[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M6CD8BBGDHSWVRKMJ09PXBAW":3,"skill-same:01M6CD8BBGDHSWVRKMJ09PXBAW":101},{"skillNo":4,"name":5,"nameZh":6,"description":7,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":16,"categories":17,"keywords":18,"publishedAt":33,"linkOnly":34,"markdownContent":35,"markdownBody":36,"frontMatter":37,"refName":44,"commitSha":45,"skillDirectory":46,"forksCount":47,"repositoryHtmlUrl":48,"repositoryHomepageUrl":6,"ownerHtmlUrl":49,"ownerBlogUrl":50,"ownerDescription":51,"updatedAt":52,"install":53,"resources":66},"01M6CD8BBGDHSWVRKMJ09PXBAW","adapting-transfer-learning-models",null,"This skill automates the adaptation of pre-trained machine learning models using transfer learning techniques. it is triggered when the user requests assistance with fine-tuning a model, adapting a pre-trained model to a new dataset, or performing...","BbgnsurfTech\u002Fclaude-skills-collection","BbgnsurfTech","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F59598605?v=4","01M6C5ZT4G3G4QPQB64QDVW438","Bbgnsurf Technologies","01M6C5ZT8JN4VWSZZH3DD8J4EG",29,"MIT","https:\u002F\u002Fgithub.com\u002FBbgnsurfTech\u002Fclaude-skills-collection\u002Fblob\u002Fmain\u002Fplugins\u002Fclaude-code-plugins-plus\u002Fplugins\u002Fai-ml\u002Ftransfer-learning-adapter\u002Fskills\u002Ftransfer-learning-adapter\u002FSKILL.md",[],[19,20,21,22,23,24,25,26,27,28,29,30,31,32],"transfer","learning","models","Adapting Transfer Learning Models","machine learning","Fine-Tuning","tuning","Bash","model","grep","read","write","edit","user","2026-11-10 10:12:30",false,"---\ndescription: This skill automates the adaptation of pre-trained machine learning models\n  using transfer learning techniques. it is triggered when the user requests assistance\n  with fine-tuning a model, adapting a pre-trained model to a new dataset, or performing...\nallowed-tools:\n- Read\n- Write\n- Edit\n- Grep\n- Glob\n- Bash\nname: adapting-transfer-learning-models\nlicense: MIT\n---\n## Overview\n\nThis skill streamlines the process of adapting pre-trained machine learning models via transfer learning. It enables you to quickly fine-tune models for specific tasks, saving time and resources compared to training from scratch. It handles the complexities of model adaptation, data validation, and performance optimization.\n\n## How It Works\n\n1. **Analyze Requirements**: Examines the user's request to understand the target task, dataset characteristics, and desired performance metrics.\n2. **Generate Adaptation Code**: Creates Python code using appropriate ML frameworks (e.g., TensorFlow, PyTorch) to fine-tune the pre-trained model on the new dataset. This includes data preprocessing steps and model architecture modifications if needed.\n3. **Implement Validation and Error Handling**: Adds code to validate the data, monitor the training process, and handle potential errors gracefully.\n4. **Provide Performance Metrics**: Calculates and reports key performance indicators (KPIs) such as accuracy, precision, recall, and F1-score to assess the model's effectiveness.\n5. **Save Artifacts and Documentation**: Saves the adapted model, training logs, performance metrics, and automatically generates documentation outlining the adaptation process and results.\n\n## When to Use This Skill\n\nThis skill activates when you need to:\n- Fine-tune a pre-trained model for a specific task.\n- Adapt a pre-trained model to a new dataset.\n- Perform transfer learning to improve model performance.\n- Optimize an existing model for a particular application.\n\n## Examples\n\n### Example 1: Adapting a Vision Model for Image Classification\n\nUser request: \"Fine-tune a ResNet50 model to classify images of different types of flowers.\"\n\nThe skill will:\n1. Download the ResNet50 model and load a flower image dataset.\n2. Generate code to fine-tune the model on the flower dataset, including data augmentation and optimization techniques.\n\n### Example 2: Adapting a Language Model for Sentiment Analysis\n\nUser request: \"Adapt a BERT model to perform sentiment analysis on customer reviews.\"\n\nThe skill will:\n1. Download the BERT model and load a dataset of customer reviews with sentiment labels.\n2. Generate code to fine-tune the model on the review dataset, including tokenization, padding, and attention mechanisms.\n\n## Best Practices\n\n- **Data Preprocessing**: Ensure data is properly preprocessed and formatted to match the input requirements of the pre-trained model.\n- **Hyperparameter Tuning**: Experiment with different hyperparameters (e.g., learning rate, batch size) to optimize model performance.