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在 OpenClaw 中安装
/install task-decomposer-skill
功能描述
任务拆解技能 - 将需求分解为可执行的最小任务单元。 使用场景：(1) 需求分析时拆解任务 (2) 项目规划时细化工作 (3) 估算工时 (4) 制定迭代计划。 支持技术栈：Java/Spring Boot、Node.js、Python、Go、前端项目。
安全使用建议
This skill is internally coherent and low-risk: it's purely documentation/instruction for breaking requirements into small tasks and does not request secrets or install code. Before installing, consider governance questions: the source/homepage is unknown so verify the publisher/trust if you require an auditable supply chain. When using the skill, avoid pasting sensitive secrets or credentials into prompts (the skill's templates reference service features like login flows but don't need real credentials). If you want extra caution, test the skill in a limited environment or review future versions for added install steps or env requirements.
功能分析
Type: OpenClaw Skill
Name: task-decomposer-skill
Version: 1.0.0
The skill bundle is a pure documentation and configuration set designed to guide an AI agent in decomposing complex requirements into smaller tasks. It contains no executable code, shell commands, or network activity, and the instructions in SKILL.md and decomposition-methods.md are strictly aligned with project management and task estimation goals.
能力评估
Purpose & Capability
The name, description and supported stacks align with the SKILL.md content and templates. All guidance and templates are coherent with a task-decomposition/planning utility and do not ask for unrelated capabilities (e.g., cloud credentials or system-level access).
Instruction Scope
SKILL.md contains only decomposition methodology, templates, examples and configurable options. It does not instruct the agent to read local files, environment variables, or send data to external endpoints beyond producing formatted task lists.
Install Mechanism
No install spec or code files beyond documentation are included (instruction-only). This yields a low on-disk/installation footprint and no downloaded artifacts or executables to analyze.
Credentials
The skill declares no required environment variables, credentials, or config paths. The instructions do not reference secrets or external service tokens, so requested access is proportional to the described purpose.
Persistence & Privilege
Flags show always:false and default autonomous invocation allowed (platform default). The skill does not request permanent presence, nor does it modify other skills or system settings in the provided docs.
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 task-decomposer-skill - 安装完成后，直接呼叫该 Skill 的名称或使用
/task-decomposer-skill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 with major refactor and restructuring:
- Simplified and fully rewritten documentation, with SKILL.md now in Chinese and focused on actionable templates and workflows.
- Removed extended English instructions, universal capability taxonomy, and skill search/generation guidance.
- Added concise task decomposition templates, detailed breakdowns per technical stack (Java/Spring Boot, Node.js, Python, Go, front-end), and ready-to-use markdown output samples.
- Introduced new output formats for task lists, milestone plans, acceptance criteria, time estimation standards, and risk assessment.
- Documentation now emphasizes quick breakdown, planning, estimation, and prioritization for engineering teams.
- Added task configuration options and practical usage examples, streamlining the skill for team/project workflow integration.
元数据
常见问题
task-decomposer-skill 是什么？
任务拆解技能 - 将需求分解为可执行的最小任务单元。 使用场景：(1) 需求分析时拆解任务 (2) 项目规划时细化工作 (3) 估算工时 (4) 制定迭代计划。 支持技术栈：Java/Spring Boot、Node.js、Python、Go、前端项目。 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件，目前累计下载 497 次。
如何安装 task-decomposer-skill？
在 OpenClaw 或 Claude Code 对话框中运行命令「/install task-decomposer-skill」即可一键安装，无需额外配置。
task-decomposer-skill 是免费的吗？
是的，task-decomposer-skill 完全免费，采用 MIT-0 许可证，可自由下载、安装和使用。
task-decomposer-skill 支持哪些平台？
task-decomposer-skill 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 task-decomposer-skill？
由 whisky（@whiskeyforsun）开发并维护，当前版本 v1.0.0。
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