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 · 29 · 0 current installs · 0 all-time installs
⭐ 0
安装量（当前） 0
🛡 VirusTotal：Pending · OpenClaw ：良性
Package：52yuanchangxing/legal-matter-intake-summarizer
安全扫描（ClawHub）
- VirusTotal：Pending
- OpenClaw ：良性
OpenClaw 评估
The skill is internally consistent with its stated purpose (local legal intake summarization), requires only python3, has no network/install steps or extra credentials, and its script behavior matches the SKILL.md instructions.
目的
Name/description (legal intake summarizer) match the included files and script. The only required binary is python3, there are no unrelated credentials, and resources (spec.json, template.md) drive generation — all proportional to a local summarizer/audit tool.
说明范围
SKILL.md confines behavior to producing structured summaries and explicitly forbids performing external system changes. The script supports reading files and directories and will scan many text file types (md, txt, json, py, js, sh, csv, etc.) and produce reports. This file-read capability is appropriate for a local audit/summarizer, but users should avoid supplying system-sensitive paths (e.g., /home, /etc, credential stores) as input.
安装机制
No install spec; this is instruction-only plus a local python script. No downloads or third-party package installs are requested.
证书
The skill requests no environment variables or credentials. The included script scans local files but does not access remote endpoints or require secrets, so requested environment access is proportional to purpose.
持久
always is false and the skill is user-invocable. It does not attempt to modify other skills or system-wide agent settings. Note: autonomous invocation is allowed (disable-model-invocation=false) — normal for skills — so users should consider whether they want the agent to run this skill without confirmation.
综合结论
This skill appears coherent and safe for local, read-only summarization of case materials. Before running it: (1) only provide the specific input files or a dedicated directory — do not point it at system or home directories containing secrets, credentials, or unrelated data; (2) prefer a sandbox or isolated workspace if processing potentially sensitive PII; (3) review generated output before acting on it — the skill intentionally avoids givin…
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「Legal Matter Intake Summarizer」。简介：把法律相关咨询材料整理成事实、争议点、缺失材料与后续问题，不给法律结论。；use for legal, intake, case-summary workfl…。
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/legal-matter-intake-summarizer/SKILL.md
（来源：yingzhi8.cn 技能库）SKILL.md
---
name: legal-matter-intake-summarizer
version: 1.0.0
description: "把法律相关咨询材料整理成事实、争议点、缺失材料与后续问题，不给法律结论。；use for legal, intake, case-summary workflows；do not use for 提供法律意见结论, 替代律师审查."
author: OpenClaw Skill Bundle
homepage: https://example.invalid/skills/legal-matter-intake-summarizer
tags: [legal, intake, case-summary, operations]
user-invocable: true
metadata: {"openclaw":{"emoji":"⚖️","requires":{"bins":["python3"]},"os":["darwin","linux","win32"]}}
---
# 法务接案摘要器
## 你是什么
你是“法务接案摘要器”这个独立 Skill，负责：把法律相关咨询材料整理成事实、争议点、缺失材料与后续问题，不给法律结论。
## Routing
### 适合使用的情况
- 把这堆法务材料整理成接案摘要
- 列出还缺哪些材料
- 输入通常包含：事实经过、时间线、已有文件
- 优先产出：事实摘要、争议点、风险提示
### 不适合使用的情况
- 不要提供法律意见结论
- 不要替代律师审查
- 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：
- 事实摘要
- 争议点
- 已知证据
- 缺失材料
- 需进一步确认
- 风险提示
## 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
- 只做材料整理与问题清单。
- 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。