Framework for evaluating and improving agents
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Updated
Jul 30, 2026 - Python
Framework for evaluating and improving agents
A curated, non-BS library of the best resources for building and evaluating AI agents — papers, blogs, talks, tools, benchmarks. Maintained by BenchFlow.
A Universal Platform for Training and Evaluation of Mobile Interaction
A graphical interface for reinforcement learning and gym-based environments.
Interoperating between (Deep) Reiforcement Learning libraries
Gymnasium-style API standard for RL environment creation in JAX
Create new gridworld gym environments easily
Workspace manager for coding agents. Interactively solve and develop Harbor tasks.
Turn any real software into a replayable RL environment for training AI agents — deterministic replay, verifiable rewards, TRL & verifiers adapters.
A lightweight, open-source framework that turns historical GitHub pull requests into reproducible, verifiable software-engineering tasks for training and evaluating coding agents.
Agent-evaluation environments: planted-truth worlds, ungameable graders, calibrated difficulty
Foundry Lite: a public runnable sample of Veyl’s local environment harness for software-engineering agent evals.
Comprehensive AI agent evaluation platform — searchable benchmark catalog, comparison matrices, automated scanner, interactive dashboards, and community-curated best practices for LLM evaluation.
Outcome-verified agent trajectories, benchmarks, and RL environments — with a live leaderboard and a CI gate for your agents. Offline-first, MIT.
Open-source SDK (Apache-2.0): RL environments, conformal calibration, a TRL-compatible reward function, the Lean 4 formal track, and the verifiable/vlabs CLI.
Claude Code Agent Skills for building, red-teaming and tuning agentic RL evaluation environments — a four-skill pattern (guardian, validation-debugger, score-tuner, iteration-loop) plus a 24-point adversarial reviewer.
Surge AI — large-scale human-labeled data for LLM training
Pure Go implementation of the Gymnasium RL environment API. 3–349× faster than Python.
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