Gepa Tuned Sql Agent
Description
Self-debugging SQL agent with GEPA evolutionary prompt optimization — no fine-tuning, just context engineering
Installation
This entry records only its repository, not the path inside it, so there is no
exact command to give. Open the source below and copy the folder into
~/.claude/skills/, or the file into ~/.claude/agents/.
README
SQL Agent
Self-Debugging · GEPA Prompt Evolution · RL Environment
An AI SQL agent that gets measurably better over time — without retraining the model.
Quick Start · How It Works · Architecture · RL Environment · Research
An AI SQL agent that **gets measurably better over time** — without retraining or fine-tuning the model. It combines three research ideas running together in one app:
- Self-Debug Loop — the agent critiques and fixes its own SQL errors, no human in the loop
- GEPA Prompt Evolution — after user feedback, an LLM reflects on failures and evolves the system prompt
- Mini-RL Environment — a LinUCB contextual bandit learns which repair strategy works best for each error type
The result: pure prompt + context engineering. No model weights needed.
Quick Start
git clone htRelated Skills
mcp-server-postgres
Read-only PostgreSQL database access.
mcp-server-sqlite
SQLite database interaction and querying.
mcp-server-google-maps
Google Maps integration for location data.
Bitbucket Data Center
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Automatically analyze CSV files and generate comprehensive insights with visualizations
OpenViking
Self-evolving Context Database for AI Agents. Unify Agent Memory, Knowledge RAG and Skills.
