GOD is a control room for observing and directing societies of language-model agents running in simulated worlds. It lets researchers inspect replays, question individual agents, alter future events, reset simulations, and export experiments for reuse. The catalogue entries are skills and agents for operating and investigating these simulations.
Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add XiaoLuoLYG/GOD --skill financial-document-parsergit clone --depth 1 https://github.com/XiaoLuoLYG/GODWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/xiaoluolyg/god/financial-document-parser)<a href="https://agentmods.dev/skills/xiaoluolyg/god/financial-document-parser"><img src="https://agentmods.dev/badge/skills/xiaoluolyg/god/financial-document-parser/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/xiaoluolyg/god/financial-document-parser"><img src="https://agentmods.dev/badge/skills/xiaoluolyg/god/financial-document-parser.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium Privilege Escalation · line 22 Commands invoke sudo or root privileges. Verify this elevated access is necessary and justified.Fix: Avoid sudo/root unless strictly required. Prefer least-privilege patterns. If elevation is needed, document the justification and scope.
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00042 | $0.01214 |
| Opus 5.5 | $0.00017 | $0.00486 |
| Sonnet 5.5 | $0.00008 | $0.00243 |
| Haiku 4.5 | $0.00004 | $0.00121 |
Grade B, and why
financial-document-parser scanned grade B with 1 finding against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Asks for rootmediumPrivilege escalation
A mod that escalates privileges can change anything on the machine, not only the project.
# Ubuntu: sudo apt install tesseract-ocr tesseract-ocr-chi-sim How it starts
The opening of the file, as written. The whole thing — 163 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Financial Document Parser
解析财务文档（发票、收据、银行对账单）并提取结构化数据。
核心脚本
本 skill 包含一个可复用的 Python 脚本：financial_parser.py
依赖安装
pip install pdfplumber
# 可选：OCR 支持（用于扫描版 PDF 和图片）
pip install pdf2image pytesseract
# 还需要安装 tesseract-ocr 系统包
# Ubuntu: sudo apt install tesseract-ocr tesseract-ocr-chi-sim
命令行用法
# 解析 PDF 发票，输出 Markdown 报告
python financial_parser.py invoice.pdf
# 输出 JSON 格式
python financial_parser.py invoice.pdf --format json
# 导出为 CSV
python financial_parser.py invoice.pdf --format csv
# 解析图片收据
python financial_parser.py receipt.jpg
# 解析 CSV 银行对账单
python financial_parser.py statement.csv
# 完整输出（Markdown + JSON）
python financial_parser.py invoice.pdf --format all
Python API 用法
from financial_parser import FinancialParser
# 解析文档
parser = FinancialParser("/path/to/invoice.pdf")
doc = parser.parse()
# 获取结构化数据
print(doc.doc_type) # Invoice, Receipt, Statement
print(doc.total) # 总金额
print(doc.line_items) # 明细项目列表
# 导出
print(parser.to_markdown()) # Markdown 报告
print(parser.to_json()) # JSON 数据
parser.to_csv("output.csv") # CSV 文件
When to Use This Skill
当用户：
- 提供发票、收据或银行对账单文件
- 要求 "解析这张发票" 或 "提取收据数据"
- 需要费用分类
- 想要追踪消费模式
- 要求生成费用报告
- 提供 PDF 或图片格式的财务文档
执行流程
- 确认文件路径 - 获取用户提供的文件路径
- 运行解析脚本 - 使用 Bash 工具执行：
python financial_parser.py <文件路径> --format all - 展示结果 - 将解析结果展示给用户
- 按需导出 - 如用户需要，导出 CSV 或 JSON
支持的文档类型
| 类型 | 格式 | 提取内容 |
|---|---|---|
| 发票 | 发票号、日期、供应商、明细、税额、总额 | |
| 收据 | PDF/图片 | 商户、日期、商品、金额 |
| 银行对账单 | PDF/CSV | 交易明细、余额、费用 |
| 信用卡账单 | 交易记录、还款信息 |
费用分类
脚本自动将费用分类为：
- Software: 软件、订阅、云服务
- Office: 办公用品、打印
- Travel: 差旅、机票、酒店
- Meals: 餐饮、外卖
- Utilities: 水电、网费
- Marketing: 广告、推广
- Professional: 咨询、法律、会计
- Equipment: 设备、硬件
- Other: 其他
输出示例
# 财务文档分析报告
## 文档信息
- **类型**: Invoice
- **日期**: 2025-01-15
- **单据号**: INV-2025-0042
- **供应商**: 某某科技有限公司
- **总金额**: ¥12,580.00
## 明细项目
| 描述 | 数量 | 单价 | 金额 | 类别 |
|------|------|------|------|------|
| 云服务器年费 | 1 | ¥9,800.00 | ¥9,800.00 | Software |
| 技术支持服务 | 1 | ¥2,000.00 | ¥2,000.00 | Professional |
## 财务汇总
- **小计**: ¥11,150.94
- **税额**: ¥1,429.06
- **总计**: ¥12,580.00
## 费用分类
| 类别 | 金额 |
|------|------|
| Software | ¥9,800.00 |
| Professional | ¥2,000.00 |
## 洞察
- ✓ 最大支出类别: Software (¥9,800.00)
- ✓ 可抵扣税额: ¥1,429.06
## 需关注项
- ⚠ 大额交易: 云服务器年费 (¥9,800.00)
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 1mo ago First seen · 163 lines · 42 tokens per session scan B 307f657557ae
financial-document-parser is a skill published in the GitHub repository XiaoLuoLYG/GOD (1,230 stars, last pushed 2d ago), licensed Apache-2.0. It adds 42 tokens to every session and 1,214 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it B with 1 finding (asks for root). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
Other skills, from other repositories
evo-pdf-invoice-parser
Extracts text from each page of a PDF invoice file using pdfplumber and parses structured fields (vendor name, IBAN, PO number, invoice amount) using regex.
invoice
A printable invoice page — sender + recipient block, line items table, tax breakdown, totals, and payment instructions. Use when the brief mentions "invoice", "bill", "billing statement", or "发票".
cwicr-report-generator
Generate professional cost estimation reports from CWICR calculations. HTML, PDF, Excel outputs with charts and breakdowns.
report-generator
Generate professional HTML/PDF investment reports with interactive visualizations.
financial-parser
Extract and analyze data from invoices, receipts, bank statements, and financial documents. Categorize expenses, track recurring charges, and generate expense reports. Use when user provides financial PDFs or images.
iflytek-ocr-invoice
An image-reading tool that extracts structured information from Chinese invoices, receipts, bills, and tickets. OCR means turning text in a photo or scan into computer-readable data.