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ai-image-digest

Compile daily AI image digests from multiple English and Chinese feeds.

Updated Feb 6, 2026
Search Tags:#automation#ai#deduplication#html-generation#digest#data-collection
One-click install
npx skills add https://github.com/glfruit/gorin-skills --skill ai-image-digest
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: ai-image-digest
Source: https://github.com/glfruit/gorin-skills/tree/main/openclaw/ai-image-digest
Command: npx skills add https://github.com/glfruit/gorin-skills --skill ai-image-digest

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Aggregates daily AI industry content from multiple sources into a concise, consistently formatted digest, eliminating manual curation and ensuring up-to-date visibility.

Core Features & Use Cases

  • Multi-source ingestion: pulls from English follow-builders feeds (X, podcasts, blogs) and Chinese sources via Tavily to cover a broad AI landscape.
  • De-duplication and relevance: filters duplicates and low-signal items to keep the digest focused and high quality.
  • Output generation: renders an HTML digest with screenshots and a plain-text digest, plus a JSON meta file for downstream automation.
  • Operational readiness: maintains state across runs and handles errors with structured logging.

Quick Start

Run the digest pipeline to fetch sources, generate daily HTML and TXT, and prepare metadata for delivery.

Frequently Asked Questions about ai-image-digest

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I automate daily AI image digest compilation from multiple feeds?▼

Automating a daily AI image digest is done by pulling from English builder feeds and Chinese sources via Tavily, then applying deduplication and relevance filtering. The pipeline renders HTML and TXT outputs while maintaining state and handling errors with structured logging.

What is the best way to deduplicate AI industry content collected from multiple sources?▼

Deduplicating AI industry content involves filtering duplicate and low-signal items during the multi-source ingestion phase. This ensures the generated digest remains focused and high quality before rendering the final HTML and plain-text outputs.

Does Tavily work with Chinese AI sources for automated data collection?▼

Tavily works with Chinese AI sources to cover a broad AI landscape alongside English follow-builder feeds from X, podcasts, and blogs. It ingests this multi-source data to compile a concise, consistently formatted daily digest.

Can I generate both HTML and plain-text digests from automated data collection pipelines?▼

You can generate both HTML and plain-text digests from automated data collection pipelines. The process renders an HTML digest with screenshots and a TXT file, plus a JSON meta file for downstream automation, ensuring consistently formatted outputs.

How does stateful tracking work for daily digest pipelines that fail mid-run?▼

Stateful tracking for daily digest pipelines maintains state across runs and handles errors with structured logging. This operational readiness ensures that automated data collection and HTML generation processes can recover and track progress without losing previous digest states.

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