# SKILLFOUNDRY: Building Self-Evolving Agent Skill Libraries from Heterogeneous Scientific Resources

arXiv: https://arxiv.org/abs/2604.03964 · HTML: https://mlsanity.com/paper/2604.03964/

## Key facts

- Cited by 42 papers in the map (data through 14 Oct 2026).
- Builds on 17 of its 33 references that are in the map.
- First posted on arXiv 5 Apr 2026.

## Builds on (most cited first, 17 of 17)

- [Toolformer: Language Models Can Teach Themselves to Use Tools](https://mlsanity.com/paper/2302.04761/) (2023)
- [A Survey on Large Language Model based Autonomous Agents](https://mlsanity.com/paper/2308.11432/) (2023)
- [Voyager: An Open-Ended Embodied Agent with Large Language Models](https://mlsanity.com/paper/2305.16291/) (2023)
- [ToolLLM: Facilitating Large Language Models to Master 16000+ Real-world APIs](https://mlsanity.com/paper/2307.16789/) (2023)
- [Gorilla: Large Language Model Connected with Massive APIs](https://mlsanity.com/paper/2305.15334/) (2023)
- [API-Bank: A Comprehensive Benchmark for Tool-Augmented LLMs](https://mlsanity.com/paper/2304.08244/) (2023)
- [Agent Skills for Large Language Models: Architecture, Acquisition, Security, and the Path Forward](https://mlsanity.com/paper/2602.12430/) (2026)
- [EvoSkill: Automated Skill Discovery for Multi-Agent Systems](https://mlsanity.com/paper/2603.02766/) (2026)
- [Reinforcement Learning for Self-Improving Agent with Skill Library](https://mlsanity.com/paper/2512.17102/) (2025)
- [From AI for Science to Agentic Science: A Survey on Autonomous Scientific Discovery](https://mlsanity.com/paper/2508.14111/) (2025)
- [CRISPR-GPT for Agentic Automation of Gene-editing Experiments](https://mlsanity.com/paper/2404.18021/) (2024)
- [CUA-Skill: Develop Skills for Computer Using Agent](https://mlsanity.com/paper/2601.21123/) (2026)
- [ToolUniverse: An open platform for democratizing AI scientists](https://mlsanity.com/paper/2509.23426/) (2025)
- [Paper2Agent: Reimagining Research Papers As Interactive and Reliable AI Agents](https://mlsanity.com/paper/2509.06917/) (2025)
- [Agentic Proposing: Enhancing Large Language Model Reasoning via Compositional Skill Synthesis](https://mlsanity.com/paper/2602.03279/) (2026)
- [Deploy-Master: Automating the Deployment of 50,000+ Agent-Ready Scientific Tools in One Day](https://mlsanity.com/paper/2601.03513/) (2026)
- [ToolRosella: Translating Code Repositories into Standardized Tools for Scientific Agents](https://mlsanity.com/paper/2603.09290/) (2026)

