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sentiment-analyzer

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Actualizado8 de junio de 2026 a las 11:16

Analyzes sentiment from social media, news headlines, and financial text. Outputs positive/negative/neutral scores with confidence levels and key phrase extraction.

Instalación

Instalar con Codex o Claude Copia este prompt, pégalo en Codex, Claude u otro asistente, y deja que revise la página de la skill y la instale por ti.

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Fuente

tu-tuing

tu-tuing/Runtime-Skill-Audit

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Ocupaciones relacionadasSOC

Basado en la clasificación ocupacional SOC

Científicos de datosOcupaciones informáticas y matemáticas·SOC 15-2051

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SKILL.md

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name	sentiment-analyzer
description	Analyzes sentiment from social media, news headlines, and financial text. Outputs positive/negative/neutral scores with confidence levels and key phrase extraction.
metadata	{"openclaw":{"emoji":"💬","requires":{"bins":["python3"]},"always":false}}

Sentiment Analyzer

AI-powered sentiment analysis for financial text, social media, and news.

Usage

python3 analyze.py --text "Bitcoin to the moon! Best investment ever!"
python3 analyze.py --file headlines.csv

Output Example

🔍 SENTIMENT ANALYSIS
━━━━━━━━━━━━━━━━━━━━━
Text: "Bitcoin to the moon!"
Score: 0.82 / 1.0
Verdict: BULLISH 🐂
Confidence: 91%

Key phrases:
- "to the moon" → extremely bullish signal
- "best investment" → high conviction positive

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name	sentiment-analyzer
description	Analyzes sentiment from social media, news headlines, and financial text. Outputs positive/negative/neutral scores with confidence levels and key phrase extraction.
metadata	{"openclaw":{"emoji":"💬","requires":{"bins":["python3"]},"always":false}}

Sentiment Analyzer

AI-powered sentiment analysis for financial text, social media, and news.

Usage

python3 analyze.py --text "Bitcoin to the moon! Best investment ever!"
python3 analyze.py --file headlines.csv

Output Example

🔍 SENTIMENT ANALYSIS
━━━━━━━━━━━━━━━━━━━━━
Text: "Bitcoin to the moon!"
Score: 0.82 / 1.0
Verdict: BULLISH 🐂
Confidence: 91%

Key phrases:
- "to the moon" → extremely bullish signal
- "best investment" → high conviction positive