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Install in OpenClaw
/install news-sentiment
Description
Analyze crypto news sentiment (bullish/bearish). Scan Twitter, news sites, and social media. Get sentiment scores and trading signals.
README (SKILL.md)
📰 News Sentiment Analyzer - 新闻情绪分析
Analyze crypto news and social media sentiment for trading signals.
Features
- 📊 Sentiment scoring (bullish/bearish/neutral)
- 🔍 Multi-source analysis (Twitter, news, Reddit)
- 📈 Trading signal generation
- 🎯 Coin-specific sentiment
- ⚡ Real-time updates
Usage
# Analyze sentiment for a coin
/news-sentiment analyze BTC
# Get market sentiment
/news-sentiment market
# Set alerts
/news-sentiment alert --threshold 0.7
Sentiment Scale
- 0.7 - 1.0: Very Bullish 🚀
- 0.3 - 0.7: Neutral ➡️
- 0.0 - 0.3: Very Bearish 📉
API Sources
- Twitter API (6551.io)
- News APIs
- LLM analysis (Dashscope)
Usage Guidance
Before installing or supplying API keys: (1) Note the skill will send tweet/news text to two external services (ai.6551.io and dashscope.aliyuncs.com); confirm you trust those domains. (2) The package omissions are concerning — TWITTER_TOKEN is required by the code but not declared in registry metadata. Only provide keys that are scoped and easily revoked. (3) Prefer testing in an isolated environment or container, and inspect/modify the Python script if you want to limit what is sent externally (for example, remove or sanitize PII). (4) If you need the 'news sites' or 'Reddit' features, ask the author for a complete, up-to-date implementation and clear documentation of required credentials and endpoints. (5) If you remain unsure, avoid providing real API tokens and run with mock/test tokens first.
Capability Analysis
Type: OpenClaw Skill
Name: news-sentiment
Version: 1.0.2
The news-sentiment skill is a functional tool designed to analyze cryptocurrency market sentiment by fetching data from a Twitter search API (ai.6551.io) and processing it via the Alibaba Dashscope LLM. The Python script (sentiment_analyzer.py) uses standard libraries for network requests and handles API keys through environment variables as expected. No evidence of data exfiltration, malicious command execution, or prompt injection was found; the code logic is transparent and aligns with the stated purpose in SKILL.md and README.md.
Capability Assessment
Purpose & Capability
The skill claims to scan Twitter, news sites, and social media, but the included code only implements a Twitter search + LLM sentiment call; README/SKILL.md mention other sources (news RSS, Reddit) that are not implemented. The registry metadata declares only DASHSCOPE_API_KEY as required, yet the code uses a TWITTER_TOKEN environment variable as well. The declared required binary 'curl' is listed but never used in the shipped Python code. These mismatches suggest sloppy packaging or missing declarations.
Instruction Scope
Runtime behavior (sentiment_analyzer.py) performs network calls to third-party endpoints (ai.6551.io for Twitter search and dashscope.aliyuncs.com for LLM analysis) and will send tweet/news text to the remote LLM service. SKILL.md/README mention these sources but do not declare that user data will be transmitted to these specific domains or explain privacy implications. The instructions and metadata fail to fully enumerate all required env vars (TWITTER_TOKEN is used but not listed), expanding the actual scope of data sent off-host.
Install Mechanism
No install spec is provided (instruction-only install), so nothing arbitrary is downloaded at install time. The only shipped code is a Python script which will run on the host; no archive downloads or remote installers are used.
Credentials
The registry requires only DASHSCOPE_API_KEY, but the code also requires TWITTER_TOKEN to query the ai.6551.io Twitter proxy — this secret is referenced in README but not declared in requires.env. The skill therefore underdeclares secrets it needs. The endpoints are third-party (including a non-official Twitter proxy domain), so providing these credentials would grant access to external services not fully described in metadata.
Persistence & Privilege
The skill does not request always:true, does not modify other skills or system configuration, and has no install-time persistence mechanism. Autonomous invocation is allowed (platform default) but not combined with other high privileges.
How to Use
- Make sure OpenClaw is installed (local or Docker)
- Run the install command in chat:
/install news-sentiment - After installation, invoke the skill by name or use
/news-sentiment - Provide required inputs per the skill's parameter spec and get structured output
Version History
v1.0.2
- Reduced Pro plan monthly price from $14.99 to $1.99.
- No other changes.
v1.0.1
- Added a new freemium pricing section to the documentation.
- Described daily free query limits and updated premium (pro) plan features and details.
v1.0.0
Initial release of News Sentiment Analyzer:
- Analyze crypto news and social media (Twitter, news, Reddit) sentiment.
- Provide bullish, bearish, and neutral sentiment scores.
- Generate trading signals and coin-specific sentiment analysis.
- Support for real-time updates and custom alerts.
- Utilizes APIs and LLM analysis for sentiment scoring.
Metadata
Frequently Asked Questions
What is News Sentiment?
Analyze crypto news sentiment (bullish/bearish). Scan Twitter, news sites, and social media. Get sentiment scores and trading signals. It is an AI Agent Skill for Claude Code / OpenClaw, with 961 downloads so far.
How do I install News Sentiment?
Run "/install news-sentiment" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.
Is News Sentiment free?
Yes, News Sentiment is completely free (open-source). You can download, install and use it at no cost.
Which platforms does News Sentiment support?
News Sentiment is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).
Who created News Sentiment?
It is built and maintained by eddie (@alexbrc20); the current version is v1.0.2.
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