prompt-engineering-summary
About
This skill provides specialized techniques for creating effective summarization prompts within Claude. It helps developers generate concise, accurate summaries of various content types by offering structured prompt templates and best practices. Use it when you need to implement reliable text summarization features in your applications.
Quick Install
Claude Code
Recommendednpx skills add vamseeachanta/workspace-hub -a claude-code/plugin add https://github.com/vamseeachanta/workspace-hubgit clone https://github.com/vamseeachanta/workspace-hub.git ~/.claude/skills/prompt-engineering-summaryCopy and paste this command in Claude Code to install this skill
GitHub Repository
Related Skills
agenta-1-prompt-versioning-and-management
OtherThis skill enables version control and management for AI prompts, allowing developers to track changes, compare iterations, and maintain prompt history. It provides tools to create versioned prompt templates with parameters like style and length constraints. Use this when you need reproducible, auditable prompt workflows across different model versions or team collaborations.
agenta-1-prompt-versioning-strategy
OtherThis skill provides best practices for versioning AI prompts using semantic versioning and structured metadata. It helps developers track prompt changes, maintain changelogs, and organize different prompt versions systematically. Use this when implementing version control for production prompts in AI applications.
agenta
OtherAgenta is a self-hosted platform for managing and evaluating LLM prompts. It enables developers to version prompts, run A/B tests, and track experiments with evaluation metrics. Use it to systematically test and deploy prompt changes with confidence.
pandasai
Otherpandasai enables conversational data analysis by letting developers query pandas DataFrames using natural language. It supports chart generation, transformation explanations, and multi-table analysis, powered by various LLM backends. Use this skill to quickly build exploratory data interfaces or ask plain-English questions about your datasets.