\n- **Regularization**: Apply regularization techniques (e.g., dropout, weight decay) to prevent overfitting.\n\n## Integration\n\nThis skill can be integrated with other plugins for data loading, model evaluation, and deployment. For example, it can work with a data loading plugin to fetch datasets and a model deployment plugin to deploy the adapted model to a serving infrastructure.","## Overview\n\nThis skill streamlines the process of adapting pre-trained machine learning models via transfer learning. It enables you to quickly fine-tune models for specific tasks, saving time and resources compared to training from scratch. It handles the complexities of model adaptation, data validation, and performance optimization.\n\n## How It Works\n\n1. **Analyze Requirements**: Examines the user's request to understand the target task, dataset characteristics, and desired performance metrics.\n2. **Generate Adaptation Code**: Creates Python code using appropriate ML frameworks (e.g., TensorFlow, PyTorch) to fine-tune the pre-trained model on the new dataset. This includes data preprocessing steps and model architecture modifications if needed.\n3. **Implement Validation and Error Handling**: Adds code to validate the data, monitor the training process, and handle potential errors gracefully.\n4. **Provide Performance Metrics**: Calculates and reports key performance indicators (KPIs) such as accuracy, precision, recall, and F1-score to assess the model's effectiveness.\n5. **Save Artifacts and Documentation**: Saves the adapted model, training logs, performance metrics, and automatically generates documentation outlining the adaptation process and results.\n\n## When to Use This Skill\n\nThis skill activates when you need to:\n- Fine-tune a pre-trained model for a specific task.\n- Adapt a pre-trained model to a new dataset.\n- Perform transfer learning to improve model performance.\n- Optimize an existing model for a particular application.\n\n## Examples\n\n### Example 1: Adapting a Vision Model for Image Classification\n\nUser request: \"Fine-tune a ResNet50 model to classify images of different types of flowers.\"\n\nThe skill will:\n1. Download the ResNet50 model and load a flower image dataset.\n2. Generate code to fine-tune the model on the flower dataset, including data augmentation and optimization techniques.\n\n### Example 2: Adapting a Language Model for Sentiment Analysis\n\nUser request: \"Adapt a BERT model to perform sentiment analysis on customer reviews.\"\n\nThe skill will:\n1. Download the BERT model and load a dataset of customer reviews with sentiment labels.\n2. Generate code to fine-tune the model on the review dataset, including tokenization, padding, and attention mechanisms.\n\n## Best Practices\n\n- **Data Preprocessing**: Ensure data is properly preprocessed and formatted to match the input requirements of the pre-trained model.\n- **Hyperparameter Tuning**: Experiment with different hyperparameters (e.g., learning rate, batch size) to optimize model performance.\n- **Regularization**: Apply regularization techniques (e.g., dropout, weight decay) to prevent overfitting.\n\n## Integration\n\nThis skill can be integrated with other plugins for data loading, model evaluation, and deployment. For example, it can work with a data loading plugin to fetch datasets and a model deployment plugin to deploy the adapted model to a serving infrastructure.",{"name":5,"license":15,"description":7,"allowed-tools":38},[39,40,41,42,43,26],"Read","Write","Edit","Grep","Glob","main","01d3fafeca1133f841956b8b90b939fee92d71e7","plugins\u002Fclaude-code-plugins-plus\u002Fplugins\u002Fai-ml\u002Ftransfer-learning-adapter\u002Fskills\u002Ftransfer-learning-adapter",9,"https:\u002F\u002Fgithub.com\u002FBbgnsurfTech\u002Fclaude-skills-collection","https:\u002F\u002Fgithub.com\u002FBbgnsurfTech","www.bbgnsurf.com","An ICT solutions provider and software development company","2025-12-18 20:19:58",{"source":8,"skillName":5,"commands":54,"prompt":64,"zipAvailable":65},[55,58,61],{"tool":56,"command":57},"npx","npx skills add BbgnsurfTech\u002Fclaude-skills-collection --skill adapting-transfer-learning-models",{"tool":59,"command":60},"bunx","bunx skills add BbgnsurfTech\u002Fclaude-skills-collection 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visual changes in UI components using screenshot comparison.\nUse when detecting unintended UI changes or pixel differences.