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 seaworld008/Commonly-used-high-value-skills --skill event-driven-trackergit clone --depth 1 https://github.com/seaworld008/Commonly-used-high-value-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/seaworld008/commonly-used-high-value-skills/event-driven-tracker)<a href="https://agentmods.dev/skills/seaworld008/commonly-used-high-value-skills/event-driven-tracker"><img src="https://agentmods.dev/badge/skills/seaworld008/commonly-used-high-value-skills/event-driven-tracker/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/seaworld008/commonly-used-high-value-skills/event-driven-tracker"><img src="https://agentmods.dev/badge/skills/seaworld008/commonly-used-high-value-skills/event-driven-tracker.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 2 findings, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium MCP Rug Pull · line 117 npx commands without a version suffix (e.g. @1.0.0) create a rug-pull risk if the upstream server is compromised and publishes a malicious update.Fix: Pin the version: npx @scope/[email protected]
- medium MCP Rug Pull · line 26 npx commands without a version suffix (e.g. @1.0.0) create a rug-pull risk if the upstream server is compromised and publishes a malicious update.Fix: Pin the version: npx @scope/[email protected]
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 | $0.01760 |
| Opus 5 | $0.00018 | $0.00880 |
| Sonnet 5 | $0.00007 | $0.00352 |
| Haiku 4.5 | $0.00004 | $0.00176 |
Grade A, and why
event-driven-tracker 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.
How it starts
The opening of the file, as written. The whole thing — 130 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Event Driven Tracker (事件驱动跟踪器)
在市场“收割”你之前,先锁定关键的股价催化剂(Catalysts)。Event Driven Tracker 旨在帮助投资者从海量的日常公告中识别出真正具备“市场影响力”的大事件,并围绕这些时间点构建防御性或进攻性的交易计划。
安装与前提条件
# 确保已安装事件日历相关的库
pip install openbb pandas
# 准备事件数据
npx clawhub install event-driven-tracker
触发条件 / When to Use
- 股价催化剂日历 (Catalyst Calendars):需要为特定的投资组合建立未来 30 天的重大事件表。
- 关键仓位监控 (Position Monitoring):在财报发布、并购(M&A)审批或期权到期日前后的风险对冲。
- PM 每周准备 (Weekly Prep):为基金经理提供下周可能导致波动(Volatility)的核心节点。
- 事件驱动策略研究 (Event-driven Strategy Notes):针对分拆(Spinoff)、私有化(LBO)、大股东减持(Unlocks)或纳指/标普调样进行专题跟踪。
- 宏观数据预警:非农数据(NFP)、CPI 连续超预期后的政策节点捕捉。
核心能力 / Core Capabilities
1. 事件分类与优先级评估 (Event Prioritization)
- 操作步骤:
- 识别事件类型:软性事件(如分析师日、新产品发布) vs 硬性事件(如财报、特别股息、FDA 审批结果)。
- 根据历史波动率(Implied Volatility vs Realized Volatility)为事件打分 (Importance Score: 1-10)。
- 分配关键属性:公告日期、预期日期、确认日期。
- 最佳实践:优先关注那些“结果非黑即白”(Binary Events)的事件,如法庭判决或重大合同签署。
2. 自动化监控与提醒 (Proactive Monitoring)
- 操作步骤:
- 运行
scripts/track_events.py。 - 提取未来两周内的所有“高分”事件。
- 将事件同步至 Google Calendar 或 Slack 通道。
- 运行
- 最佳实践:在事件发生前 48 小时触发“准备检查清单”。
3. 交易计划关联 (Trade Plan Integration)
- 操作步骤:
- 针对每个事件,关联“如果 A 发生,则执行 B”的逻辑(If-Then Scenarios)。
- 记录当前持仓的止损价和止盈位(Stop-loss / Take-profit)。
- 评估事件后的“情绪漂移”(Post-event Drift)。
- 最佳实践:不仅记录“何时发生”,更要记录“如果结果不及预期,市场最可能的杀跌幅度是多少”。
4. 历史回测与归因分析 (Post-mortem)
- 操作步骤:
- 记录事件前后的真实股价波动。
- 对比共识预期与真实数据。
- 为下一次类似事件优化“影响力得分”。
常用命令/模板 / Common Patterns
事件监控 JSON 模板 (Events JSON)
{
"ticker": "TSLA",
"event_type": "Product Launch",
"event_name": "Robotaxi Day",
"date": "2026-08-08",
"priority": "Critical",
"implied_move": "±8.5%",
"scenario_analysis": {
"Bull": "Full FSD integration roadmap shared -> Target $280",
"Bear": "Vague delay or regulatory hurdles -> Target $210"
}
}
每周催化剂清单模板 (Weekly Catalyst List)
### 🗓️ 本周核心催化剂 (2026-03-30 ~ 2026-04-03)
**1. [高优先级] NVDA GTC 大会 (周二)**:
- **预期**: 发布 B100 架构详情。
- **仓位风险**: 重仓持有中,建议买入 Puts 对冲潜在的“Sell the news”。
**2. [中优先级] PCE 物价指数发布 (周五)**:
- **预期**: 2.6% (YoY)。
- **市场含义**: 如果 > 2.8%,降息预期可能进一步推迟。
**3. [低优先级] AAPL 股息除权日 (周三)**:
- **操作**: 保持现状,无需额外动作。
What ships with it
3 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.
- 5d ago Changed 3477071c58f3
- 9d ago First seen · 130 lines · 36 tokens per session scan A 6053fde009b3
event-driven-tracker is a skill published in the GitHub repository seaworld008/Commonly-used-high-value-skills (70 stars, last pushed 5d ago), licensed MIT. It adds 36 tokens to every session and 1,760 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 2026-09-03.
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