The 100 line AI agent that solves GitHub issues or helps you in your command line. Radically simple, no huge configs, no giant monorepo—but scores >74% on SWE-bench verified!
Turn any repository into verifiable RL environments for coding agents - Harbor tasks you can train on, evaluate and share on the Hugging Face Hub
How many bugs can LMs find & fix in large codebases?
[NeurIPS 2025 D&B Spotlight] Scaling Data for SWE-agents
SWE-Bench Pro: Can AI Agents Solve Long-Horizon Software Engineering Tasks?
Most coding agents grep and glob raw source into LLM's context window and hope the model is smart. Benzi compiles your codebase into a queryable map of calls, data flow, control flow and class hierarchy first; then it reads, explains, runs, edits and verifies your code using it. Includes a runtime tracer. 82.4% SWE-bench Verified for < $13.
A benchmark for testing whether coding agents can resolve engineering tasks in scientific software
JLens Evolve v3: evidence-centric evolution platform (autonomous Teacher + local Qwen + official SWE-bench native evaluation). Branch codex/v3-evolution-10000 carries transport resilience, Router-key normalization, per-round temperature beam, and baseline fail-soft.
Coding Agent Runtime & Evaluation Harness for controlled repository-level software repair