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Update .claude/agents/tutorial-tool-extractor-implementor.md
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.claude/agents/tutorial-tool-extractor-implementor.md
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name: tutorial-tool-extractor-implementor
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description: Use this agent when you need to systematically process tutorials to extract and implement their tools as reusable functions for current folder with ONLY <github_repo_name>-env environment installed (no mcps-env required). This agent should be triggered when: (1) You have discovered tutorials that need to be converted into a function library, (2) You need to analyze tutorial code and classify tools by their applicability to new data, (3) You want to create standardized Python modules from tutorial notebooks or scripts. Examples: <example>Context: The user has a collection of bioinformatics tutorials and wants to extract reusable functions. user: 'Process the GWAS tutorial and extract all applicable tools' assistant: 'I'll use the tutorial-tool-extractor agent to analyze the GWAS tutorial and create the function module' <commentary>Since the user wants to extract tools from a tutorial, use the tutorial-tool-extractor agent to systematically process it.</commentary></example> <example>Context: Multiple tutorials need to be converted to a function library. user: 'Start processing tutorials from the discovered list' assistant: 'Let me launch the tutorial-tool-extractor agent to process each tutorial systematically' <commentary>The user wants to process tutorials in order, so use the tutorial-tool-extractor agent.</commentary></example>
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model:
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color: cyan
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name: tutorial-tool-extractor-implementor
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description: Use this agent when you need to systematically process tutorials to extract and implement their tools as reusable functions for current folder with ONLY <github_repo_name>-env environment installed (no mcps-env required). This agent should be triggered when: (1) You have discovered tutorials that need to be converted into a function library, (2) You need to analyze tutorial code and classify tools by their applicability to new data, (3) You want to create standardized Python modules from tutorial notebooks or scripts. Examples: <example>Context: The user has a collection of bioinformatics tutorials and wants to extract reusable functions. user: 'Process the GWAS tutorial and extract all applicable tools' assistant: 'I'll use the tutorial-tool-extractor agent to analyze the GWAS tutorial and create the function module' <commentary>Since the user wants to extract tools from a tutorial, use the tutorial-tool-extractor agent to systematically process it.</commentary></example> <example>Context: Multiple tutorials need to be converted to a function library. user: 'Start processing tutorials from the discovered list' assistant: 'Let me launch the tutorial-tool-extractor agent to process each tutorial systematically' <commentary>The user wants to process tutorials in order, so use the tutorial-tool-extractor agent.</commentary></example>
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model: haiku
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color: cyan
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