[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M6KFGG2R9ACTCGP4ZHAVCYB1":3,"skill-same:01M6KFGG2R9ACTCGP4ZHAVCYB1":66},{"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":23,"publishedAt":33,"linkOnly":34,"markdownContent":35,"markdownBody":36,"frontMatter":37,"refName":38,"commitSha":39,"skillDirectory":40,"forksCount":14,"repositoryHtmlUrl":41,"repositoryHomepageUrl":6,"ownerHtmlUrl":42,"ownerBlogUrl":43,"ownerDescription":44,"updatedAt":45,"install":46,"resources":59},"01M6KFGG2R9ACTCGP4ZHAVCYB1","fallback-python-execution",null,"Reliable Python execution workflow when execute_code_sandbox or shell_agent fail","xyliu-cs\u002FOpenSpace-GDPval","xyliu-cs","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F89236536?v=4","01M6KF8Z1V4TXS86CKSH48BY8T","xy","01M6KF8Z67443W0SHXM85JEF0B",0,"MIT","https:\u002F\u002Fgithub.com\u002Fxyliu-cs\u002FOpenSpace-GDPval\u002Fblob\u002Fmain\u002Fgdpval_bench\u002Fskills\u002Ffallback-python-execution\u002FSKILL.md",[18],{"categoryNo":19,"categoryName":20,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000023","Skill与智能体开发","SCENARIO","使用场景",[24,25,26,27,28,29,30,31,32],"python","execution","fallback","fallback python execution","sandbox","workflow","code","shell","execute","2026-11-10 10:12:30",false,"---\nname: fallback-python-execution\ndescription: Reliable Python execution workflow when execute_code_sandbox or shell_agent fail\n---\n\n# Fallback Python Execution Pattern\n\n## When to Use\n\nUse this pattern when:\n- `execute_code_sandbox` returns unknown errors or fails repeatedly\n- `shell_agent` cannot successfully execute Python code\n- You need to create files (spreadsheets, documents, data files) via Python\n- Direct delegated approaches prove unreliable in the current environment\n\n## Core Technique\n\nInstead of delegating Python execution to agents, use this two-step inline approach:\n\n1. **Write** Python code to a `.py` file using `write_file`\n2. **Execute** the file using `run_shell` with `python \u003Cscript.py>`\n\n## Step-by-Step Instructions\n\n### Step 1: Write Python Code to File\n\nUse `write_file` to create a Python script with all necessary code inline:\n\n```\nwrite_file\npath: \u002Fpath\u002Fto\u002Fscript.py\ncontent: |\n    import pandas as pd\n    # Your complete Python code here\n    df = pd.DataFrame({...})\n    df.to_excel('output.xlsx', index=False)\n```\n\n### Step 2: Execute via run_shell\n\nRun the script directly:\n\n```\nrun_shell\ncommand: python \u002Fpath\u002Fto\u002Fscript.py\n```\n\n### Step 3: Verify and Clean Up\n\n- Check the output for success\u002Ferrors\n- Verify the expected files were created\n- Optionally remove the temporary script if no longer needed\n\n## Why This Works\n\nThis approach is more reliable because:\n- Avoids agent interpretation layers that can introduce errors\n- Provides direct control over execution environment\n- Gives clear error output for debugging\n- Bypasses sandbox delegation issues\n\n## Example: Excel File Creation\n\n```yaml\n# Step 1: Write the script\nwrite_file:\n  path: create_report.py\n  content: |\n    import pandas as pd\n    from openpyxl import Workbook\n    \n    # Create data\n    data = {'Column1': [1, 2, 3], 'Column2': ['A', 'B', 'C']}\n    df = pd.DataFrame(data)\n    \n    # Save to Excel\n    df.to_excel('report.xlsx', index=False)\n    print('Excel file created successfully')\n\n# Step 2: Execute\nrun_shell:\n  command: python create_report.py\n```\n\n## Tips\n\n- Include error handling in your Python code for better debugging\n- Use