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Project overview

smolagents offers a compact Python framework for code-writing agents, conventional tool-calling agents, and multi-agent hierarchies, with support for different model providers and Hub sharing. Its CodeAgent expresses actions as Python snippets. Since those snippets are executed, untrusted workloads should use a sandboxed backend; the local Python executor is explicitly not a security boundary.

Project overview

SkillOpt treats a skill document as the trainable state of an otherwise frozen agent. An optimizer model converts scored trajectories into bounded add, delete, or replace edits, and a candidate is accepted only when it strictly improves a held-out validation score. The resulting best_skill.md can be deployed without changing model weights or adding extra model calls at inference time, giving researchers and engineering teams a controlled way to improve reusable agent instructions.