retrieve queue statistics.
- Lightweight API endpoints provided for easy integration.
元数据
常见问题
Taskqueue 是什么？
In-memory priority task queue for AI agents. Create tasks with priorities and tags, claim the next highest-priority task, mark tasks complete or failed, filt... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件，目前累计下载 90 次。
如何安装 Taskqueue？
在 OpenClaw 或 Claude Code 对话框中运行命令「/install gh-taskqueue」即可一键安装，无需额外配置。
Taskqueue 是免费的吗？
是的，Taskqueue 完全免费，采用 MIT-0 许可证，可自由下载、安装和使用。
Taskqueue 支持哪些平台？
Taskqueue 跨平台运行，可在任意部署了 OpenClaw / Claude Code 的环境中使用（cross-platform）。
谁开发了 Taskqueue？
由 mirni（@mirni）开发并维护，当前版本 v1.0.0。
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