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Us Macro News Monitor

核心功能:从彭博、WSJ等媒体及美联储等官方源收集美国宏观新闻,分类主题、标记基调,映射对越南板块/个股的溢出影响,输出带分级信度的监控内容。典型场景:用户询问美宏观新闻对越南股市的影响、美联储/CPI信号的溢出等。输入为用户相关提问,可指定关注个股;输出含头条、主题分布、板块影响、观察清单,不提供买卖指令。

teahann
teahann
热度 95.83
最近更新 2026-05-22 08:21:59
分类:数据依赖:联网浏览搜索 / 第三方 API应用场景:市场分析 / 报告撰写 / 数据处理

安装技能

复制下面的话术发给你的 Agent,它会通过 secure-skills 检索并安装该技能。

执行命令安装此 skill: npx secure-skills-cli add us-macro-news-monitor
Metadata
name
us-macro-news-monitor
description
Tracks US macro signals from Bloomberg, WSJ, and Reuters and maps potential spillover to Vietnam sectors; used when users ask about US macro news and likely impacts on Vietnamese equities.
compatibility
Requires OpenClaw web fetch and Brave API access.

US Macro News Monitor (Web Workflow)

Use this skill for US macro monitoring that can indirectly impact Vietnamese equities.

Data sources

Primary media sources:

Fallback (open/public macro sources):

Requirements and fallback behavior

  • Requires web access to collect current macro headlines, release pages, and source URLs.
  • Prefer primary media sources when accessible; use public official sources when paywalls or blocks prevent full-text access.
  • If fewer than three distinct sources are accessible, continue with available sources, downgrade confidence, and list blocked or missing sources.
  • No Python scripts are required for this skill.

Execution workflow (ordered)

  1. Collect fresh headlines from primary sources.
  2. Replace blocked/paywalled coverage with fallback public sources.
  3. Classify items into macro themes.
  4. Tag each item with tone (risk-on, risk-off, neutral).
  5. Map transmission channels to Vietnam sectors and representative tickers.
  6. Run quality gate and confidence scoring.
  7. Produce required output sections with source links.

Theme taxonomy

Classify each item into these macro themes:

  • inflation
  • rates/yields
  • growth/employment
  • USD/FX
  • oil/energy
  • geopolitics/trade

Summarization horizon:

  • 24h changes
  • 7d narrative drift

Data quality gate (required)

Run this gate before finalizing output:

  1. Freshness: include only items with explicit publish/update time; report window in ICT (UTC+7).
  2. Coverage: target >= 3 distinct sources; if < 3, downgrade confidence.
  3. De-duplication: remove near-duplicate headlines by normalized title + URL domain.
  4. Evidence tags: mark each claim as Fact or Inference.
  5. Missingness log: list blocked/paywalled sources and what fallback replaced them.

Shared confidence rubric (required)

Apply this common standard:

  • High: >= 3 distinct sources, <= 24h freshness for core items, and no single-source dominance over 60%.
  • Medium: >= 3 distinct sources with partial freshness gaps or moderate concentration issues, but core themes still cross-confirmed.
  • Low: fewer than 3 distinct sources, stale coverage, or major paywall blocks without reliable fallback.

Always output confidence with:

  1. Source count and source list.
  2. Time window used (ICT UTC+7).
  3. Main uncertainty driver (paywall, missing source, stale timing, or weak cross-confirmation).

Output format (required)

  • Section 1: Top headlines with source URLs.
  • Section 2: Theme counts and tone distribution.
  • Section 3: Vietnam sector spillover map.
  • Section 4: Actionable watchlist (what to monitor next).

Watchlist mode (optional)

If the user provides an ACTIVE_WATCHLIST (tickers), extend Sections 3–4:

  • Add a Watchlist Impact Map that maps macro themes → transmission channel → each ticker.
  • Provide monitoring triggers (what would confirm/negate the impact) and a confidence tag.
  • Never output absolute buy/sell instructions; this skill produces signals and watch items.

Trigger examples

  • "What US macro news overnight could move VN stocks today?"
  • "Summarize Fed/CPI signals and their impact on Vietnam sectors."
  • "Map US rates and USD narrative to Vietnamese equities."

Quality rules

  • Clearly mark inferred impacts as inference.
  • Respect paywalls: use only accessible metadata when full text is unavailable.
  • Avoid over-claiming causality.
  • If source coverage is below threshold, explicitly set confidence to Low.