\nTrigger with phrases like \"test visual changes\", \"compare screenshots\", or \"detect UI regressions\".","https:\u002F\u002Fgithub.com\u002FBbgnsurfTech\u002Fclaude-skills-collection\u002Fblob\u002Fmain\u002Fplugins\u002Fclaude-code-plugins-plus\u002Fplugins\u002Ftesting\u002Fvisual-regression-tester\u002Fskills\u002Fvisual-regression-tester\u002FSKILL.md",[108],{"categoryNo":109,"categoryName":110,"taxonomyType":111,"taxonomyTypeDesc":112},"01JBSEEDCAT000000000000008","测试与质量","SCENARIO","使用场景",[114,115,116,31,28,29,30,117,118,119,120,121,122,26],"testing visual 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coverage\".","https:\u002F\u002Fgithub.com\u002FBbgnsurfTech\u002Fclaude-skills-collection\u002Fblob\u002Fmain\u002Fplugins\u002Fclaude-code-plugins-plus\u002Fplugins\u002Ftesting\u002Funit-test-generator\u002Fskills\u002Funit-test-generator\u002FSKILL.md",[129],{"categoryNo":109,"categoryName":110,"taxonomyType":111,"taxonomyTypeDesc":112},[131,132,133,134,135,119,31,136,137,138,117,139,140,30,29,28,26,141],"unit tests","Generating Unit Tests","generate","create","add test","functions","modules","test coverage","coverage","code","edge",{"skillNo":143,"name":144,"nameZh":6,"description":145,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":146,"categories":147,"keywords":154,"publishedAt":33},"01M6CDVPQKGQ450Q50ZC84FPMR","generating-test-reports","Generate comprehensive test reports with metrics, coverage, and visualizations.\nUse when performing specialized testing.\nTrigger with phrases like \"generate test report\", \"create test documentation\", or \"show test metrics\".","https:\u002F\u002Fgithub.com\u002FBbgnsurfTech\u002Fclaude-skills-collection\u002Fblob\u002Fmain\u002Fplugins\u002Fclaude-code-plugins-plus\u002Fplugins\u002Ftesting\u002Ftest-report-generator\u002Fskills\u002Ftest-report-generator\u002FSKILL.md",[148,149],{"categoryNo":109,"categoryName":110,"taxonomyType":111,"taxonomyTypeDesc":112},{"categoryNo":150,"categoryName":151,"taxonomyType":152,"taxonomyTypeDesc":153},"01JBSEEDCAT000000000000034","行政与办公人员","PROFESSION","适用职业",[119,155,156,157,158,117,139,31,159,30,29,160,26,161,133,134,162,115,28],"reports","Generating Test Reports","test report","specialized","report","visualizations","metrics","documentation",{"skillNo":164,"name":165,"nameZh":6,"description":166,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":167,"categories":168,"keywords":170,"publishedAt":33},"01M6CDVK97VFZ53CEYEGQ4QFZ6","orchestrating-test-execution","Coordinate parallel test execution across multiple environments and frameworks.\nUse when performing specialized testing.\nTrigger with phrases like \"orchestrate tests\", \"run parallel tests\", or \"coordinate test execution\".","https:\u002F\u002Fgithub.com\u002FBbgnsurfTech\u002Fclaude-skills-collection\u002Fblob\u002Fmain\u002Fplugins\u002Fclaude-code-plugins-plus\u002Fplugins\u002Ftesting\u002Ftest-orchestrator\u002Fskills\u002Ftest-orchestrator\u002FSKILL.md",[169],{"categoryNo":109,"categoryName":110,"taxonomyType":111,"taxonomyTypeDesc":112},[171,172,119,29,117,31,30,158,28,173,26,174,175,115],"orchestrating test execution","execution","parallel","orchestrate","run",{"skillNo":177,"name":178,"nameZh":6,"description":179,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":180,"categories":181,"keywords":183,"publishedAt":33},"01M6CDVFTCBQ65TGB1YJCZB90G","managing-test-environments","Provision and manage isolated test environments with configuration and data.\nUse when performing specialized testing.\nTrigger with phrases like \"manage test environment\", \"provision test env\", or \"setup test infrastructure\".","https:\u002F\u002Fgithub.com\u002FBbgnsurfTech\u002Fclaude-skills-collection\u002Fblob\u002Fmain\u002Fplugins\u002Fclaude-code-plugins-plus\u002Fplugins\u002Ftesting\u002Ftest-environment-manager\u002Fskills\u002Ftest-environment-manager\u002FSKILL.md",[182],{"categoryNo":109,"categoryName":110,"taxonomyType":111,"taxonomyTypeDesc":112},[184,119,31,30,29,158,28,26,185,186,187,115,188,189,117],"Managing Test Environments","data","infrastructure","setup","environment","manage",{"skillNo":191,"name":192,"nameZh":6,"description":193,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":194,"categories":195,"keywords":197,"publishedAt":33},"01M6CDVD0NPFXVEQGT9CMF02H0","generating-test-doubles","Generate mocks, stubs, spies, and fakes for dependency isolation.\nUse when creating mocks, stubs, or test isolation fixtures.\nTrigger with phrases like \"generate mocks\", \"create test doubles\", or \"setup stubs\".","https:\u002F\u002Fgithub.com\u002FBbgnsurfTech\u002Fclaude-skills-collection\u002Fblob\u002Fmain\u002Fplugins\u002Fclaude-code-plugins-plus\u002Fplugins\u002Ftesting\u002Ftest-doubles-generator\u002Fskills\u002Ftest-doubles-generator\u002FSKILL.md",[196],{"categoryNo":109,"categoryName":110,"taxonomyType":111,"taxonomyTypeDesc":112},[119,198,199,117,31,30,29,28,26,133,134,187],"Generating Test Doubles","dependency"]