Summarize content from URLs, files, codebases, and conversations.
npx skills add https://github.com/phuetz/code-buddy --skill summarize-phuetz
Please help me install this Agent Skill. Skill: summarize Source: https://github.com/phuetz/code-buddy/tree/main/.codebuddy/skills/bundled/summarize Command: npx skills add https://github.com/phuetz/code-buddy --skill summarize-phuetz
This Skill summarizes or extracts content from URLs, files, codebases, and conversations, saving time and enabling quick comprehension.
Use the summarize skill to produce a concise summary of the article located at https://example.com/news
High-intent search queries and answers about installing and using this skill.
To get a TLDR for a web article or document, you provide the URL or file to a summarization tool, which extracts main ideas and removes noise to deliver a concise, structured summary.
Yes, you can extract key decisions and action items from a long chat transcript by applying text summarization to the conversation. It identifies important points and requirements to give you a quick digest of the discussion.
The best way to summarize a large codebase is to use an automated extraction tool that processes the code project to identify main ideas and output a structured, concise summary of its functionality and structure.
Automated text summarization works directly on raw URLs by fetching the web article content, removing noise, and applying generic text processing to output a structured TLDR without needing manual text copying.
Limitations of generic text processing for document extraction include potential loss of nuanced context or specific formatting, as the mechanism focuses on identifying main ideas and removing noise to generate concise summaries.
one-ieExtract YouTube subtitles into clean text transcripts for LLM processing.
wangjiawei508Convert Markdown-formatted text into structured Word documents.
TTAWDTTIndex and retrieve relevant passages from user-uploaded attachments using attachment_search.
Nathanto-aiDelegate context-expensive tasks to read-only subagents and return concise digests.
