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Removes extraneous information (source, author, etc.) from link titles using LLM intelligence.
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Basierend auf der SOC-Berufsklassifikation
Appends relevant hashtags to journal entries based on content analysis. Intended for LLM execution.
Organizes tagged links from a source file into the daily journal structure.
Removes timestamps and decodes URLs in the specified markdown file.
Checks if the daily journal file exists for a given date. If not, creates it using the 'Daily framework' template.
End-to-end workflow to process daily news digest: ensures journal, cleans links, tags, and organizes them.
Empties the content of a specified file. Use with caution.
| name | clean_link_titles |
| description | Removes extraneous information (source, author, etc.) from link titles using LLM intelligence. |
This skill uses an LLM to intelligently clean news link titles by removing unnecessary metadata such as source names, author names, and site branding, while preserving the core headline.
TempLinks.md).[Title](URL), identify and remove extraneous suffixes or prefixes. | SiteName (e.g., | TechNews, | iThome, - MoneyDJ). - Source Name (especially if it looks like a brand).(Source) at the end.【Source】 or [Source] if it's clearly a publisher tag.Author Name: if present at start.Input:
- [NVIDIA stock jumps 5% | CNBC](...)
- [【TechCrunch】OpenAI releases new model](...)
- [Review: iPhone 16 | The Verge](...)
Output:
- [NVIDIA stock jumps 5%](...)
- [OpenAI releases new model](...)
- [Review: iPhone 16](...)