agenta
About
Agenta is a self-hosted platform for managing and evaluating LLM prompts through versioning, A/B testing, and metric tracking. It provides a playground interface and experiment tracking to help developers deploy optimized prompts with confidence. Use it for systematic prompt engineering, comparison, and testing within your MLOps workflow.
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/agentaCopy 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.
prompt-engineering-calculation
OtherThis skill provides structured calculation capabilities within Claude, showing step-by-step mathematical reasoning. It's designed for developers needing transparent computational workflows in AI-assisted coding tasks. Use it when you require verifiable calculations or want to demonstrate mathematical problem-solving processes.
