tech-news-digest
Generate tech news digests with unified source model, quality scoring, and multi-format output. Six-source data collection from RSS feeds, Twitter/X KOLs, GitHub releases, GitHub Trending, Reddit, and web search. Pipeline-based scripts with retry mechanisms and deduplication. Supports Discord, email, and markdown templates.
Why use this skill?
Efficiently aggregate, score, and format tech news from RSS, Twitter, GitHub, and more. Create custom, high-quality automated digests with OpenClaw.
Install via CLI (Recommended)
clawhub install openclaw/skills/skills/dinstein/tech-news-digestWhat This Skill Does
The tech-news-digest skill is a professional-grade automated intelligence agent designed to aggregate, score, and format technology news into a structured digest. It serves as a central hub for monitoring industry updates by pulling data from six diverse channels: RSS feeds, Twitter/X KOLs, GitHub releases, GitHub Trending repositories, Reddit discussions, and automated web searches. The system employs a sophisticated pipeline-based approach that includes intelligent deduplication and a quality scoring engine, ensuring that only the most relevant and high-value information reaches the user. Whether you need to track specific AI foundation model updates, open-source project releases, or broader tech trends, this skill automates the drudgery of manual monitoring.
Installation
Installation is straightforward via the ClawHub CLI. To integrate this into your OpenClaw environment, execute the following command in your terminal:
clawhub install openclaw/skills/skills/dinstein/tech-news-digest
Once installed, you must initialize your local environment by copying the default configurations from config/defaults/ to your local workspace/config/ directory. Ensure you have the necessary API keys (such as TAVILY_API_KEY, BRAVE_API_KEY, or GITHUB_TOKEN) exported in your environment variables to unlock full functionality. Refer to the system documentation to configure your specific news sources and interest topics in the respective JSON files.
Use Cases
- Executive Briefings: Automatically generate a nightly or weekly summary of AI and SaaS market shifts for leadership teams.
- Open Source Tracking: Keep tabs on newly trending repositories or specific version releases for libraries your tech stack relies upon.
- Competitive Intelligence: Monitor competitor blogs, CEO Twitter feeds, and public discourse on Reddit to keep a finger on the pulse of the market.
- Research Automation: Populate markdown-based newsletters or Slack/Discord channels with pre-curated high-quality technical content without manual copy-pasting.
Example Prompts
- "Run the tech-news-digest pipeline for the last 24 hours focusing on LLM updates and export it as a markdown file to my workspace."
- "Generate a tech news summary based on my custom topics.json configuration and send it to our team Discord channel using the latest template."
- "Check for new GitHub releases in the 'ai-agent' category and summarize the top 5 most impactful updates found in the last 48 hours."
Tips & Limitations
To maximize the utility of this skill, prioritize defining a clean topics.json file with specific must_include and exclude keywords to reduce noise. Because the tool relies on external APIs (Twitter, Brave, GitHub), ensure your rate limits are managed by providing multiple API keys where supported, such as with Brave Search. Note that the quality scoring is heuristic-based; reviewing the output periodically ensures your configuration settings are effectively filtering for the content depth you require. Be mindful of the freshness setting when running your pipeline, as narrow windows might miss long-running discussions on platforms like Reddit.
Metadata
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Find the right skillPaste this into your clawhub.json to enable this plugin.
{
"plugins": {
"official-dinstein-tech-news-digest": {
"enabled": true,
"auto_update": true
}
}
}Tags(AI)
Flags: network-access, file-write, file-read, external-api
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tech-digest
Generate tech news digests with unified source model, quality scoring, and multi-format output. Four-layer data collection from RSS feeds, Twitter/X KOLs, GitHub releases, and web search. Pipeline-based scripts with retry mechanisms and deduplication. Supports Discord, email, and markdown templates.