用于银行零售金融场景的材料/证明核验,当需要检查完整性、一致性、真实性红旗并输出补件与复核建议时触发。
Scanned 6/6/2026
Install via CLI
openskills install aifinlab/FinClaw---
name: bank-t162-retail-finance-proof-validation-assistant
description: "用于银行零售金融场景的材料/证明核验,当需要检查完整性、一致性、真实性红旗并输出补件与复核建议时触发。"
---
# 收入与经营证明核验助手
## 这个 skill 是做什么的
对收入证明、经营证明、流水、合同/发票等材料进行结构化核验,输出完整性检查、跨材料一致性检查、异常红旗提示和补件/复核建议。输出用于支持贷前审查与运营复核,不直接给出“真伪定论”。
## 适用范围
- 经营贷/消费贷材料核验、收入与经营证明核验
- 客户经理、零售运营、贷前审核辅助团队
- 需形成可执行的补件清单、异常项与升级建议
## 何时使用
- 需要对材料完整性、字段一致性、规则符合性做检查时
- 需要将核验发现整理成结构化报告时
## 何时不要使用
- 需要伪造材料或绕过核验规则时
- 未提供任何原始材料或可核验字段时
## 默认工作流
1. 明确核验对象与规则口径(必需材料、字段定义、有效期)
2. 完整性校验(材料/字段缺失)
3. 一致性校验(跨材料字段对齐,如姓名、金额、日期)
4. 真实性红旗识别(异常时间、逻辑冲突、明显篡改迹象)
5. 输出核验结论摘要、补件与复核建议
## 输入要求
- 材料清单(材料类型、来源、时间、字段)
- 核验规则与口径(必需材料、字段一致性规则、有效期要求)
- 业务场景与时间窗口
- 如涉及影像件:必须提供结构化字段或OCR结果
## 输出要求
- 材料完整性结论与缺失清单
- 跨材料一致性异常清单
- 真实性红旗提示与优先级
- 补件清单与复核/升级建议
- 明确“待人工确认”的事项
## 风险与边界
- 不能把自动核验结果等同于最终真伪认定
- 涉嫌伪造、欺诈线索时需建议人工复核/升级
- 不得输出超出材料范围的事实
## 信息不足时的处理
- 明确缺失材料与关键字段
- 输出可继续推进的最小核验建议
- 对关键规则缺失标注[待确认]
## 配套脚本
- `scripts/proof_validation.py`:读取材料清单与核验规则,输出缺失项、一致性异常与红旗提示。
### 脚本使用
```bash
python scripts/proof_validation.py --input documents.json --rules rules.json --output out.json
```
### documents.json 示例结构
```json
{
"documents": [
{
"doc_type": "income_proof",
"issue_date": "2025-12-01",
"fields": {
"name": "张三",
"id_no": "110101********1234",
"monthly_income": 20000
}
},
{
"doc_type": "bank_statement",
"issue_date": "2025-12-15",
"fields": {
"name": "张三",
"monthly_income": 21000
}
}
]
}
```
### rules.json 示例结构
```json
{
"required_docs": ["income_proof", "bank_statement"],
"field_matches": [
{"field": "name", "doc_types": ["income_proof", "bank_statement"]}
],
"valid_days": {
"income_proof": 90
}
}
```
### out.json 输出要点
- `missing_docs`:缺失材料
- `missing_fields`:缺失字段
- `inconsistencies`:跨材料不一致项
- `red_flags`:真实性红旗(如日期异常、逻辑冲突)
- `next_steps`:补件与复核建议
## 交付标准
- 结论可追溯到具体材料与字段
- 能直接用于补件与复核推进
No comments yet. Be the first to comment!
Ultra-compressed communication mode. Cuts token usage ~75% by speaking like caveman while keeping full technical accuracy. Supports intensity levels: lite, full (default), ultra, wenyan-lite, wenyan-full, wenyan-ultra. Use when user says "caveman mode", "talk like caveman", "use caveman", "less tokens", "be brief", or invokes /caveman. Also auto-triggers when token efficiency is requested.
Adversarial multi-agent planning skill. Self-orchestrates 5 hostile category members (unspecified-low, unspecified-high, deep, ultrabrain, artistry) via team-mode for ruthless cross-critique debate, distills only the defensible insights, then MANDATORILY hands the distilled insight bundle to the `plan` agent for executable plan formalization. Use when planning needs maximum rigor and surfacing of weak assumptions, blind spots, and over-engineering. Triggers: 'hyperplan', 'hpp', '/hyperplan', ...
**Complete production-ready guide for Google Gemini embeddings API** This skill provides comprehensive coverage of the `gemini-embedding-001` model for generating text embeddings, including SDK usage, REST API patterns, batch processing, RAG integration with Cloudflare Vectorize, and advanced use cases like semantic search and document clustering. ---
Interview, source-challenge, verify, save, and ADR-gate fuzzy coding requests into Codex-ready implementation specs. Use when a feature, bugfix, refactor, migration, repo-wide change, or architecture task needs user-verified requirements, source-backed decisions, durable architecture decisions, acceptance criteria, validation commands, rollout notes, saved spec/ADR files, and a Codex execution prompt. Do not use when already fully specified or when the user wants direct implementation now.
Use when a repo needs CodeGraph plus ast-grep for Codex MCP setup, exploration, impact analysis, structural search, or safe refactor planning.