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-sector-weightinggit 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-sector-weighting)<a href="https://agentmods.dev/skills/travisun/opptrix/lean-sector-weighting"><img src="https://agentmods.dev/badge/skills/travisun/opptrix/lean-sector-weighting/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/skills/travisun/opptrix/lean-sector-weighting"><img src="https://agentmods.dev/badge/skills/travisun/opptrix/lean-sector-weighting.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00071 | $0.01219 |
| Opus 5 | $0.00036 | $0.00609 |
| Sonnet 5 | $0.00014 | $0.00244 |
| Haiku 4.5 | $0.00007 | $0.00122 |
Grade A, and why
lean-sector-weighting 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.
What it actually says
LEAN 行业加权
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）。
何时使用
用户要在 A股行业/板块上做权重目标设定、实际持仓或基准对照与漂移表（LEAN 方法溯源，非美股原版照搬）。默认交付可预览网页。
边界：组合整体复盘用 @skill:portfolio-review；因子暴露用 @skill:factor-exposure；再平衡方案用 @skill:rebalance。
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。
- 行业用
get_sector_*（申万/概念等）；权重对照默认 CN 指数行业结构。 - 不做空行业腿。
- 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：行业权重相对目标/基准偏离多少？
- 证据清单：板块分类、持仓或候选权重、对照表
- 多维交叉验证：权重和=100%；分类口径一致
- 结论与不确定：漂移表≠调仓指令
- 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 |
|---|---|---|
| 行业口径 | get_sector_list / ask_user |
先统一分类 |
| 实际/候选权重 | 组合持仓或用户表 | 仅目标示意 |
| 基准对照（可选） | 指数成分近似 | 标明非官方行业指数 |
| 交付 | list_web_vendor → create_web |
可跳过口头要点 |
| A股行业 | get_sector_* + 指数行业权重代理 |
无行业权重官方源则标假设 |
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）。
- 确认分类与对象：持仓/模型组合/基准
- LEAN 溯源边界：灵感来自行业配置示例；不跑 LEAN
- 汇总权重与漂移：事实表
- 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
- 目标 vs 实际/基准权重表
- 漂移与集中度
- 事实 / 假设 / 推断分栏
- 缺口与分类局限
- A股适配与限制（默认 CN；微观结构/代理/完整度）
- 免责声明（无调仓指令）
禁止
- 荐股、目标价、仓位建议；编造未返回数字
- 输出具体调仓下单清单伪装成分析
- 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 · 80 lines · 71 tokens per session scan A f1fc3bdabcdd
lean-sector-weighting is a skill published in the GitHub repository Travisun/Opptrix (231 stars, last pushed yesterday), licensed Apache-2.0. It adds 71 tokens to every session and 1,219 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.
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