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Decision Ledger
by
vx:17605205782
· GitHub ↗
· v1.0.0
· MIT-0
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Install in OpenClaw
/install decision-ledger
Description
从纪要、聊天或项目材料中提取决策、负责人、截止时间、前提假设与撤销条件。;use for decision, meeting, governance workflows;do not use for 编造不存在的决策, 替代法律审计.
README (SKILL.md)
决策台账整理器
你是什么
你是“决策台账整理器”这个独立 Skill,负责:从纪要、聊天或项目材料中提取决策、负责人、截止时间、前提假设与撤销条件。
Routing
适合使用的情况
- 把本周项目会议记录整理成决策台账
- 从纪要中抽取负责人和截止日期
- 输入通常包含:会议纪要、聊天记录、文档摘录
- 优先产出:已确认决策、待确认事项、后续依赖
不适合使用的情况
- 不要用来编造不存在的决策
- 不要用来替代法律审计
- 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:
- 已确认决策
- 待确认事项
- 负责人和截止日
- 前提假设
- 推翻条件
- 后续依赖
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
- 只整理显式信息,隐含判断会被标注为推断。
- 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。
Usage Guidance
This skill appears to be what it says: a local, read-only (by default) tool to extract and structure decisions. Before installing or running:
- Review scripts/run.py (already included) — it only uses the Python standard library and does not make network calls or run shell pipes.
- When running, prefer --dry-run first and avoid pointing the script at system or repository roots that may contain secrets (e.g., /, ~/.ssh, CI config dirs). The script will read many file types and could surface sensitive lines if you feed it a directory with credentials.
- If you plan to let the agent invoke the skill autonomously, be deliberate about allowed inputs (restrict directories/files) so it cannot be asked to scan unexpected local paths.
- Run the provided smoke test locally to confirm behavior (python3 scripts/run.py --input examples/example-input.md --output out.md) and inspect outputs before using on sensitive data.
Capability Analysis
Type: OpenClaw Skill
Name: decision-ledger
Version: 1.0.0
The 'decision-ledger' skill bundle is a legitimate utility designed to extract and organize decisions, owners, and deadlines from meeting notes and project materials. The core logic in scripts/run.py is a versatile reporting tool that supports structured data extraction, directory auditing, and security pattern scanning (e.g., detecting hardcoded secrets or dangerous commands), which aligns with the stated 'governance' and 'audit' use cases. The script follows safe practices by masking detected secrets in its output and lacks any indicators of data exfiltration, unauthorized execution, or malicious intent.
Capability Assessment
Purpose & Capability
Name/description match the provided resources and the included script. Requesting python3 is proportionate. The shipped script supports several audit modes (directory, CSV, pattern, skill audit) in addition to structured brief extraction — this is reasonable for a general-purpose 'ledger/audit' helper but slightly broader than only processing meeting notes (it can scan code and repo files).
Instruction Scope
SKILL.md confines behavior to reading provided inputs and producing structured output or running the local script. It explicitly warns against executing high-risk actions. The runtime instructions ask to run the bundled script or to produce output from bundled templates if execution isn't possible; nothing in SKILL.md instructs the agent to exfiltrate data or access unrelated system resources.
Install Mechanism
No install spec (instruction-only) and no external downloads; the only runtime requirement is python3. This is low-risk — nothing is written to disk by an installer beyond the repo contents already present.
Credentials
No environment variables or external credentials are requested. However, the script will read arbitrary files under any input directory you provide (it considers many extensions including .py/.sh/.env-like files), so if you instruct the agent to scan a system or repo directory it can read potentially sensitive local files. That capability is functional for audit use-cases but worth awareness.
Persistence & Privilege
Skill is not 'always' enabled and does not request elevated or persistent privileges. It does not modify other skills or global agent configuration. The agent can invoke it autonomously by default (normal platform behavior) but there is no indication of increased privilege or self-enablement.
How to Use
- Make sure OpenClaw is installed (local or Docker)
- Run the install command in chat:
/install decision-ledger - After installation, invoke the skill by name or use
/decision-ledger - Provide required inputs per the skill's parameter spec and get structured output
Version History
v1.0.0
decision-ledger 1.0.0 初始发布
- 新增从会议纪要、聊天或项目材料中自动提取决策、负责人、截止时间、前提假设与撤销条件的能力。
- 支持适用于决策记录、治理与会议追踪等场景,产生结构化的决策台账输出。
- 明确区分适用与不适用范围,强调不可编造决策及法律审计用途限制。
- 默认先生成可审阅草案,优先罗列待确认项,严格执行安全和合规边界。
Metadata
Frequently Asked Questions
What is Decision Ledger?
从纪要、聊天或项目材料中提取决策、负责人、截止时间、前提假设与撤销条件。;use for decision, meeting, governance workflows;do not use for 编造不存在的决策, 替代法律审计. It is an AI Agent Skill for Claude Code / OpenClaw, with 207 downloads so far.
How do I install Decision Ledger?
Run "/install decision-ledger" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.
Is Decision Ledger free?
Yes, Decision Ledger is completely free, licensed under MIT-0. You can download, install and use it at no cost.
Which platforms does Decision Ledger support?
Decision Ledger is cross-platform and runs anywhere OpenClaw / Claude Code is available (darwin, linux, win32).
Who created Decision Ledger?
It is built and maintained by vx:17605205782 (@52yuanchangxing); the current version is v1.0.0.
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