Borrowing it
Nothing to install: this file belongs to godisego/hot-money. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/godisego/hot-money/main/CLAUDE.mdgit 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/instructions/godisego/hot-money/claude-md)<a href="https://agentmods.dev/instructions/godisego/hot-money/claude-md"><img src="https://agentmods.dev/badge/instructions/godisego/hot-money/claude-md/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/instructions/godisego/hot-money/claude-md"><img src="https://agentmods.dev/badge/instructions/godisego/hot-money/claude-md.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 | $0.00536 | $0.00536 |
| Opus 5 | $0.00268 | $0.00268 |
| Sonnet 5 | $0.00107 | $0.00107 |
| Haiku 4.5 | $0.00054 | $0.00054 |
Grade A, and why
hot-money CLAUDE.md 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 10d 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
UZI-Skill · Claude Code Context
本文件供 Claude Code 自动读取，提供项目上下文。
这是什么
一个股票深度分析 plugin。用户说"分析 XXX"时，你应该自动触发 deep-analysis skill。
核心技能
| Skill | 触发条件 | 说明 |
|---|---|---|
deep-analysis |
用户提到"分析/研究/估值/DCF/值不值得买"等 | 22维数据 + 51评委 + Bloomberg报告 |
investor-panel |
用户要求"只看评委/大佬怎么看" | 单独跑投资者面板 |
lhb-analyzer |
用户提到"龙虎榜/游资/营业部" | 龙虎榜专项分析 |
trap-detector |
用户提到"杀猪盘/有没有问题/安全吗" | 杀猪盘检测 |
工作流 · 深浅两档（v2.10.6）
快速路径（默认）：用户说"分析/看看"时，优先走 CLI 直跑。
python3 run.py <ticker> --depth lite --no-browser # 30-60s
# 或
python3 run.py <ticker> --depth medium --no-browser # 2-4min，默认完整度
v2.10.4 起 CLI 直跑 agent_analysis.json 缺失自动降级 warning，照样出 HTML 报告。不需要 role-play 51 评委。
深度路径：仅当用户明确要 DCF / IC memo / 首次覆盖 / 投委会备忘录等深度产物时走两段式：
stage1()— 脚本采集数据 + 规则引擎骨架分- 你介入 — 读
panel.json，role-play 51 评委，写agent_analysis.json stage2()— 自动合并你的分析，生成报告
详细流程见 AGENTS.md / skills/deep-analysis/SKILL.md。
重要文件
AGENTS.md— 完整 agent 指令skills/deep-analysis/SKILL.md— 深度分析工作流skills/deep-analysis/scripts/run_real_test.py— 主引擎commands/analyze-stock.md—/analyze-stock命令
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.
- 10d ago First seen · 41 lines · 536 tokens per session scan A 1709f67af8c3
hot-money CLAUDE.md is an instructions file published in the GitHub repository godisego/hot-money (2 stars, last pushed 4mo ago), licensed MIT. It adds 536 tokens to every session, about $0.0027 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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