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Skill2Env: Capability-Oriented Environment Synthesis from Skills for General Agents

Hugging Face daily papersby Weiyi Xu, Xiaowen Yang, Wen Da ()1 min read1 · 1 read
AI summary · grok-4.7Summaries by Vani AI

Skill2Env synthesizes executable agent environments from skills; fine-tuning on 1,500 trajectories improves benchmarks.

Skill2Env turns skills—domain knowledge, procedures, and tool instructions—into executable tasks and environments for agent post-training. Reusable difficulty patterns become blueprints covering objectives, challenges, environment facts, information boundaries, and acceptance criteria, which guide instructions, substrates, workspaces, and rubric evaluators. Iterative Task Hardening uses solver traces to strengthen insufficiently difficult tasks. Supervised fine-tuning on 1,500 high-scoring trajectories produces consistent gains across a broad range of agent benchmarks.

Key facts
  • Starts from skills and capability demands rather than hand-built environments.
  • Blueprints specify objectives, challenges, facts, boundaries, and acceptance criteria.
  • Iterative Task Hardening revises weak tasks using solver execution evidence.
  • SFT on 1,500 trajectories improves results across agent benchmarks.
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From the original article

1 min read at huggingface.co

Executable environments are critical for post-training agents on tasks that require tool use and multi-step interaction, but constructing executable tasks together with their environments remains difficult to scale.

Hugging Face daily papers

By Weiyi Xu, Xiaowen Yang, Wen Da · huggingface.co

Read the full article at Hugging Face daily papers

A short excerpt; the article and its images belong to the publisher. Summary, key facts and assessment above are AI-written from the article and can be wrong.