dspy-gepa-reflective
This skill should be used when the user asks to "optimize an agent with GEPA", "use reflective optimization", "optimize ReAct agents", "provide feedback metrics", mentions "GEPA optimizer", "LLM reflection", "execution trajectories", "agentic systems optimization", or needs to optimize complex multi-step agents using textual feedback on execution traces.
npx skills add majiayu000/claude-skill-registry --skill dspy-gepa-reflective --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# DSPy GEPA Optimizer ## Goal Optimize complex agentic systems using LLM reflection on full execution traces with Pareto-based evolutionary search. ## When to Use - **Agentic systems** with tool use - When you have **rich textual feedback** on failures - Complex multi-step workflows - Instruction-only optimization needed ## Related Skills - For non-agentic programs: [dspy-miprov2-optimizer](../dspy-miprov2-optimizer/SKILL.md), [dspy-bootstrap-fewshot](../dspy-bootstrap-fewshot/SKILL.md) - Measure improvements: [dspy-evaluation-suite](../dspy-evaluation-suite/SKILL.md) ## Inputs | Input | Type | Description | |-------|------|-------------| | `program` | `dspy.Module` | Agent or complex program | | `trainset` | `list[dspy.Example]` | Training examples | | `metric` | `callable` | Must return `(score, feedback)` tuple | | `reflection_lm` | `dspy.LM` | Strong LM for reflection (GPT-4) | | `auto` | `str` | "light", "medium", "heavy" | ## Outputs | Output | Type | Description | |--------|------|-------------| | `compiled_program` | `dspy.Module` | Reflectively optimized program | ## Workflow ### Phase 1: Define Feedback Metric GEPA requires metrics that return *textual feedback*: ```pytho
- Goal
- When to Use
- Related Skills
- Inputs
- Outputs
- Workflow
- Phase 1: Define Feedback Metric
- Phase 2: Setup Agent
- Phase 3: Optimize with GEPA
- Production Example
- Tool Optimization
- Best Practices
- Limitations
- Official Documentation
What does the dspy-gepa-reflective skill do?
This skill should be used when the user asks to "optimize an agent with GEPA", "use reflective optimization", "optimize ReAct agents", "provide feedback metrics", mentions "GEPA optimizer", "LLM reflection", "execution trajectories", "agentic systems optimization", or needs to optimize complex multi-step agents using textual feedback on execution traces.
How do I install it?
Run `npx skills add majiayu000/claude-skill-registry --skill dspy-gepa-reflective --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From majiayu000/claude-skill-registry, a repository with 534 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.