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 ai-berkshiregit 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/ai-berkshire)<a href="https://agentmods.dev/skills/travisun/opptrix/ai-berkshire"><img src="https://agentmods.dev/badge/skills/travisun/opptrix/ai-berkshire/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/ai-berkshire"><img src="https://agentmods.dev/badge/skills/travisun/opptrix/ai-berkshire.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 | $0.00092 | $0.01950 |
| Opus 5 | $0.00046 | $0.00975 |
| Sonnet 5 | $0.00018 | $0.00390 |
| Haiku 4.5 | $0.00009 | $0.00195 |
Grade A, and why
ai-berkshire 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 10d 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.
How it starts
The opening of the file, as written. The whole thing — 124 lines — stays where its author put it; the contents beside it link to each section on GitHub.
AI Berkshire 分析
署名：Opptrix · AI Berkshire 分析
本技能是价值投资工作流总入口：路由并激活基础 skill，禁止无差别串行跑完全部重研究 skill（成本爆炸）。
何时使用 / 非目标 / 边界
| 使用 | 不要用本技能 |
|---|---|
| 用户要「按 AI Berkshire / 四大师流程」做投研，但场景未钉死单一 skill | 用户明确只要多空辩论研讨团 → @skill:multi-role-research-council |
| 需要场景路由 + 统一质量门禁与 web 交付结构 | 用户已点名单一基础 skill（如只要财报精读）→ 直接激活对应 skill |
| 量化因子/LEAN 回测 → quants / lean-* 技能 |
与 multi-role-research-council（硬性）
| 本技能 | 投资研讨团 | |
|---|---|---|
| 框架 | 段永平/巴菲特/芒格/李录价值投资 | 多空辩论 + 风险互评 |
| 角色 | 流程入口 + 基础 AB skill | 分析师→Bull/Bear→主席→风险三人 |
| 署名 | Opptrix · AI Berkshire 分析 | Opptrix投资研讨团流程 |
| 禁止合并 | 勿把研讨团报告写成四大师流程，反之亦然 |
强制质量规则摘要（契约 §6，执行时必须重申）
- 四大师：深度结论须显式覆盖四视角，或声明因数据不足无法评分。团队类须
run_subagent独立成稿再综合，禁止「一个 prompt 切四段」冒充对抗。 - 强制结论：通过 / 有条件通过 / 不通过 / 灰色地带（或场景等价枚举）；禁止两面讨好收尾。区分好生意 ≠ 好价格下的好投资。
- 镜子测试：买入或「通过」前 ≤5 句说清生意、为何现在、证伪条件。
- A/B/C：报告头标注；资料多 ≠ 确定性高；AI 置信度 ≠ 投资确定性。
- 快速否决：诚信/能力圈红线一票否决。
- 纪律：
get_current_time→ 数据截止日；事实|观点；关键数字经financial-data严谨脚本；取数失败禁止训练知识冒充；交付免责声明。
场景路由表（摘要）
完整表见 references/route-table.md。路由脚本：
python scripts/route_plan.py --input route.json --output plan.json
输入示例：
{ "intent": "deep_research", "symbol": "600519", "urgency": "normal" }
| intent 示例 | 推荐技能顺序（核心） | team 并行 |
|---|---|---|
quick_screen |
financial-data → investment-checklist → quality-screen | 否 |
deep_research |
financial-data → investment-research → investment-memo-craft | 否 |
team_research |
financial-data → investment-team → investment-memo-craft | 是 |
earnings / earnings_team |
financial-data → earnings-review 或 earnings-team | team 仅后者 |
industry_funnel |
financial-data → industry-funnel → investment-checklist | 否 |
portfolio |
financial-data → value-portfolio-review | 否 |
thesis / thesis_drift |
financial-data → value-thesis-tracker / thesis-drift | 否 |
news_pulse |
financial-data → news-pulse | 是 |
| 其他 | 见 route-table（management / private / series / income / bottleneck / wechat / memo_craft / dyp） | 视场景 |
What ships with it
4 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.
- 10d ago First seen · 124 lines · 92 tokens per session scan A f3492cd5b59d
ai-berkshire is a skill published in the GitHub repository Travisun/Opptrix (231 stars, last pushed 3d ago), licensed Apache-2.0. It adds 92 tokens to every session and 1,950 once invoked, about $0.0005 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.
Other skills, from other repositories
national-team-position
A Chinese-language analysis tool that estimates changes in China’s government-backed ETF holdings by tracking ETF share counts and related index prices. ETFs are funds traded on stock exchanges, and the “national team” refers here to Central Huijin, a state investment company.
caijing-ipo-hk
A Chinese-language adviser for Hong Kong stock initial public offerings, or IPOs—the first sale of a company's shares to the public. It covers how to apply, how much to apply for, and risks such as the share price falling below the offering price.
caijing-fundamental
A finance research skill for writing a detailed, forward-looking analysis of a listed company’s business, financials, valuation, risks, and investment arguments. It covers companies listed in mainland China and Hong Kong.
rodya-caijing-studio
A toolkit for researching Chinese A-share and Hong Kong-listed companies and producing financial content. It includes separate workflows for company fundamentals, earnings, valuation, risks, industries, and IPO checks.
caijing-earnings
A finance research skill for reviewing listed companies’ earnings reports, or preparing for an upcoming report. It focuses on Chinese A- and Hong Kong-listed companies.
caijing-valuation
A Chinese-language adviser that assesses whether a stock's current valuation looks high or low. It adapts the comparison to the industry and examines historical and peer-company valuation ranges.