Guide users who want to optimize their LLM prompts. We will interact with them, understanding their datasets and grader requirements, and finally writing DSPy code to optimize their prompt (using a custom implementation of the GEPA algorithm).
EnglishMigrate DSPy GEPA usage in DSPy from the original to gepa-observable. This makes it possible for teams to clearly review each iteration and the lineage to understand how their prompt is evolving. The repository offers a web dashboard for monitoring, but requires a custom GEPA fork that provides custom observers and LM call logging. Use when developers want to add observability to GEPA optimization.
English
AGENT SKILLS ATLASIncludes Observable Gepa Migration and other workflows.
Claude Code
Codex
Cursor
GitHub Copilot
Gemini CLISupported by the Atlas install prompt. Skill-specific requirements vary.
Pack stats
What’s included
Gepa Demo
Guide users who want to optimize their LLM prompts. We will interact with them, understanding their datasets and grader requirements, and finally writing DSPy code to optimize their prompt (using a custom implementation of the GEPA algorithm).
Observable Gepa Migration
Migrate DSPy GEPA usage in DSPy from the original to gepa-observable. This makes it possible for teams to clearly review each iteration and the lineage to understand how their prompt is evolving. The repository offers a web dashboard for monitoring, but requires a custom GEPA fork that provides custom observers and LM call logging. Use when developers want to add observability to GEPA optimization.
Quick start
- Choose your skills. Select individual skills above, or choose the entire pack.
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Try it with your agent
After installation, start with a request like:
Use the Gepa Demo skill to help with my task.
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