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.
git clone --depth 1 https://github.com/godisego/hot-moneyWrote 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/commands/godisego/hot-money/dd)<a href="https://agentmods.dev/commands/godisego/hot-money/dd"><img src="https://agentmods.dev/badge/commands/godisego/hot-money/dd.svg" alt="Measured on agentmods" 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 | $0.00022 | $0.00454 |
| Opus 5 | $0.00011 | $0.00227 |
| Sonnet 5 | $0.00004 | $0.00091 |
| Haiku 4.5 | $0.00002 | $0.00045 |
Grade A, and why
dd 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 7d 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.
This is a copy
100% identical to dd — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
What it actually says
/dd <股票代码>
自动生成 PE/M&A 风格的 Due Diligence Checklist。
5 大工作流
- 财务尽调 (Financial DD) — 5Y 营收 / ROE / FCF / 资产负债率 / 审计意见
- 商业尽调 (Commercial DD) — TAM / 竞争格局 / 客户集中度 / 上下游
- 法律尽调 (Legal DD) — 股权结构 / 重大诉讼 / 关联交易 / 质押
- 运营尽调 (Operational DD) — 护城河 / 研发 / 管理层 / ESG
- 市场尽调 (Market DD) — 政策 / 舆情 / 事件 / 杀猪盘风险
工作流
from lib.deep_analysis_methods import build_dd_checklist
dd = build_dd_checklist(features, raw)
输出
- 每条 ✅ 已有数据 / ⚪ 需人工核查 / ❌ 缺失
items_auto_verified / total_items完成率manual_review_required剩余人工待办数
展示样式
📋 DD Checklist — 水晶光电 (002273.SZ)
财务尽调: ✅ 营收 ✅ ROE ✅ 债务 ✅ FCF ⚪ 审计
商业尽调: ✅ TAM ✅ 竞争 ⚪ 客户 ✅ 上下游
法律尽调: ✅ 股权 ⚪ 诉讼 ⚪ 关联 ✅ 质押
运营尽调: ✅ 护城河 ⚪ 研发 ⚪ 管理 ⚪ ESG
市场尽调: ✅ 政策 ✅ 舆情 ✅ 事件 ✅ 杀猪盘
15/21 auto-verified (71%) · 6 items need manual review
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.
- 7d ago First seen · 44 lines · 22 tokens per session scan A e884a5376524
dd is a command published in the GitHub repository godisego/hot-money (2 stars, last pushed 4mo ago), licensed MIT. It adds 22 tokens to every session and 454 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to dd, differing in 0 lines, and is treated as a copy.
Other commands, from other repositories
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tax-planning
Optimize tax liability or ensure tax compliance.
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child-support-calc
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