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 Travisun/Opptrix --skill lean-pearson-pairsgit clone --depth 1 https://github.com/Travisun/OpptrixWrote 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/travisun/opptrix/lean-pearson-pairs)<a href="https://agentmods.dev/skills/travisun/opptrix/lean-pearson-pairs"><img src="https://agentmods.dev/badge/skills/travisun/opptrix/lean-pearson-pairs.svg" alt="Measured on agentmods" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00093 | $0.01553 |
| Opus 5 | $0.00046 | $0.00776 |
| Sonnet 5 | $0.00019 | $0.00311 |
| Haiku 4.5 | $0.00009 | $0.00155 |
Grade A, and why
lean-pearson-pairs 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.
How it starts
The opening of the file, as written. The whole thing — 88 lines — stays where its author put it; the contents beside it link to each section on GitHub.
LEAN Pearson配对
方法溯源 QuantConnect LEAN 社区算法/示例思路;本技能是平台工具编排的投研工作流,禁止假装跑完整 LEAN 引擎或输出 LEAN 回测曲线、订单日志冒充引擎结果。实际取数与计算仅限 Opptrix 工具(行情/财务/opptrix_run 沙盒等)。
能力声明(assumption-only):本技能仅提供 Pearson/滚动相关 描述统计。本地无原生协整/Johansen 库;禁止声明「已协整」或输出协整 p 值。需要价差框架请转
@skill:pairs-rv(同样禁止假装协整检验通过)。完整度:assumption-only。
何时使用
用户要在 A股/场内 ETF 上基于 Pearson(或滚动)相关系数 找配对/相关篮候选(LEAN 方法溯源,非美股原版照搬)。默认交付可预览网页。
边界:价差/比值相对价值与协整讨论用 @skill:pairs-rv(亦无原生协整库)。本技能只做相关统计,不得把高相关写成「已协整」或可开多空价差指令。
A股适配(默认)
- 默认市场 CN(A股 / 场内 ETF)。用户点名美股/港股再切换,并声明数据口径与微观结构差异。
- 默认配对:AH 对(若两边可得)或 同业 A股对;禁止默认美股配对清单。
- 融券/做空受限:配对交易模板默认改为相关监测 + 多头侧示意,或「多头+空仓」;禁止假设可自由做空完成经典多空价差。
- 完整度:纯相关分析 partial;可交易多空价差常为 not-feasible-now(需声明)。
- 不可硬适配或数据缺口时:首页横幅写清完整度(partial 或更严)+ 必要时
ask_user。
分析架构(投研方法)
- 问题/假设:哪些标的对在样本期内高相关?相关是否稳定?
- 证据清单:多标的行情序列、相关矩阵、滚动相关(若可算)
- 多维交叉验证:全样本相关 vs 滚动相关;高相关 vs 价差是否均值回归(仅描述,不作协整证明)
- 结论与不确定:相关≠因果;相关≠协整
- 微观/制度风险:涨跌停钝化、T+1、ST/停牌、融券受限(及相关会计口径差异);不得按美股连续可成交或自由做空假设叙事
- 事实 | 假设 | 推断 分栏强制
数据维度
| 维度 | 取数方向 | 缺失时 |
|---|---|---|
| 标的清单 | search_instruments / ask_user |
先确认 |
| 行情序列 | get_instrument_quotes / chart |
标明缺失侧 |
| 相关计算 | opptrix_run |
仅展示散点/表并标假设 |
| 交付 | list_web_vendor → create_web |
可跳过口头要点 |
| 市场/微观结构 | AH 或同业 A 股对;相关矩阵 | 不可做空 → 禁止经典多空模板;横幅说明 |
步骤
- 确认默认 CN:标的/宇宙为 A股或场内 ETF(用户点名其他市场再切换并声明差异)。应用涨跌停/T+1/融券受限等微观约束(见 A股适配)。
- 确认标的与样本期:窗口、收益口径(日/周)
- 能力横幅:无协整声明;与
@skill:pairs-rv分工写清 - 取序列并算相关:矩阵 + 可选滚动相关
- 解读:事实/假设/推断;禁止开平仓指令
- 交付网页(默认):
create_web
网页报告建议目录
- 范围:默认 A股/场内 ETF + LEAN 溯源;仅 Pearson 无协整
- LEAN 溯源与「非引擎」声明
- 样本期与收益口径
- 相关矩阵与候选对
- 滚动稳定性(若有)
- 事实 / 假设 / 推断分栏
- 与 pairs-rv 边界说明
- A股适配与限制(默认 CN;微观结构/代理/完整度)
- 免责声明(无开平仓建议)
禁止
- 荐股、目标价、仓位建议;编造未返回数字
- 声称协整成立或编造协整统计量
- 输出「开多A空B」交易指令
- 与
@skill:pairs-rv混淆表述 - 禁止假装跑完整 LEAN 引擎或伪造 LEAN 日志/回测净值
- 禁止无交付就结束(默认须有 web 产物,除非用户明确只要口头要点)
- 禁止把美股成分/ETF 清单不经映射直接当 A股结果
- 禁止假设可自由融券做空
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 · 88 lines · 93 tokens per session scan A 3d35a7a63efa
lean-pearson-pairs is a skill published in the GitHub repository Travisun/Opptrix (230 stars, last pushed yesterday), licensed Apache-2.0. It adds 93 tokens to every session and 1,553 once invoked, about $0.0005 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 2026-09-03.
Other skills, from other repositories
national-team-position
A Chinese-language analysis tool that estimates changes in China’s government-backed ETF holdings by tracking ETF share counts and related index prices. ETFs are funds traded on stock exchanges, and the “national team” refers here to Central Huijin, a state investment company.
caijing-ipo-hk
A Chinese-language adviser for Hong Kong stock initial public offerings, or IPOs—the first sale of a company's shares to the public. It covers how to apply, how much to apply for, and risks such as the share price falling below the offering price.
caijing-fundamental
A finance research skill for writing a detailed, forward-looking analysis of a listed company’s business, financials, valuation, risks, and investment arguments. It covers companies listed in mainland China and Hong Kong.
rodya-caijing-studio
A toolkit for researching Chinese A-share and Hong Kong-listed companies and producing financial content. It includes separate workflows for company fundamentals, earnings, valuation, risks, industries, and IPO checks.
caijing-earnings
A finance research skill for reviewing listed companies’ earnings reports, or preparing for an upcoming report. It focuses on Chinese A- and Hong Kong-listed companies.
caijing-valuation
A Chinese-language adviser that assesses whether a stock's current valuation looks high or low. It adapts the comparison to the industry and examines historical and peer-company valuation ranges.