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 skills/travisun/opptrix/factor-researchnpx skills add Travisun/Opptrix --skill factor-researchgit clone --depth 1 https://github.com/Travisun/OpptrixWhat 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 | $0.00075 | $0.00905 |
| Opus 5 | $0.00037 | $0.00452 |
| Sonnet 5 | $0.00015 | $0.00181 |
| Haiku 4.5 | $0.00007 | $0.00090 |
Grade A, and why
factor-research 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 3d 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
因子研究
何时使用
用户要做因子历史有效性/多空表现检验(非只要组合当下暴露)。边界:当下持仓暴露用 @skill:factor-exposure;参数扰动网格用 @skill:robustness-check。
分析架构(投研方法)
- 问题/假设:该因子在指定样本期内是否具备可复现的区分度?收益是否伴随不可接受回撤?
- 证据清单:
run_backtest返回的收益、回撤、交易统计;用户声明的因子定义与样本期 - 多维交叉验证:全样本 vs 分段;收益 vs 换手/成本(若可得)
- 结论与不确定:历史≠未来;过拟合须单独成章
- 风险与缺口:样本过短、幸存者偏差、无法做真正截面 IC 时诚实降级
- 事实 | 假设 | 推断 分栏:回测 KPI 为事实;因子构造规则为假设;「仍有效」为推断
数据维度
| 维度 | 取数方向 | 缺失时 |
|---|---|---|
| 因子定义与样本期 | ask_user(须写清起止日期、再平衡、费用假设) |
禁止静默用未声明区间 |
| 回测 | run_backtest |
写明失败原因,禁止口头编造曲线 |
| 分段/对照 | 多次 run_backtest 或工具返回分段 |
标明无法分段验证 |
| 交付 | list_web_vendor → create_web |
用户只要口头要点时可跳过 |
步骤
- 确认因子定义:多空规则、标的池、再平衡频率、费用/滑点假设。
- 写明样本期:起止日期必须出现在报告首页;不足则提示拉长或降级。
- 执行
run_backtest;必要时分段再跑。 - 过拟合审查:参数是否事后挑选、样本是否过拟合训练区间;无样本外则标明。
- 交付网页(默认):
list_web_vendor→create_web;见@skill:create-web。
网页报告建议目录
- 因子定义、样本期与假设表
- 回测 KPI(全样本)
- 分段/对照(若有)
- 过拟合与数据缺口警示
- 事实 / 推断分栏结论
- 免责声明(非投资建议)
禁止
- 荐股或暗示因子必然持续有效
- 编造未返回的 IC/夏普/曲线;口头「回测」冒充
run_backtest - 禁止隐瞒样本期或用模糊「长期」代替具体日期
- 禁止无交付就结束
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.
- 3d ago First seen · 64 lines · 75 tokens per session scan A 89299adb3448
factor-research is a skill published in the GitHub repository Travisun/Opptrix (224 stars, last pushed 5d ago), licensed Apache-2.0. It adds 75 tokens to every session and 905 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 2026-08-30.
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