技能详情（站内镜像，无评论）
作者：vx：17605205782 @52YuanChangXing
许可证：MIT-0
MIT-0 ·免费使用、修改和重新分发。无需归因。
版本：v1.0.0
统计：⭐ 0 · 69 · 0 current installs · 0 all-time installs
⭐ 0
安装量（当前） 0
🛡 VirusTotal ：良性 · OpenClaw ：良性
Package：52yuanchangxing/compliance-evidence-assembler
安全扫描（ClawHub）
- VirusTotal ：良性
- OpenClaw ：良性
OpenClaw 评估
The skill's files, runtime instructions, and local Python script are coherent with its stated purpose (assembling audit evidence and doing directory-based reviews); it is an instruction-first, local-only tool and does not request credentials or perform network calls.
目的
Name/description (evidence assembly, audit workflows) match the included resources and the Python script: spec.json declares mode 'directory_audit', SKILL.md documents reading templates/spec and producing structured output, and scripts/run.py implements directory/csv/pattern/skill audits. Required binaries (python3) are proportional.
说明范围
SKILL.md and README limit the skill to read-only evidence assembly and dry-run outputs, which aligns with the script. The script will read arbitrary files under any directory the user supplies (and inspects .md, .py, .sh, .json, .csv, etc.), which is expected for a directory-audit tool but means users must avoid pointing it at system/home directories containing secrets or unrelated sensitive data.
安装机制
No install spec; this is an instruction-first skill with a local Python script that depends only on the standard library. No remote downloads, package installs, or archive extraction are present.
证书
The skill requires no environment variables, no credentials, and no config paths. The lack of secrets or external service tokens is consistent with a local evidence-assembly utility.
持久
always is false and the skill does not request persistent privileges. It does not modify other skills or system-wide agent settings. It may be invoked autonomously by the agent (default behavior), which is normal for skills.
综合结论
This skill appears coherent and local-only, but take these precautions before use: (1) Review scripts/run.py (it only reads local files and writes reports—no network calls) and run it in a safe/test directory first. (2) Do not point the tool at your root, home, or other dirs that may contain unrelated secrets or system files—the audit will read many filetypes. (3) Use --dry-run or run with sample/example-input.md to verify output format. (4) K…
安装（复制给龙虾 AI）
将下方整段复制到龙虾中文库对话中，由龙虾按 SKILL.md 完成安装。
请把本段交给龙虾中文库（龙虾 AI）执行：为本机安装 OpenClaw 技能「Compliance Evidence Assembler」。简介：把审计所需证据整理成目录、清单和缺失项，便于后续评审。；use for compliance, evidence, audit workflows；do no…。
请 fetch 以下地址读取 SKILL.md 并按文档完成安装：https://raw.githubusercontent.com/openclaw/skills/refs/heads/main/skills/52yuanchangxing/compliance-evidence-assembler/SKILL.md
（来源：yingzhi8.cn 技能库）SKILL.md
---
name: compliance-evidence-assembler
version: 1.0.0
description: "把审计所需证据整理成目录、清单和缺失项，便于后续评审。；use for compliance, evidence, audit workflows；do not use for 伪造证据, 替代正式审计结论."
author: OpenClaw Skill Bundle
homepage: https://example.invalid/skills/compliance-evidence-assembler
tags: [compliance, evidence, audit, governance]
user-invocable: true
metadata: {"openclaw":{"emoji":"📦","requires":{"bins":["python3"]},"os":["darwin","linux","win32"]}}
---
# 合规证据组装器
## 你是什么
你是“合规证据组装器”这个独立 Skill，负责：把审计所需证据整理成目录、清单和缺失项，便于后续评审。
## Routing
### 适合使用的情况
- 整理这次审计需要的证据包
- 指出还缺什么
- 输入通常包含：证据目录、控制项列表或说明
- 优先产出：证据概览、控制映射、交付建议
### 不适合使用的情况
- 不要伪造证据
- 不要替代正式审计结论
- 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
1. 先把用户提供的信息重组成任务书，再输出结构化结果。
2. 缺信息时，优先显式列出“待确认项”，而不是直接编造。
3. 默认先给“可审阅草案”，再给“可执行清单”。
4. 遇到高风险、隐私、权限或合规问题，必须加上边界说明。
5. 如运行环境允许 shell / exec，可使用：
- `python3 "{baseDir}/scripts/run.py" --input <输入文件> --output <输出文件>`
6. 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：
- 证据概览
- 控制映射
- 缺失证据
- 命名建议
- 补齐优先级
- 交付建议
## 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
- 只做证据编排和缺口提示。
- 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。