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news-sentiment-analyst新闻情绪分析师

Agent Skill

news-sentiment-analyst 用于补充开发相关能力,适合在 OpenClaw 中需要让 Agent 承接开发相关任务时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

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安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

MIT-0

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:news-sentiment-analyst(新闻情绪分析师)
来源仓库:https://github.com/finskills/news-sentiment-analyst
安装命令:
openclaw skills install news-sentiment-analyst
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 OpenClaw 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

ClawHubOpenClaw
openclaw skills install news-sentiment-analyst

简介

使用 Finskills API 将金融新闻情绪汇总并分类为市场和个股的风险开启/风险关闭信号。

SKILL.md

name
News Sentiment Analyst
version
1.0.3
description
Aggregate and classify financial news sentiment into Risk-On / Risk-Off signals for market and individual stocks using the Finskills API.
author
finskills
metadata
openclaw
requires
env
primaryEnv
FINSKILLS_API_KEY
homepage
https://github.com/finskills/news-sentiment-analyst

News Sentiment Analyst

Aggregate and analyze financial news and market sentiment using the Finskills API news endpoints. Extract actionable signals from headlines, classify sentiment by ticker and sector, and surface market-moving catalysts — so you can react to information before it's fully priced in.


Setup

API Key requiredRegister at https://finskills.net to get your free key. Header: X-API-Key: <your_api_key>

Get your API key: Register at https://finskills.net — free tier available, Pro plan unlocks real-time quotes, history, and financials.

When to Activate This Skill

Activate when the user:

  • Asks "what's happening in the market today?"
  • Wants to check sentiment for a specific stock before trading
  • Asks about recent news for a company or sector
  • Wants to understand why a stock moved (news catalyst identification)
  • Asks to summarize financial media themes or narratives

Data Retrieval — Finskills API Calls

1. General Financial News Feed

GET https://finskills.net/v1/free/news/finance

Extract: title, summary, source, published timestamp, sentiment score (if provided), tickers mentioned

2. Latest News (Pro — broader coverage)

GET https://finskills.net/v1/news/latest

Extract: same fields as above, with more sources and more recent latency

3. Symbol-Specific News

GET https://finskills.net/v1/news/by-symbol/{SYMBOL}

Extract: news articles filtered to a specific stock — title, summary, sentiment, source, timestamp


Analysis Workflow

Step 1 — News Aggregation

Collect and deduplicate articles across sources. Sort by:

  1. Recency (most recent first)
  2. Estimated impact (market-moving stories: Fed decisions, earnings, M&A, macro data)

Source trust tiers:

  • Tier 1 (high authority): Reuters, Bloomberg, WSJ, FT, CNBC
  • Tier 2 (solid): MarketWatch, Barron's, Seeking Alpha (News), Yahoo Finance
  • Tier 3 (background): General blogs, press releases

Step 2 — Market-Wide Sentiment Classification

For each article, classify:

SignalBearishNeutralBullish
Fed/PolicyRate hike surprise, hawkish tonePolicy hold expectedRate cut, dovish language
EarningsMiss + lowered guidanceBeat, maintained guidanceBeat + raised guidance
Economic DataWeak jobs, poor PMIMixed dataStrong GDP, low unemployment
GeopoliticsNew conflicts, trade warOngoing tensionsPeace/trade deal
M&ADeal collapse, hostile bidRumored dealsFriendly acquisition at premium
MacroRecession signalsSoft landing narrativeGrowth acceleration

Assign an overall Market Sentiment Score for the day:

  • 🟢 Risk-On: Majority of market-moving news is bullish
  • 🟡 Mixed: Conflicting signals across sectors
  • 🔴 Risk-Off: Majority bearish, defensive positioning

Step 3 — Ticker/Sector Sentiment Map

Group articles by stocks/sectors mentioned:

  • For each ticker mentioned 2+ times: assign net sentiment (positive/negative/neutral)
  • Identify sectors with bullish news clusters (potential sector momentum)
  • Identify sectors with bearish news clusters (potential sector rotation out)

Step 4 — Catalyst Identification

Flag high-impact event types:

  • 🔴 Earnings: Beat/miss/guidance change
  • 🔴 Merger/Acquisition: Target premium, integration cost
  • 🔴 FDA/Regulatory: Drug approval, regulatory violation
  • 🔴 Management change: CEO/CFO departure or appointment
  • 🟡 Analyst action: Upgrade, downgrade, price target change
  • 🟡 Macro data: CPI, NFP, GDP, FOMC minutes
  • 🟡 Insider activity: Large insider buy/sell (link to insider-trade-tracker)
  • 🟢 Buyback announcement: Often positive signal
  • 🟢 Contract win / Partnership: Revenue catalyst

Step 5 — Summary and Recommendations

Generate:

  1. 3-bullet market summary (most important macro/market stories)
  2. Top 3 bullish catalysts (specific stocks/sectors)
  3. Top 3 bearish risks (specific stocks/sectors)
  4. Sector rotation signal: which sectors are in/out of favor today

Output Format

╔══════════════════════════════════════════════════════╗
║     NEWS & SENTIMENT REPORT  —  {DATE} {TIME}       ║
╚══════════════════════════════════════════════════════╝

🌡️ OVERALL MARKET SENTIMENT: {RISK-ON / MIXED / RISK-OFF}
   Sources analyzed: {N}  |  Timeframe: Last {hours}h

📌 TOP MARKET THEMES
  1. {Most important market-moving story}
  2. {Second important story}
  3. {Third important story}

📈 BULLISH CATALYSTS
  🟢 {TICKER/SECTOR}: {headline}
     Source: {source} | Sentiment: Positive | Impact: {High/Medium/Low}
     Signal: {one-line interpretation}

  🟢 {TICKER/SECTOR}: {headline}
     ...

📉 BEARISH RISKS
  🔴 {TICKER/SECTOR}: {headline}
     Source: {source} | Sentiment: Negative | Impact: {High/Medium/Low}
     Signal: {one-line interpretation}

  🔴 {TICKER/SECTOR}: {headline}
     ...

🏭 SECTOR SENTIMENT MAP
  Sector          Sentiment   Key Driver
  Technology      🟢 Bullish  AI chip demand stories, NVDA + SMCI positive
  Energy          🔴 Bearish  Crude oil supply glut concerns
  Financials      🟡 Mixed    Rate cut hopes vs. credit risk headlines
  Healthcare      🟡 Neutral  No major catalysts today
  ...

🔍 STOCK-SPECIFIC NEWS
  [If user specified a ticker]
  {TICKER} — {N} stories in last 24h:
    {timestamp}: {headline} [{Positive/Negative/Neutral}]
    {timestamp}: {headline} [{sentiment}]
  Net Sentiment: {Positive/Mixed/Negative}

⚡ HIGH-IMPACT EVENTS TO WATCH
  • {Event 1} — scheduled {date/time}
  • {Event 2} — expected announcement

Limitations

  • News latency varies by source; some articles may be 15–60 minutes delayed.
  • Sentiment classification is AI-assisted and may miss nuanced or sarcastic language.
  • This skill surfaces information signals, not guaranteed trading signals.
  • Always verify high-impact news with primary sources (company IR, official filings).

适合场景

01

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02

用户想查找某类 Agent Skill 时

03

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04

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能力 5

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

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安装前确认

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