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 agentmods add commands/godisego/hot-money/compsgit 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/comps)<a href="https://agentmods.dev/commands/godisego/hot-money/comps"><img src="https://agentmods.dev/badge/commands/godisego/hot-money/comps.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 | $0.00029 | $0.00312 |
| Opus 5 | $0.00015 | $0.00156 |
| Sonnet 5 | $0.00006 | $0.00062 |
| Haiku 4.5 | $0.00003 | $0.00031 |
Grade A, and why
comps 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 5d 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 comps — 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
/comps <股票代码>
对目标股票做机构级 Comparable Company Analysis，识别相对同行的估值位置。
工作流
- 拉取目标股票基础数据 + 同行列表 (
fetch_similar_stocks.py) - 调用：
from lib.fin_models import build_comps_table comps = build_comps_table(target, peers) - 输出：
- 同行池（默认 4-10 家）
- 关键倍数统计：min / p25 / median / p75 / max / mean
- 目标公司在每个倍数上的百分位排名
- 中位 PE × EPS → 隐含每股价
- 中位 PB × BVPS → 隐含每股价
- 估值结论（便宜 / 合理偏低 / 合理偏高 / 昂贵）
展示规范
- 峰值排序：PE / EV-EBITDA / P/S 三栏为主
- 颜色：低于 p25 标绿，高于 p75 标红
- 百分位：0-25 便宜 / 25-50 合理偏低 / 50-75 合理偏高 / 75-100 昂贵
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.
- 5d ago First seen · 31 lines · 29 tokens per session scan A 0917b84fb738
comps is a command published in the GitHub repository godisego/hot-money (2 stars, last pushed 4mo ago), licensed MIT. It adds 29 tokens to every session and 312 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 comps, differing in 0 lines, and is treated as a copy.
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