1K skills ・ Works with: Excel · sorted by popularity
Validate spreadsheet sources before running Python scripts to transform data, update multiple sheets, or apply formatting. Check required data first, try backup sources when needed, and report errors clearly if processing cannot proceed.
Update or create Excel workbooks with checks against the requested structure. Identify the correct file before editing, then reread the saved workbook to verify sheet names, populated columns, row counts, and selected sample counts.
Process Excel files with Python after checking that input files and source URLs are accessible. The workflow covers data transformations, formulas, and formatting, with alternative sources and error logs when access fails.
Create or edit Excel workbooks with checks for sheet names, row counts, formulas, and merged cells. Reopen the saved file and verify each requirement, recording explicit results rather than relying on a completion summary.
Gather web information and turn it into an Excel workbook with explicit checks. Handles search failures through delegated research, records sources and missing data, and verifies the saved workbook against requested requirements.
Verify saved Excel files directly with Python and openpyxl, a workbook library. Check sheets, headers, row counts, marked rows, and output files to resolve conflicting agent reports and summarize what actually exists on disk.
Process Excel workbooks and generate PDF reports by running Python scripts directly. Covers multiple sheets, data transformations, formatting, and error handling, with scripts saved as files for complex tasks.
Process Excel workbooks by saving Python scripts to files and running them through the shell. Covers multiple sheets, data transformations, formulas, formatting, and error reporting for complex spreadsheet tasks.
Create and process Excel files, PDF checklists, and structured reports by running Python scripts directly. The skill covers multiple sheets, formulas, formatting, data transformations, and error handling for document workflows with several steps.
Track tasks that require several output files with an upfront checklist, checks after each file is created, and a final review. Confirm that every required file exists and has a nonzero size before reporting completion.
Run Python through shell commands when sandbox execution fails because required packages are unavailable. The skill explains short commands, multiline scripts, package checks, and output verification, with examples for creating Excel and Word files.
Build answers and reports from provided reference files before searching the web. The workflow identifies attachments, extracts and checks relevant data, tries alternatives for unreadable Word files, and states sources and missing information.
Helps agents build outputs from supplied reference files by reading, checking, and citing their data first. External searches are reserved for missing details, verification, or tasks that explicitly require current information.
Use attached spreadsheets and documents as the primary source for reports and analysis. Identify relevant files, extract needed data, and cite filenames, turning to external searches or clearly labeled estimates only when the supplied material lacks required information.
Extract data from supplied spreadsheets and documents, check for missing or truncated content, and try alternative reading methods when needed. Results identify source files and clearly separate extracted facts from external information or estimates.
Recover failed Python tasks by saving the code as a script and running it through the shell. Provides steps to inspect errors and confirm generated files for spreadsheet creation, data processing, and calculations.
Create and edit Excel workbooks by running a complete Python script through the shell. Covers multiple sheets, data entry, formatting, formulas, and saving files when other file-reading or code-execution tools fail.
Recover from failed inline Python execution by saving the code as a script, running it through the shell, and checking the output. The four-step workflow helps diagnose errors in multiline code and spreadsheet generation tasks.
Diagnose Python spreadsheet failures through staged checks of the interpreter, library imports, file access, and basic operations. Minimal test scripts help separate environment problems from errors in the full processing script.
Create spreadsheets, diagrams, and PDF reports in a staged workflow. Allocate execution attempts across deliverables, check generated files, and use simpler methods or alternative formats when tool errors or limited remaining attempts interrupt progress.
Continue Excel file creation and editing when execute_code_sandbox repeatedly fails with openpyxl errors. Use run_shell to run Python directly, then check that the workbook was saved with the expected sheets and content.
Build Excel spreadsheets with merged titles and headers using openpyxl, a Python library for spreadsheet files. Follow a sequence for entering values, merging cells, and applying formatting, with guidance for updating existing merged ranges and checking saved results.
Find generated files that are missing from their expected locations in isolated or temporary execution environments. Search confirmed directories, identify the right file, copy it to the intended destination, and verify that it is readable and nonempty.
Locate missing files and verify their full paths before processing them. This workflow checks directory contents, searches by filename, and inspects permissions, size, and modification time to help resolve FileNotFoundError, an error indicating a file could not be found.