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 R2h1/my-book-skills --skill v17git clone --depth 1 https://github.com/R2h1/my-book-skillsWrote 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/r2h1/my-book-skills/v17)<a href="https://agentmods.dev/skills/r2h1/my-book-skills/v17"><img src="https://agentmods.dev/badge/skills/r2h1/my-book-skills/v17/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/r2h1/my-book-skills/v17"><img src="https://agentmods.dev/badge/skills/r2h1/my-book-skills/v17.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00036 | $0.00720 |
| Opus 5 | $0.00018 | $0.00360 |
| Sonnet 5 | $0.00007 | $0.00144 |
| Haiku 4.5 | $0.00004 | $0.00072 |
Grade A, and why
v17-应对市场波动 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 11d 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
应对市场波动
R（核心引文）
"每当冬天过后，春天就来了，接着是夏天，每个夏天之后又跟着是秋天，然后又是冬天，年年如此。跟大自然的变化一样，交易所里也总有四季更替，循环往复。"
"只有当我们今天把它卖出的时候，才会有亏损。可是我们今天并没有这么做。"
"不要把你全部的钱都投资在股票或者基金上面。"
I（底层原理）
市场波动是常态而非异常。长期看，全球股市总体趋势向上，但过程中有剧烈波动。恐慌性卖出是最大的亏损来源——下跌时不卖只是账面亏损，卖出后才变成实际亏损。无法预测市场走势，正确的策略是接受波动+长期持有+保留现金储备。
A1（过去应用）
金钱魔法师们的基金下跌25%（从2万跌到14128马克），马塞尔想卖出，陶穆太太阻止了。她经历过多次危机，每次都在1-2年后恢复。她们选择逢低买进而非卖出，最终获得丰厚回报。金先生建议保留20%现金储备，以便下跌时有资金加仓。
A2（未来触发场景）
- 你持有的基金或股票大幅下跌时
- 看到"市场崩盘"的新闻感到恐慌时
- 你考虑是否应该"先退出等稳定了再进"时
- 你想抄底但不确定时机时
E（执行步骤）
- 投资前确认：这笔钱5-10年内不需要动用
- 下跌时不看盘、不操作、不恐慌
- 保留至少20%现金储备
- 市场大跌时用现金储备逢低买入
- 理解"春夏秋冬"周期理论，冬天正是播种时
B（边界与局限）
此策略适用于指数基金和优质股票基金，不适用于个股。个股可能永远无法恢复（如破产公司）。"长期持有"的前提是选对了投资标的。同时需要强大的心理素质——知行合一最难。
相关技能
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.
- 11d ago First seen · 52 lines · 36 tokens per session scan A fc7a6b5320f8
v17-应对市场波动 is a skill published in the GitHub repository R2h1/my-book-skills (2 stars, last pushed 26d ago), licensed MIT. It adds 36 tokens to every session and 720 once invoked, about $0.0002 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 2026-08-31.
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