SkillOpt v0.1.0: initial release
- Skill optimization framework with training loop analogy - 11 benchmarks, 4 model backends (Azure OpenAI, Claude, Codex, Qwen) - WebUI for browser-based training control - Pluggable architecture for extending benchmarks and backends
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site_name: SkillOpt Documentation
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site_url: https://microsoft.github.io/SkillOpt
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site_description: "SkillOpt: Agentic Skill Optimization via Reflective Training Loops"
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repo_url: https://github.com/microsoft/SkillOpt
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repo_name: microsoft/SkillOpt
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text: Inter
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code: JetBrains Mono
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nav:
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- Home: index.md
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- Getting Started:
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- Installation: guide/installation.md
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- First Experiment: guide/first-experiment.md
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- Configuration: guide/configuration.md
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- Core Concepts:
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- Training Loop: guide/training-loop.md
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- Skill Document: guide/skill-document.md
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- Deep Learning Analogy: guide/dl-analogy.md
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- Extension Guides:
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- Add a New Benchmark: guide/new-benchmark.md
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- Add a New Model Backend: guide/new-backend.md
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- Reference:
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- Configuration Reference: reference/config.md
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- CLI Reference: reference/cli.md
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- API Reference: reference/api.md
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- Contributing: contributing.md
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plugins:
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