absolute paths when possible to avoid working directory issues\n- Add print statements to track execution progress\n- Keep scripts self-contained with all imports at the top\n- For complex tasks, break into multiple scripts if needed\n\n## Troubleshooting\n\n| Issue | Solution |\n|-------|----------|\n| Module not found | Add pip install commands before python command |\n| Permission errors | Check file paths are writable |\n| Script not found | Use absolute path or cd to directory first |\n| Output not created | Check for Python errors in run_shell output |","# Fallback Python Execution Pattern\n\n## When to Use\n\nUse this pattern when:\n- `execute_code_sandbox` returns unknown errors or fails repeatedly\n- `shell_agent` cannot successfully execute Python code\n- You need to create files (spreadsheets, documents, data files) via Python\n- Direct delegated approaches prove unreliable in the current environment\n\n## Core Technique\n\nInstead of delegating Python execution to agents, use this two-step inline approach:\n\n1. **Write** Python code to a `.py` file using `write_file`\n2. **Execute** the file using `run_shell` with `python \u003Cscript.py>`\n\n## Step-by-Step Instructions\n\n### Step 1: Write Python Code to File\n\nUse `write_file` to create a Python script with all necessary code inline:\n\n```\nwrite_file\npath: \u002Fpath\u002Fto\u002Fscript.py\ncontent: |\n    import pandas as pd\n    # Your complete Python code here\n    df = pd.DataFrame({...})\n    df.to_excel('output.xlsx', index=False)\n```\n\n### Step 2: Execute via run_shell\n\nRun the script directly:\n\n```\nrun_shell\ncommand: python \u002Fpath\u002Fto\u002Fscript.py\n```\n\n### Step 3: Verify and Clean Up\n\n- Check the output for success\u002Ferrors\n- Verify the expected files were created\n- Optionally remove the temporary script if no longer needed\n\n## Why This Works\n\nThis approach is more reliable because:\n- Avoids agent interpretation layers that can introduce errors\n- Provides direct control over execution environment\n- Gives clear error output for debugging\n- Bypasses sandbox delegation issues\n\n## Example: Excel File Creation\n\n```yaml\n# Step 1: Write the script\nwrite_file:\n  path: create_report.py\n  content: |\n    import pandas as pd\n    from openpyxl import Workbook\n    \n    # Create data\n    data = {'Column1': [1, 2, 3], 'Column2': ['A', 'B', 'C']}\n    df = pd.DataFrame(data)\n    \n    # Save to Excel\n    df.to_excel('report.xlsx', index=False)\n    print('Excel file created successfully')\n\n# Step 2: Execute\nrun_shell:\n  command: python create_report.py\n```\n\n## Tips\n\n- Include error handling in your Python code for better debugging\n- Use absolute paths when possible to avoid working directory issues\n- Add print statements to track execution progress\n- Keep scripts self-contained with all imports at the top\n- For complex tasks, break into multiple scripts if needed\n\n## Troubleshooting\n\n| Issue | Solution |\n|-------|----------|\n| Module not found | Add pip install commands before python command |\n| Permission errors | Check file paths are writable |\n| Script not found | Use absolute path or cd to directory first |\n| Output not created | Check for Python errors in run_shell output |",{"name":5,"description":7},"main","af1b40a42167d09c30b3a63000aa14ace4c1e229","gdpval_bench\u002Fskills\u002Ffallback-python-execution","https:\u002F\u002Fgithub.com\u002Fxyliu-cs\u002FOpenSpace-GDPval","https:\u002F\u002Fgithub.com\u002Fxyliu-cs","https:\u002F\u002Fxyliu-cs.github.io","PhD