Where is the processed data stored?

All extracted data is stored locally on your machine in a CSV file and Markdown proposal documents, ensuring your research remains private.

Does it delete my Twitter bookmarks after processing?

By default, the skill unbookmarks processed items to keep your list fresh, but you can override this behavior using the --keep-bookmarks flag.

Does it handle external links within tweets?

Yes, the processor fetches content from linked blog posts, GitHub repositories, and documentation to provide deeper context for skill proposals.

How does the skill identify a 'skill candidate'?

The skill analyzes tweet content and assigns a relevance score from 1-5; items scoring 4 or 5 that contain actionable patterns or reusable techniques are automatically flagged as candidates.

Can I process specific categories of bookmarks?

Yes, the skill supports a --category flag (e.g., AI-LLM, DevOps) to focus your processing on specific domains of interest.

Twitter Bookmark Processor

Name: Twitter Bookmark Processor
Author: bigadamknight

bybigadamknight

소셜 미디어 관리

Automates the extraction and transformation of Twitter bookmarks into actionable skill candidates and implementation proposals.

소개

This skill streamlines the research-to-implementation pipeline by fetching bookmarked tweets, analyzing their content for technical relevance, and automatically generating detailed skill specifications. It categorizes information into domains like AI-LLM and DevOps, maintains a persistent CSV database of insights, and extracts valuable resources from external links to help developers turn fleeting social media inspirations into concrete, production-ready coding patterns.

주요 기능

Automatic resource extraction from linked blog posts and GitHub repositories
Generation of structured Markdown skill proposals with implementation notes
Intelligent relevance scoring to identify high-value skill candidates
Local CSV tracking for long-term knowledge management and duplicate prevention
Automated fetching and categorization of Twitter bookmarks via API
0 GitHub stars

사용 사례

Managing high-volume technical bookmarks without manual sorting
Discovering new AI patterns or agent workflows from technical Twitter feeds
Building a personal repository of implementation-ready coding techniques

소개

주요 기능

Automatic resource extraction from linked blog posts and GitHub repositories
Generation of structured Markdown skill proposals with implementation notes
Intelligent relevance scoring to identify high-value skill candidates
Local CSV tracking for long-term knowledge management and duplicate prevention
Automated fetching and categorization of Twitter bookmarks via API
0 GitHub stars

사용 사례

Managing high-volume technical bookmarks without manual sorting
Discovering new AI patterns or agent workflows from technical Twitter feeds
Building a personal repository of implementation-ready coding techniques