LGD Fin Guard（金融 AI 合规守门）

Screen a financial AI system against the three laws of registered, evidenced and gated before it goes live, so licensed advisory, risk-control and anti-money-laundering use cases hold up. lgd-fin-guard — 把 LGD 三律（有籍·有证·有门禁）翻译进金融 / 持牌机构 AI 应用（投顾·风控·反洗钱）的合规守门器，对 AI 系统做三律自评与门禁判定（零依赖）。

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

1. Before a financial AI system goes live, to confirm the algorithm model holds advisory or risk-control licensed qualifications.
2. Before external data ingestion, to check that the source meets the "registered · evidenced" identity-authentication requirement.
3. As the admission gate before high-sensitive transaction decisions (credit approval, large transfers) are triggered.

Usage

Call the core script fin_guard.py to run the compliance check, with configurable check dimensions. Example: python fin_guard.py --mode=guard --entity=<AI system id> --scope=qualification/permission. Here --mode is audit or gate, and --entity is the model or business ID under check.

Workflow

1. Identify the AI application module under compliance verification and its associated business scenario.
2. Run python fin_guard.py, passing the entity ID and the three-laws determination mode.
3. The script reads the files and performs the internal LGD three-laws (registered · evidenced · gated) self-assessment.
4. Generate the compliance verdict report, stating pass/reject and the specific missing items.
5. The system automatically allows passage or blocks the data flow based on the result.

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.

中文

何时用

1. 金融 AI 系统上线前，需确认算法模型具备投顾或风控持牌资质。
2. 外部数据接入前，校验源端是否满足“有籍·有证”身份认证要求。
3. 高敏感交易决策（如信贷审批、大额转账）触发前的准入门禁判定。

用法

调用核心脚本 fin_guard.py 执行合规检查逻辑，支持参数配置校验维度。例如：python fin_guard.py --mode=guard --entity=<AI 系统标识> --scope=资质/权限，其中--mode设定为audit(审计)或gate(门禁)，--entity填入待校验的模型或业务 ID。

流程

1. 确认待合规验证的 AI 应用模块及其关联的业务场景需求。
2. 执行 python fin_guard.py 命令，传入实体标识与三律判定模式参数。
3. 脚本读取文件资料对 LGD 三律（有籍·有证·有门禁）进行内部自评计算。
4. 生成合规判定报告，明确通过/拒绝状态及具体缺失项。
5. 系统根据结果自动执行允许通行或阻断数据流的动作。

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。

Triggers / 触发词

这些是用户真实会说的话（中 / 英对照），命中任一即应加载本技能：

• 「投顾算法上线前要查牌照吗」 / "does our robo-advisor need a licence check"
• 「外部数据源进模型前怎么核验」 / "verify data sources before they feed the model"
• 「大额转账的自动决策要加门禁」 / "gate automated decisions on large transfers"
• 「风控模型要不要做合规自评」 / "should the risk model run a compliance review"
• 「反洗钱系统能过监管检查吗」 / "will our AML system pass regulatory scrutiny"
• 「持牌机构的智能应用怎么过审」 / "how do licensed firms get AI approved"

Trigger when the user says any of the above, in Chinese or English.

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Ecosystem / 生态入口

This skill is one door of the LGD ecosystem — every entry below is publicly reachable. 本技能是 LGD 生态 的一个入口，下列地址均对公网可达。

• Ecosystem hub / 生态总入口: https://zhaoxinghua09-cell.github.io/lgd-hub/
• LGD theory (canonical) / 理论正本: https://github.com/zhaoxinghua09-cell/LGD
• Formal paper (DOI) / 形式化论文: https://doi.org/10.5281/zenodo.22456647
• Protocol & reference implementation / 协议与参考实现: https://github.com/zhaoxinghua09-cell/uibc-core
• Source of this skill / 本包源码: https://github.com/zhaoxinghua09-cell/agent-skills/tree/main/skills/lgd-fin-guard
• All published skills / 全部已发布技能: https://github.com/zhaoxinghua09-cell/agent-skills
• AI-readable index / AI 说明书: https://github.com/zhaoxinghua09-cell/agent-skills/tree/main/skills/lgd-fin-guard/llms.txt

Looking for something else? / 还想要别的？

Tell your AI assistant: "Find me an LGD skill that can " — the hub lists every published skill with a one-line purpose. 跟你的 AI 助手说一句「去 LGD 生态超市找能……的技能」，总入口按用途列全了所有已发布技能。