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-macro-reit-alphagit 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-macro-reit-alpha)<a href="https://agentmods.dev/skills/travisun/opptrix/lean-macro-reit-alpha"><img src="https://agentmods.dev/badge/skills/travisun/opptrix/lean-macro-reit-alpha.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 | $0.00082 | $0.01454 |
| Opus 5 | $0.00041 | $0.00727 |
| Sonnet 5 | $0.00016 | $0.00291 |
| Haiku 4.5 | $0.00008 | $0.00145 |
Grade A, and why
lean-macro-reit-alpha 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 4d 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
LEAN 宏观REIT
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）：本地无完整宏观因子/REIT 专业数据库。利率、CPI、增长等须用用户指定代理或可得指数代替，并标 assumption-only。禁止假装机构宏观 REIT Alpha 模型或 LEAN 云端因子库结果。
何时使用
用户要在 A股地产/公募 REITs/相关 ETF 上探索利率/增长等宏观代理与收益关系的假设框架（LEAN 方法溯源，非美股 REIT 原版照搬）。默认交付可预览网页。
边界：宏观简报用 @skill:macro-brief；跨资产对照用 @skill:cross-asset。无完整宏观因子库时须诚实降级。
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「利率 / 地产链」→ A股地产、公募 REITs、相关 ETF（
search_instruments/get_etf_*）；美股 REIT 仅用户点名。 - 无房贷利率/完整宏观序列时：优先
get_macro_series（若工具可用）或ask_user指定代理；完整度 assumption-only。 - 禁止假装机构宏观 REIT 因子库；不做空假设。
- 不可硬适配或数据缺口时：首页横幅写清完整度（assumption-only 或更严）+ 必要时
ask_user。
分析架构（投研方法）
- 问题/假设：所选宏观代理与 REIT 收益是否同向/反向、滞后几期？
- 证据清单：REIT 标的序列、宏观代理序列、相关/回归示意
- 多维交叉验证：不同利率口径；股权 REIT vs 抵押 REIT（若可分）
- 结论与不确定：宏观叙事易过拟合
- 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 |
|---|---|---|
| REIT 标的 | search_instruments / ask_user |
先确认 |
| 宏观代理 | ask_user（必须写清代理定义） |
禁止静默用「共识预测」 |
| 序列与回归 | get_instrument_quotes + opptrix_run |
仅定性对照 |
| 交付 | list_web_vendor → create_web |
可跳过口头要点 |
| A股地产/REITs代理 | 地产股/REITs/相关 ETF + 宏观代理 | 无利率序列 → get_macro_series / ask_user；assumption-only |
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）。
- 能力横幅：assumption-only；非机构库
- 确认 REIT 与宏观代理：样本期
- 相关/回归示意：敏感与分段
- 分栏结论：禁止仓位建议
- 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；assumption-only
- REIT 与宏观代理定义
- 相关/回归示意表
- 分段与敏感性
- 事实 / 假设 / 推断分栏
- A股适配与限制（默认 CN；微观结构/代理/完整度）
- 免责声明（无买卖建议）
禁止
- 荐股、目标价、仓位建议；编造未返回数字
- 假装机构宏观因子库或卖方 REIT 模型
- 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.
- 4d ago First seen · 84 lines · 82 tokens per session scan A 3da669ae673d
lean-macro-reit-alpha is a skill published in the GitHub repository Travisun/Opptrix (230 stars, last pushed yesterday), licensed Apache-2.0. It adds 82 tokens to every session and 1,454 once invoked, about $0.0004 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.