Dapper – Debug Adapter for Python
DAP implementation for Python, but debugpy and Pdb already handle this.
DAP integration cuts agent debug cycles from 6 prints to 1 breakpoint.
Developers using AI coding agents
TL;DR: I gave my agent a debugger and saw it go from 5-6 print-debug cycles down to 1 targeted stop.
I built a small CLI that wraps the Debug Adapter Protocol and exposes basic debugger actions so agents can call them directly. Each command blocks until execution pauses, then returns the full context.
The CLI is just a thin layer. The useful part is a debugging “skill” on top that teaches the agent how to debug methodically with it, define clear hypotheses, validate/invalidate them, etc.
Supports Python, Go, Node/TypeScript, Rust, and C/C++.
DAP implementation for Python, but debugpy and Pdb already handle this.
Breakpoints and interactive shell for GitHub Actions when act only gives you log dumps.
The ? operator macro attaching breakpoints to error propagation is genuinely clever.
Execution anchors enable replay-from-step debugging for non-deterministic agent runs.
Record production Python bugs and step backwards from crash to cause in VS Code.
Machine-parseable traces for LLM agents when pdb and breakpoint() are useless.