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在 OpenClaw 中安装
/install taskflow3
功能描述
TaskFlow 3.0 - Agent-Native 项目化任务调度系统。 AGENT INSTRUCTIONS: 1. Read PROJECT.yaml from project directory 2. Parse meta/content/target/constraints/workflow 3. E...
安全使用建议
Things to consider before installing/running:
- Backup your workspace/projects before running: the code reads and writes PROJECT.yaml and history files under ~/.openclaw workspaces. edit-project.py uses json.load/json.dump on PROJECT.yaml (a YAML file) and may convert or corrupt YAML configs — inspect and test on copies first.
- Inspect the 'intel' and 'memory' files the scripts reference (e.g., ~/.openclaw/.../intel/*.md, workspace memory) — they may contain sensitive information; the meta-planner explicitly reads these to decide publishing.
- package.json claims CLI sh wrappers that are missing; the advertised 'taskflow' commands in SKILL.md may not exist as-is — expect to run the provided Python scripts directly or validate/implement missing wrappers.
- The code uses different hardcoded workspace paths across files ('.openclaw/workspace', '.openclaw/workspace-zsxq', etc.) and SKILL.md uses OPENCLAW_WORKSPACE or pwd — this inconsistency can cause the skill to read unexpected directories. Confirm which workspace path will be used and test behavior in a sandbox.
- No external credentials are requested by the skill itself, but publishing steps described in prompts assume use of external browser/tools that require credentials; ensure those credentials are provided only to trusted tools and not to this skill implicitly.
- If you proceed: run the scripts in a restricted/sandbox environment, inspect outputs, and correct the JSON/YAML handling and missing bin wrappers before using on real projects.
功能分析
Type: OpenClaw Skill
Name: taskflow3
Version: 3.0.0
TaskFlow 3.0 is an agent-native task scheduling framework designed to manage and automate content publishing workflows. The bundle contains scripts for project configuration management (edit-project.py), status reporting (scheduler.py), and a meta-planner (meta-planner.py) that generates structured prompts to guide the AI agent through multi-step execution tasks. While the system interacts with local workspace directories (~/.openclaw) and directs the agent to use browser tools for delivery to specific platforms (e.g., Knowledge Planet/zsxq), the behavior is transparently documented and strictly aligned with the stated purpose of project-based task orchestration.
能力评估
Purpose & Capability
The declared purpose (agent-native project/task scheduler) aligns with the code and SKILL.md: scripts read PROJECT.yaml, compute scheduling, and record history. However there are several mismatches: package.json advertises CLI sh wrappers (bin/taskflow.sh, bin/scheduler.sh) that are not present; SKILL.md and package.json indicate a Python+pyyaml requirement but some code (edit-project.py and meta-planner.py) use json.load on PROJECT.yaml (which should be YAML), risking corruption of YAML config files. These discrepancies are not consistent with a cleanly implemented scheduler.
Instruction Scope
SKILL.md instructs the agent to read PROJECT.yaml, resolve paths relative to a workspace, execute workflow steps, and update executions.json — all within the expected scope. The meta-planner prompt and scripts explicitly instruct reading many files under the user's home (e.g., ~/.openclaw/.../intel/.p0-alert, vault/*.md, workspace memory files) and to use external 'browser' tools to publish. Reading local workspace and memory is expected for a scheduler, but the prompt encourages accessing potentially sensitive 'intel' vault files — which is within function but worth highlighting.
Install Mechanism
There is no remote install step (instruction-only + included scripts), so no network download risk. The metadata suggests pip install of pyyaml (reasonable for YAML parsing). However, package.json claims Node CLI sh wrappers that don't exist in the repo, which is an implementation inconsistency (users following SKILL.md may expect a provided CLI).
Credentials
The skill requests no environment variables or external credentials, which is proportionate. However the code repeatedly reads files under the user's home directory (Paths like ~/.openclaw/workspace-zsxq, ~/.openclaw/workspace/intel/vault, etc.). Access to those local files is consistent with a project scheduler, but they may contain sensitive data (the 'intel' vault). No external tokens are requested, but the skill expects the agent to use external tools (browser) for publishing, which would require platform credentials not managed by the skill.
Persistence & Privilege
The skill is not always-included and does not request elevated platform privileges. It does not modify other skills or system-wide agent settings. Autonomous invocation is allowed (platform default) but not combined with other high-risk indicators here.
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 taskflow3 - 安装完成后，直接呼叫该 Skill 的名称或使用
/taskflow3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
v3.0.0
Agent-Native project scheduler with CLI support
元数据
常见问题
TaskFlow 3.0 是什么？
TaskFlow 3.0 - Agent-Native 项目化任务调度系统。 AGENT INSTRUCTIONS: 1. Read PROJECT.yaml from project directory 2. Parse meta/content/target/constraints/workflow 3. E... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件，目前累计下载 97 次。
如何安装 TaskFlow 3.0？
在 OpenClaw 或 Claude Code 对话框中运行命令「/install taskflow3」即可一键安装，无需额外配置。
TaskFlow 3.0 是免费的吗？
是的，TaskFlow 3.0 完全免费，采用 MIT-0 许可证，可自由下载、安装和使用。
TaskFlow 3.0 支持哪些平台？
TaskFlow 3.0 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 TaskFlow 3.0？
由 深圳王哥（@manwjh）开发并维护，当前版本 v3.0.0。
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