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 qrs-timinggit 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/qrs-timing)<a href="https://agentmods.dev/skills/travisun/opptrix/qrs-timing"><img src="https://agentmods.dev/badge/skills/travisun/opptrix/qrs-timing/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/qrs-timing"><img src="https://agentmods.dev/badge/skills/travisun/opptrix/qrs-timing.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium analysis-evasion · line 1 Suspicious Unicode normalization or mixed-script contentFix: Review the flagged content for security risks. Ensure no credentials, secrets, or sensitive data are exposed.
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 | $0.00883 |
| Opus 5 | $0.00041 | $0.00441 |
| Sonnet 5 | $0.00016 | $0.00177 |
| Haiku 4.5 | $0.00008 | $0.00088 |
Grade A, and why
qrs-timing 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
QRS 择时（中金）
方法溯源中金《金融工程视角下的技术择时艺术》QRS 思路，对照 QuantsPlaybook SignalMaker/qrs.py 重写为自包含脚本（无 pandas/numpy 依赖）。与独立模块 @skill:signal-qrs（若存在）同源算法，本技能面向择时解读 + 网页交付。
何时使用
用户要对单标的（指数/ETF/个股）用高低价相关结构生成 QRS 规则状态。
非目标：多资产向量化批量选股；完整 backtrader 回测引擎；荐股。
算法要点（事实）
- 窗口 N：计算
corr(high,low)与β = (std(high)/std(low))·corr（可选 simple β 不含 corr） - 窗口 M：对 β 序列滚动 zscore →
zscore_beta regulation = |corr|^n（可选除以滚动均值）qrs = zscore_beta × regulation；阈值映射为状态 1 / -1
数据维度
| 维度 | 取数方向 | 缺失时 |
|---|---|---|
| 标的 | search_instruments / ask_user |
先确认 |
| 日 K high/low | get_instrument_chart |
无法计算 |
| 参数 | ask_user（N/M/n/阈值） |
用默认并标假设 |
| 落盘 | workspace_write |
无法跑脚本 |
| 脚本 | get_agent_skill_file → workspace |
说明从 skill 读出 |
| 计算 | opptrix_run |
写明错误 |
| 交付 | create_web |
可跳过口头要点 |
步骤
- 确认标的与区间（默认 CN）。
get_instrument_chart取 high/low（建议 ≥ N+M；经典 N=18、M≈600，不足则缩短并声明）。workspace_write输入 JSON（bars+params）。get_agent_skill_file拷贝scripts/qrs_timing.py（或等价读出后执行）。opptrix_run：python scripts/qrs_timing.py --input … --output …- 分栏解读
series与signal→ 默认create_web。
依赖
- 仅 Python 标准库（SKILL 明确：无需 numpy/pandas）
- 禁止脚本联网 / jqdata / tushare
禁止
- 荐股；把 QRS 写成下单指令
- 与
lean-indicator-playbook合并 - 无交付结束（默认 web）
What ships with it
2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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 · 68 lines · 82 tokens per session scan A e1562f55df4a
qrs-timing is a skill published in the GitHub repository Travisun/Opptrix (231 stars, last pushed yesterday), licensed Apache-2.0. It adds 82 tokens to every session and 883 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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