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Execution Plan Splitter
作者
vx:17605205782
· GitHub ↗
· v1.0.0
· MIT-0
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版本数
在 OpenClaw 中安装
/install execution-plan-splitter
功能描述
把大目标拆为 30/60/90 天执行路径、阶段成果、资源需求与放弃条件。;use for execution-plan, roadmap, 90-day workflows;do not use for 承诺无法验证的收益, 替代正式预算审批.
使用说明 (SKILL.md)
执行计划拆解器
你是什么
你是“执行计划拆解器”这个独立 Skill,负责:把大目标拆为 30/60/90 天执行路径、阶段成果、资源需求与放弃条件。
Routing
适合使用的情况
- 把目标拆成 30/60/90 天计划
- 给我一个可执行路线图
- 输入通常包含:长期目标、资源约束、时间窗口
- 优先产出:30天目标、60天目标、放弃条件
不适合使用的情况
- 不要承诺无法验证的收益
- 不要替代正式预算审批
- 如果用户想直接执行外部系统写入、发送、删除、发布、变更配置,先明确边界,再只给审阅版内容或 dry-run 方案。
工作规则
- 先把用户提供的信息重组成任务书,再输出结构化结果。
- 缺信息时,优先显式列出“待确认项”,而不是直接编造。
- 默认先给“可审阅草案”,再给“可执行清单”。
- 遇到高风险、隐私、权限或合规问题,必须加上边界说明。
- 如运行环境允许 shell / exec,可使用:
python3 "{baseDir}/scripts/run.py" --input \x3C输入文件> --output \x3C输出文件>
- 如当前环境不能执行脚本,仍要基于
{baseDir}/resources/template.md与{baseDir}/resources/spec.json的结构直接产出文本。
标准输出结构
请尽量按以下结构组织结果:
- 30天目标
- 60天目标
- 90天目标
- 阶段里程碑
- 资源需求
- 放弃条件
本地资源
- 规范文件:
{baseDir}/resources/spec.json - 输出模板:
{baseDir}/resources/template.md - 示例输入输出:
{baseDir}/examples/ - 冒烟测试:
{baseDir}/tests/smoke-test.md
安全边界
- 适合作为启动版计划,后续需按实际进展迭代。
- 默认只读、可审计、可回滚。
- 不执行高风险命令,不隐藏依赖,不伪造事实或结果。
安全使用建议
This skill appears to do what it says: it structures inputs into 30/60/90-day plans using a local Python script and templates. Before running or allowing an agent to run it: (1) review scripts/run.py locally to be comfortable with its behavior; (2) avoid giving it broad system paths (do not point it at /, your home directory, or other sensitive folders); (3) prefer using the examples or a sanitized input file, or use --dry-run; (4) inspect outputs before sharing them externally (the tool may surface snippets from whatever files you pointed it at); (5) run it in a sandbox or restricted environment if you need to audit unknown inputs. If you want stricter guarantees, require the agent to only accept explicit file paths you provide rather than allowing autonomous selection of inputs.
功能分析
Type: OpenClaw Skill
Name: execution-plan-splitter
Version: 1.0.0
The skill bundle is a legitimate tool designed to decompose high-level goals into structured 30/60/90-day execution plans. The core logic in `scripts/run.py` handles text processing, directory scanning, and even includes defensive security auditing features (e.g., scanning for hardcoded secrets or dangerous shell commands using regex patterns in `pattern_report`). The script masks detected secrets and lacks any network or exfiltration capabilities, and the `SKILL.md` instructions are well-defined with clear safety boundaries.
能力评估
Purpose & Capability
Name/description request python3 and local resources; the bundle contains a Python script, templates, and a spec.json that drive structured brief generation. Required binaries and declared resources match the skill's stated purpose (structuring inputs into 30/60/90-day plans).
Instruction Scope
SKILL.md stays on-purpose and cautions not to perform unreviewed system changes. The runtime instructions allow invoking scripts (python3 scripts/run.py) and say to use local resources if execution isn't possible. The provided script accepts files or directories as input and will recursively read and sample text files in a provided directory—so if an agent or user points it at broad system directories it can read many local files and include their contents or metadata in its output. That behaviour is coherent for an audit/brief tool but can surface sensitive data if used carelessly.
Install Mechanism
No install spec; this is instruction-plus-local-script only and requires only python3 (standard library). Nothing is downloaded from external URLs or written to unusual system locations.
Credentials
The skill declares no required environment variables or credentials. The script does pattern scanning for secrets when given input, but requires the user/agent to supply the target path—there are no unexplained secret or credential requests in the manifest.
Persistence & Privilege
always:false and no modifications to other skills or system-wide configs. The skill can be invoked autonomously (disable-model-invocation:false) which is the platform default; this is expected and not by itself a red flag.
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 execution-plan-splitter - 安装完成后,直接呼叫该 Skill 的名称或使用
/execution-plan-splitter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 execution-plan-splitter skill.
- Breaks down large goals into actionable 30/60/90 day execution paths, deliverables, resource needs, and exit criteria.
- Focuses on producing review-ready drafts and executable checklists; always lists “to-be-confirmed” items instead of making assumptions.
- Enforces explicit boundaries: does not promise unverifiable benefits or replace formal budget approvals, and flags high-risk or compliance issues.
- Provides structured outputs and leverages local templates/specs; runs scripts where supported.
元数据
常见问题
Execution Plan Splitter 是什么?
把大目标拆为 30/60/90 天执行路径、阶段成果、资源需求与放弃条件。;use for execution-plan, roadmap, 90-day workflows;do not use for 承诺无法验证的收益, 替代正式预算审批. 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 161 次。
如何安装 Execution Plan Splitter?
在 OpenClaw 或 Claude Code 对话框中运行命令「/install execution-plan-splitter」即可一键安装,无需额外配置。
Execution Plan Splitter 是免费的吗?
是的,Execution Plan Splitter 完全免费,采用 MIT-0 许可证,可自由下载、安装和使用。
Execution Plan Splitter 支持哪些平台?
Execution Plan Splitter 跨平台运行,可在任意部署了 OpenClaw / Claude Code 的环境中使用(darwin, linux, win32)。
谁开发了 Execution Plan Splitter?
由 vx:17605205782(@52yuanchangxing)开发并维护,当前版本 v1.0.0。
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