by microsoft · Agent Tool · ★ 13.1k
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SkillOpt: Executive Strategy for Self-Evolving Agent Skills Train agent skills like you train neural networks — with epochs, (mini-)batchsize, learning rates, and validation gates — but without touching model weights. 🎬 SkillOpt Demo Video https://github.com/user-attachments/assets/eb12d3bc-371c-467f-904d-91b61f339ed7 ▶ Watch the full demo on YouTube Install Requirements: Python 3.10+ Configure API Credentials Azure OpenAI (recommended): bash export AZUREOPENAIENDPOINT="https://your-resource.openai.azure.com/" Option 1: API key auth export AZUREOPENAIAPIKEY="your-key" Option 2: Azure CLI auth (
| Stars | 13,092 |
| Forks | 1,221 |
| Language | Python |
| Category | Agent Tool |
| License | MIT |
| Quality Score | 74.0364977272224/100 |
| Open Issues | 21 |
| Last Updated | 2026-07-18 |
| Created | 2026-05-08 |
| Platforms | python |
| Est. Tokens | ~15k |
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SkillOpt is SkillOpt is a text-space optimizer that trains reusable natural-language skills for frozen LLM agents through trajectory-driven edits, validation-gated updates, and deployable best_skill.md artifacts.. It is categorized as a Agent Tool with 13.1k GitHub stars.
SkillOpt is primarily written in Python. It covers topics such as agent-skills, self-evolving-agents.
You can find installation instructions and usage details in the SkillOpt GitHub repository at github.com/microsoft/SkillOpt. The project has 13.1k stars and 1221 forks, indicating an active community.
SkillOpt is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to SkillOpt on Agent Skills Hub include awesome-claude-skills, awesome-claude-code, antigravity-awesome-skills. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.