Turn supplied content into three to five bullet points focused on the main takeaways. Use it when you need a short summary or a condensed version of material you want to understand quickly.
Use when the user asks for a summary, TL;DR, or condensed version of any content.
Review the instructions the agent will receive before you install.
Summarize the given content into 3-5 bullet points. Focus on key takeaways.
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Build Java applications with cooperating AI agents using AgentScope Java. Guides asynchronous processing, where waiting tasks do not block execution, plus language model connections, external tools, workflow coordination, error handling, and tests.
Apply related edits across several files using a unified diff, a file describing code changes. Check the patch with Git before applying it, and rebuild rejected patches using the current file contents.
Turn analysis results into charts suited to the question, such as trends, comparisons, or distributions. Save a chart image and the script that generated it, with a short explanation of the findings and relevant caveats.
Locate function and class definitions, usages, and relevant files with ripgrep, using text patterns and file filters. Search Git history to see when text appeared or disappeared and investigate who changed specific lines.
Calculate the count, sum, minimum, maximum, and average of supplied numbers or datasets, then present the results in a clear, structured format. Analysis results can also be saved to a file when requested.
Use a starter template to learn how an agent skill is organized and outline its intended use, required inputs, steps, and output format. Replace the placeholder body with your own working instructions before relying on it.