## Built on by (most cited first, 30 of 42)

- [SkillOpt: Executive Strategy for Self-Evolving Agent Skills](https://mlsanity.com/paper/2605.23904/) (2026)
- [MetaSkill-Evolve: Recursive Self-Improvement of LLM Agents via Two-Timescale Meta-Skill Evolution](https://mlsanity.com/paper/2607.05297/) (2026)
- [SkillOps: Managing LLM Agent Skill Libraries as Self-Maintaining Software Ecosystems](https://mlsanity.com/paper/2605.13716/) (2026)
- [Skill Self-Play: Pushing the Frontier of LLM Capability with Co-Evolving Skills](https://mlsanity.com/paper/2607.22529/) (2026)
- [Evolving-RL: End-to-End Optimization of Experience-Driven Self-Evolving Capability within Agents](https://mlsanity.com/paper/2605.10663/) (2026)
- [SkillAudit: Ground-Truth-Free Skill Evolution via Paired Trajectory Auditing](https://mlsanity.com/paper/2606.14239/) (2026)
- [The Last AI Built by Humans: Toward Genuine Recursive Self-Improvement](https://mlsanity.com/paper/2609.11873/) (2026)
- [Co-Evolving Skill Generation and Policy Optimization](https://mlsanity.com/paper/2606.08755/) (2026)
- [Agent Skill Evaluation and Evolution: Frameworks and Benchmarks](https://mlsanity.com/paper/2606.11435/) (2026)
- [SkillCoach: Self-Evolving Rubrics for Evaluating and Enhancing Agentic Skill-Use](https://mlsanity.com/paper/2607.01874/) (2026)
- [Dynamic Agent Skills: A Lifecycle Survey and Taxonomy of Evolving Skill Libraries](https://mlsanity.com/paper/2607.10113/) (2026)
- [Agent Skills Matter: Inferring Proprietary Skills from Execution Trajectories](https://mlsanity.com/paper/2607.25560/) (2026)
- [SoftSkill: Behavioral Compression for Contextual Adaptation](https://mlsanity.com/paper/2606.20333/) (2026)
- [Coalition-Aware Skill Reliability for Self-Evolving Agents](https://mlsanity.com/paper/2608.22610/) (2026)
- [RESOURCE2SKILL: Distilling Executable Agent Skills from Human-Created Multimodal Resources](https://mlsanity.com/paper/2606.29538/) (2026)
- [Workflow-Localized Mechanism Learning: Attribution-Guided Repair and Knowledge Reuse for Structured Agent Skills](https://mlsanity.com/paper/2607.20999/) (2026)
- [SkillReason: Reasoning-Enhanced Agent Skill Retrieval for Implicit User Requests](https://mlsanity.com/paper/2608.08640/) (2026)
- [Scientific Agent Skills: A Library of Procedural Knowledge for Research Agents](https://mlsanity.com/paper/2609.00065/) (2026)
- [Agentic-imodels: Evolving agentic interpretability tools via autoresearch](https://mlsanity.com/paper/2605.03808/) (2026)
- [StatefulDiscovery: Evidence-Calibrated Claim Formation in Open-Ended Scientific Discovery](https://mlsanity.com/paper/2606.11851/) (2026)
- [GuideSkill: Evolving Executable LLM Agent Skills for Guideline-Grounded Clinical Reasoning](https://mlsanity.com/paper/2607.26160/) (2026)
- [SkillHEX: Improving Agent Skills via Hypothesis-Driven Autonomous Exploration and Exploitation](https://mlsanity.com/paper/2608.05628/) (2026)
- [Do Personalized Skills Help Coding Agents? An Empirical Study of Developer Interaction Histories](https://mlsanity.com/paper/2608.10319/) (2026)
- [VCE-Skill: Enhancing Skill Self-Evolution with Version-Change Experience](https://mlsanity.com/paper/2608.16544/) (2026)
- [Towards a Systems Foundation for Agentic Skills: Architecture, Lifecycle, and Security](https://mlsanity.com/paper/2608.29596/) (2026)
- [SkillLift: Learning Dense Rubrics from Sparse Oracles for Efficient Skill Evolution](https://mlsanity.com/paper/2609.15396/) (2026)
- [SkillSeek: Revisiting Agent Skill Retrieval at Marketplace Scale](https://mlsanity.com/paper/2609.38822/) (2026)
- [AgentCo-op: Retrieval-Based Synthesis of Interoperable Multi-Agent Workflows](https://mlsanity.com/paper/2605.20425/) (2026)
- [Self-Supervised Skill Optimization](https://mlsanity.com/paper/2607.28777/) (2026)
- [FinReportBench: Measuring and Improving Institution-Grade Financial Report Generation](https://mlsanity.com/paper/2608.04374/) (2026)

## Abstract (arXiv)

Modern scientific ecosystems are rich in procedural knowledge across repositories, APIs, scripts, notebooks, documentation, databases, and papers, yet much of this knowledge remains fragmented across heterogeneous artifacts that agents cannot readily operationalize. This gap between abundant scientific know-how and usable agent capabilities is a key bottleneck for building effective scientific agents. We present SkillFoundry, a self-evolving framework that converts such resources into validated agent skills, reusable packages that encode task scope, inputs and outputs, execution steps, environment assumptions, provenance, and tests. SkillFoundry organizes a target domain as a domain knowledge tree, mines resources from high-value branches, extracts operational contracts, compiles them into executable skill packages, and then iteratively expands, repairs, merges, or prunes the resulting library through a closed-loop validation process. SkillFoundry produces a substantially novel and internally valid skill library, with 71.1% of mined skills differing from existing skill libraries such as SkillHub and SkillSMP. We demonstrate that these mined skills improve coding agent performance on five of the six MoSciBench datasets. We further show that SkillFoundry can design new task-specific skills on demand for concrete scientific objectives, and that the resulting skills substantially improve performance on two challenging genomics tasks: cell type annotation and the scDRS workflow. Together, these results show that automatically mined skills improve agent performance on benchmarks and domain-specific tasks, expand coverage beyond hand-crafted skill libraries, and provide a practical foundation for more capable scientific agents.