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 malue-ai/dazee-small --skill invoice-organizergit clone --depth 1 https://github.com/malue-ai/dazee-smallWrote 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/malue-ai/dazee-small/invoice-organizer)<a href="https://agentmods.dev/skills/malue-ai/dazee-small/invoice-organizer"><img src="https://agentmods.dev/badge/skills/malue-ai/dazee-small/invoice-organizer/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/malue-ai/dazee-small/invoice-organizer"><img src="https://agentmods.dev/badge/skills/malue-ai/dazee-small/invoice-organizer.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00027 | $0.00704 |
| Opus 5 | $0.00014 | $0.00352 |
| Sonnet 5 | $0.00005 | $0.00141 |
| Haiku 4.5 | $0.00003 | $0.00070 |
Grade A, and why
invoice-organizer scanned grade A with 0 findings 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 11d 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.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
What it actually says
发票整理助手
自动整理发票和收据：读取文件、提取关键信息、统一命名、分类归档。
使用场景
- 用户说「帮我整理一下发票」「把下载文件夹里的发票分类」
- 报税前需要整理全年发票
- 日常收据管理，按月份/类别归档
依赖安装
首次使用时自动安装：
pip install pypdf Pillow
执行方式
通过 Python 脚本扫描文件夹，识别发票文件，提取信息并归档。
1. 扫描目标文件夹
import os
from pathlib import Path
def scan_invoices(folder: str) -> list:
"""Scan folder for invoice files (PDF/image)."""
extensions = {'.pdf', '.png', '.jpg', '.jpeg'}
invoices = []
for f in Path(folder).rglob('*'):
if f.suffix.lower() in extensions:
invoices.append(f)
return invoices
2. 提取发票信息
对于 PDF 发票：
from pypdf import PdfReader
def extract_pdf_text(path: str) -> str:
"""Extract text from PDF invoice."""
reader = PdfReader(path)
text = ""
for page in reader.pages:
text += page.extract_text() or ""
return text
对于图片发票，使用 LLM 视觉能力识别内容。
3. 信息结构化
从提取的文本中识别：
- 日期：开票日期
- 金额：总金额
- 商家/供应商：开票方名称
- 类型：餐饮/交通/办公用品/住宿等
- 发票号：如有
4. 统一命名和归档
# 命名规则：日期_商家_金额_类型.ext
# 示例：20250115_星巴克_35.00_餐饮.pdf
# 目录结构
# 发票整理/
# ├── 2025-01/
# │ ├── 餐饮/
# │ ├── 交通/
# │ └── 办公用品/
# └── 2025-02/
输出规范
- 操作前先列出发现的发票清单，请求用户确认
- 整理完成后输出汇总表格（数量、总金额、分类统计）
- 保留原始文件不删除，只复制到新目录结构
- 无法识别的发票单独放入「待分类」文件夹
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.
- 11d ago First seen · 105 lines · 27 tokens per session scan A f1d85d9ce6a4
invoice-organizer is a skill published in the GitHub repository malue-ai/dazee-small (36 stars, last pushed 5mo ago), licensed MIT. It adds 27 tokens to every session and 704 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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