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evid-four-check

电子证据四性审查判定器:通过命令行提交证据特征(类型、是否含签名、关联性取值等),按 TH-LAW-001 规则库分别审查真实性、合法性、关联性与完整性,融合后输出含元数据、判定逻辑与置信度的 JSON 结果;退出码 0/1/2 表示通过、告警或用法错误。本地运行、无第三方包依赖,定位为 AI 辅助决策支持,而非法律意见或法律结论。

zhaoxinghua09-cell
zhaoxinghua09-cell
热度 61.35
最近更新 2026-10-17 07:26:05
分类:安全依赖:代码执行应用场景:法律文档 / 数据处理 / 自动化脚本

安装技能

复制下面的话术发给你的 Agent,它会通过 secure-skills 检索并安装该技能。

执行命令安装此 skill: npx secure-skills-cli add evid-four-check
Metadata
name
evid-four-check
slug
evid-four-check
displayName
电子证据四性审查判定器
version
1.0.1
category
it-ops-security
display_name
电子证据四性审查判定器
display_name_en
Electronic Evidence Four-Properties Review
title
电子证据四性审查判定器
author
诺律(SynomosAI)
author_note
"SynomosAI" — 未申请实体注册、未申请商标注册(not a registered legal entity; no trademark registered)
license
MIT
allowed-tools
Read, Glob, Grep, Bash, Write, Edit, WebFetch
license_scope
代码(.py 文件)MIT;本 SKILL.md 与其中理论文本不在 MIT 覆盖范围内(见文末「License & attribution」)
description
电子证据四性审查判定器——基于官方规则源的零依赖决策支持工具,JSON IR 输出,覆盖TH-LAW-001域。 适用场景:当需要电子证据四性审查判定器能力时使用本技能;触发词:合规、判定器、TH-LAW-001、evid-four-check。
tags
["合规","判定器","TH-LAW-001","evid-four-check","电子证据","四性审查"]
description_zh
电子证据四性审查判定器——基于官方规则源的零依赖决策支持工具,JSON IR 输出,覆盖TH-LAW-001域。
description_en
Electronic evidence authenticity and legality (four-properties) review determination tool: zero-dependency decision support with JSON IR output (domain TH-LAW-001).
classification
{"skillhub":["security-compliance"],"iso_25010":["Security"]}
risk_tier
medium
risk_rationale
门禁批量补丁默认 medium(按默认策略设计为中等风险):调用 API/读写文件/本地执行,最小权限,密钥走 Secret;若实际涉对外代执行(push/发布/发送/上架)须人工复评,改 high 并走人工批准。
platforms
["windows","macos","linux"]
read_when
["法院/仲裁庭等法律环境下要对电子证据做四性(真实/合法/关联/完整)形式审查","要把多源异构证据数据转成标准 JSON IR 供下游系统解析","需要零依赖、可审计、输入不全时从严推定的证据判定","用户说「电子证据能不能用」「四性审查」「聊天记录/合同证据效力」"]
ai_protocol
true
spec
usk/1.0
interface
{"type":"cli","entry_point":"evid-four-check.py","runtime":"python3","call_pattern":"args"}
input_schema
{"args":{"type":"string","description":"命令行参数透传给主脚本,具体取值见各包 --help","required":false}}
output_schema
{"stdout":{"type":"string","description":"标准输出为 JSON 结果,含逐项检查与总体结论"},"exit_code":{"type":"integer","description":"0=PASS/完成;1=FAIL/有警告或待补强;2=用法或参数错误"}}
capabilities
["cli_tool"]
permissions
{"network":false,"filesystem":false,"subprocess":false}
requirements
{"python_packages":[],"min_python":"3.8"}
changelog
1.0.1: Bilingual rewrite (full EN+ZH, English first), added read_when; 1.0.0: initial upload (USK v3)

凡自治之物 · LGD 治理学 · 创造术家族 | 评测协议:见平台质量门禁规范

English

When to use

Use it in legal settings such as courts or arbitral tribunals, when the compliance of electronic evidence must be reviewed against court-admission standards. It also fits the front-end of a legal-AI decision chain, where multi-source heterogeneous data must be converted into a standardized JSON IR for downstream systems to parse. It further fits deployments with no external-script dependency constraints, where a local rule base must deliver a zero-risk, auditable determination of the four properties of electronic evidence — authenticity, legality, relevance and integrity.

Usage

Submit the electronic evidence dataset to be reviewed directly through the skill's configuration interface, and pass domain=TH-LAW-001 to lock the rule-source scope. No external script needs to be loaded: just set input_data (path to the evidence package), output_format=json (forces JSON IR) and strict_mode=true (enables strict determination). When the run finishes, read the skill response object directly — it contains the standard JSON result with metadata, decision logic and confidence, needing no extra conversion tool.

Workflow

  1. Initialization & validation: auto-load the official TH-LAW-001 rule base, receive the user's evidence input and verify completeness.
  2. Parallel review: launch four sub-modules — authenticity, legality, relevance, integrity — to judge the evidence independently.
  3. Result fusion: compare each sub-module's conclusion against preset thresholds, producing an overall compliance score and anomaly flags.
  4. Report serialization: wrap the analysis logic into a JSON IR structure, embedding a metadata index for later traceability.
  5. Return via the standard interface: push a standardized response package so downstream systems can parse it directly.
  6. Log archival: automatically record the review-process hash and operation logs, forming a tamper-evident audit trail.

Evidence & safety statement

  • Evidence: TBD (no evaluation / badge link yet; update here once it is produced)
  • Version: 1.0.1
  • Security: no independent security scan has been performed (TBD); the conclusion is pending and no endorsement is given until it is completed. This is AI-assisted decision support, not legal advice or a legal conclusion — verify against official texts.

中文

何时用

适用于法院、仲裁庭等法律环境下的电子证据合规性审查场景,确保输出结果符合法庭采信标准。 适用于构建法律 AI 决策链路的前端环节,需要将多源异构数据转换为标准化 JSON IR 格式供下游系统解析的集成环境。 适用于无外部脚本依赖约束的项目部署,要求利用本地规则库实现零风险、可审计的电子证据四性(真实性、合法性、关联性、完整性)判定需求。

用法

直接通过技能配置接口提交待审查电子证据数据集合,并传入 domain=TH-LAW-001 以锁定规则源范围。 调用时无需加载任何外部脚本文件,仅需设置参数 input_data(证据包路径)、output_format=json(强制 JSON IR)及 strict_mode=true(开启严格判定)。 系统运行结束后,直接读取技能响应对象即可获取包含元数据、判定逻辑及置信度的标准 JSON 结果,无需额外转换工具。

流程

  1. 初始化与校验:自动加载 TH-LAW-001 官方规则库,接收用户输入的证据数据并验证完整性。
  2. 并行审查执行:分别启动真实性、合法性、关联性、完整性四个子模块对证据进行独立判定。
  3. 结果融合分析:比对各子模块结论与预设阈值,生成综合合规性评分及异常标记。
  4. 报告序列化:将分析逻辑封装为 JSON IR 结构,嵌入元数据索引以便后续溯源验证。
  5. 返回标准接口:向调用方推送标准化响应包,确保下游系统可直接解析使用。
  6. 日志归档:自动记录审查过程哈希值与操作日志,形成不可篡改的审计轨迹。

证据与安全声明

  • 证据:TBD(暂无评测/徽章链接;产生后在此更新实际链接)
  • 版本:1.0.1
  • 安全:未做独立安全扫描(TBD),结论待补;补全前不作推荐背书。本工具为 AI 辅助决策支持,非法律意见、非法律结论——请对照官方文本核实。