Student in CS, CUHK-Shenzhen.","2026-04-06 20:32:15",{"source":8,"skillName":5,"commands":47,"prompt":57,"zipAvailable":58},[48,51,54],{"tool":49,"command":50},"npx","npx skills add xyliu-cs\u002FOpenSpace-GDPval --skill fallback-python-execution",{"tool":52,"command":53},"bunx","bunx skills add xyliu-cs\u002FOpenSpace-GDPval --skill fallback-python-execution",{"tool":55,"command":56},"pnpm","pnpm dlx skills add xyliu-cs\u002FOpenSpace-GDPval --skill 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step","https:\u002F\u002Fgithub.com\u002Fxyliu-cs\u002FOpenSpace-GDPval\u002Fblob\u002Fmain\u002Fgdpval_bench\u002Fskills\u002Fzip-export-deliverable\u002FSKILL.md",[],[74,75,76,77,78,79],"zip export deliverable","zip","export","deliverables","codebase","as",{"skillNo":81,"name":82,"nameZh":6,"description":83,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":84,"categories":85,"keywords":86,"publishedAt":33},"01M6KG8GAZWHHEK7VNJDW0ME21","zip-deliverable-finalization","Ensure codebase deliverables are properly packaged as ZIP exports in a dedicated final step","https:\u002F\u002Fgithub.com\u002Fxyliu-cs\u002FOpenSpace-GDPval\u002Fblob\u002Fmain\u002Fgdpval_bench\u002Fskills\u002Fzip-deliverable-finalization\u002FSKILL.md",[],[87,75,77,78,79],"zip deliverable finalization",{"skillNo":89,"name":90,"nameZh":6,"description":91,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":92,"categories":93,"keywords":94,"publishedAt":33},"01M6KG8CMQQ1PYMNTSRZ9VS1MD","zero-iteration-failure-analysis","Identify and handle agent failures with 0 iterations as pre-execution system issues","https:\u002F\u002Fgithub.com\u002Fxyliu-cs\u002FOpenSpace-GDPval\u002Fblob\u002Fmain\u002Fgdpval_bench\u002Fskills\u002Fzero-iteration-failure-analysis\u002FSKILL.md",[],[95,96,97,98,99,100,101,25,79,102],"failure analysis","ZeRO","analysis","iteration","zero iteration failure analysis","with","issues","system",{"skillNo":104,"name":105,"nameZh":6,"description":106,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":107,"categories":108,"keywords":114,"publishedAt":33},"01M6KG86W3PA07FT9W58YHHERM","write-file-fallback-report","Generate professional documents using write_file when primary data sources fail, leveraging embedded domain knowledge instead of external retrieval","https:\u002F\u002Fgithub.com\u002Fxyliu-cs\u002FOpenSpace-GDPval\u002Fblob\u002Fmain\u002Fgdpval_bench\u002Fskills\u002Fwrite-file-fallback-report\u002FSKILL.md",[109],{"categoryNo":110,"categoryName":111,"taxonomyType":112,"taxonomyTypeDesc":113},"01JBSEEDCAT000000000000034","行政与办公人员","PROFESSION","适用职业",[26,115,116,117,118,119,120,121,122,123,124,125,126,127],"write","file","report","write file fallback report","domain","professional","sources","retrieval","generate","embedded","documents","data","knowledge",{"skillNo":129,"name":130,"nameZh":6,"description":131,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":132,"categories":133,"keywords":135,"publishedAt":33},"01M6KG82GAEY3GG77CMGCK1C2T","fallback-doc-with-delegation","Generate professional documents after tool failures using shell_agent for complex formats or write_file for simple text\u002Fmarkdown","https:\u002F\u002Fgithub.com\u002Fxyliu-cs\u002FOpenSpace-GDPval\u002Fblob\u002Fmain\u002Fgdpval_bench\u002Fskills\u002Fwrite-file-fallback-report-enhanced\u002FSKILL.md",[134],{"categoryNo":19,"categoryName":20,"taxonomyType":21,"taxonomyTypeDesc":22},[136,100,26,137,138,31,125,123,116,139,140,141,115,142,120,143,144],"fallback doc with 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