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 closing-market-briefgit 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/closing-market-brief)<a href="https://agentmods.dev/skills/travisun/opptrix/closing-market-brief"><img src="https://agentmods.dev/badge/skills/travisun/opptrix/closing-market-brief/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/closing-market-brief"><img src="https://agentmods.dev/badge/skills/travisun/opptrix/closing-market-brief.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 | $0.00066 | $0.00923 |
| Opus 5 | $0.00033 | $0.00462 |
| Sonnet 5 | $0.00013 | $0.00185 |
| Haiku 4.5 | $0.00007 | $0.00092 |
Grade A, and why
closing-market-brief 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.
What it actually says
收盘报告
何时使用
用户要一份收盘后的市场复盘（不是盘前早报，也不是个股深度分析）。默认交付可预览网页报告。
分析架构（投研方法）
- 问题/假设：今日收盘主线与风险偏好如何变化？涨跌停与龙虎榜是否验证热点？
- 证据清单：指数与成交、涨跌分布、涨跌停池、龙虎榜、情绪指标
- 多维交叉验证：指数涨跌 vs 涨跌停家数；题材热度 vs 龙虎榜上榜结构
- 结论与不确定：收盘一句话；标注盘中扰动、数据源覆盖不全
- 风险与缺口：未收盘、缺涨跌停/龙虎榜时写明
- 事实与推断必须分开：家数与涨跌幅为事实；「资金抱团/情绪过热」为推断
数据维度
| 维度 | 取数方向 | 缺失时 |
|---|---|---|
| 时段确认 | get_market_session |
盘中则降级为实时全景并说明 |
| 市场全景 | get_market_dynamics |
禁止编造指数/成交 |
| 涨跌停池 | get_limit_updown |
notes 说明；勿虚构连板 |
| 龙虎榜 | get_dragon_tiger（可选） |
跳过栏目并说明 |
| 情绪 | get_market_sentiment |
省略情绪章 |
| 专题 | get_cn_market_special（须 kind，可选） |
跳过 |
| 交付 | list_web_vendor → create_web |
用户只要口头要点时可跳过 |
步骤
- 确认范围：已收盘则完整复盘；盘中说明并降级。
- 按维度取数：全景 → 涨跌停 → 按需龙虎榜/情绪/专题。
- 交叉验证与结构化结论：主线、强弱、资金博弈要点；事实/推断分栏。
- 交付网页（默认）：
list_web_vendor→create_web完整 HTML；已有则read_web/update_web。 - 备选：用户点名画布用
create_canvas；只要结构图用create_mindmap。
网页报告建议目录
- 报告头：日期、收盘一句话
- 指数与成交（表/图）
- 涨跌分布与情绪
- 涨跌停池与连板高度
- 龙虎榜要点（若有）
- 今日主线与观察（推断标注）
- 数据说明与免责声明
禁止
- 荐股 / 编造涨跌停或龙虎榜
- 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）
- 与早报混淆：本技能含涨跌停与龙虎榜复盘
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 · 67 lines · 66 tokens per session scan A 0b4f9515deeb
closing-market-brief is a skill published in the GitHub repository Travisun/Opptrix (231 stars, last pushed 3d ago), licensed Apache-2.0. It adds 66 tokens to every session and 923 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 2026-08-30.
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.