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 stress-testgit 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/stress-test)<a href="https://agentmods.dev/skills/travisun/opptrix/stress-test"><img src="https://agentmods.dev/badge/skills/travisun/opptrix/stress-test/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/stress-test"><img src="https://agentmods.dev/badge/skills/travisun/opptrix/stress-test.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 | $0.00052 | $0.00897 |
| Opus 5 | $0.00026 | $0.00449 |
| Sonnet 5 | $0.00010 | $0.00179 |
| Haiku 4.5 | $0.00005 | $0.00090 |
Grade A, and why
stress-test 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
压力测试
何时使用
用户要对持仓组合做 显式情景冲击测算（如指数跌 X%、单票腰斩、板块共振等），而非历史归因或再平衡方案。边界：归因用 @skill:performance-attribution；调仓方案用 @skill:rebalance。完整度 assumption-only：情景参数必须显式（用户给或 ask_user）；可用 opptrix_run 计算。
分析架构（投研方法）
- 问题/假设：在约定冲击下，组合市值/盈亏如何变化？集中风险是否放大？
- 证据清单：持仓权重与市值、用户情景参数、计算结果
- 多维交叉验证：加总冲击 vs 分项；相关性简化假设是否披露
- 结论与不确定：结果为情景输出；非预测
- 风险与缺口：无持仓、情景未定义、忽略流动性
- 事实 | 假设 | 推断 分栏强制
数据维度
| 维度 | 取数方向 | 缺失时 |
|---|---|---|
| 持仓 | get_portfolio_holdings / portfolio_summary |
not-feasible |
| 情景参数 | ask_user（跌幅、相关性简化等） |
禁止静默套用「标准危机」冒充事实 |
| 计算 | opptrix_run |
手工表并说明 |
| 固化 | workspace_write / workspace_read |
可选 |
| 交付 | list_web_vendor → create_web |
用户只要口头要点时可跳过 |
步骤
- 确认组合范围与持仓快照。
- 显式情景表：每个情景名称、冲击规则、相关性假设；
ask_user补全。 - 测算：
opptrix_run；记录中间假设。 - 解读：最大回撤近似、贡献集中；推断分栏。
- 交付网页（默认）：
list_web_vendor→create_web；标注 assumption-only。
网页报告建议目录
- 组合快照与时效
- 显式情景参数表（假设）
- 冲击结果表/图
- 分项贡献与集中度
- 事实 | 假设 | 推断分栏
- 方法局限（线性、忽略流动性等）
- 风险与缺口
- 免责声明（非预测；无调仓指令）
禁止
- 荐股/强平建议；把情景结果写成「将会发生」
- 隐瞒情景假设
- 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）
- assumption / not-feasible 须诚实降级
- 禁止伪造历史危机复现精度
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 · 52 tokens per session scan A 8b93eb5220d6
stress-test is a skill published in the GitHub repository Travisun/Opptrix (231 stars, last pushed 2d ago), licensed Apache-2.0. It adds 52 tokens to every session and 897 once invoked, about $0.0003 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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