374 skills · sorted by relevance
Set up KubeEye in KubeSphere to inspect Kubernetes clusters. Define checks for configurations, nodes, and services, schedule recurring or one-time inspections, and retrieve findings as HTML or spreadsheet reports.
Select random winners from lists, CSV files, Excel, or Google Sheets. Choose multiple winners without duplicates, exclude previous winners, apply entry-based weighting, and record the selection method and timestamp for review.
Create, read, and edit Word documents with headings, tables, page numbers, and images. Use it to turn content into formatted reports or letters, reorganize existing documents, replace text, and work with tracked changes and comments.
Automate Google Workspace tasks through a command-line tool: read email, calendars, files, documents, and spreadsheet data, or make requested updates. Inspect authentication, return structured JSON data, and restrict allowed operations for agent workflows.
Audit an Excel workbook before editing, then verify the saved file with Python and openpyxl. Each requested requirement receives an explicit status, so completion depends on checks of the actual file.
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.
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.
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.
Find input files in confirmed workspace folders, save outputs to explicit locations, and check the results against task requirements. Useful in restricted execution environments where familiar folders may be missing or inaccessible.
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.
Create or modify Excel workbooks, then independently check the saved file with Python. Verify required sheets, columns, populated cells, row counts, and sample selections against the requested structure before reporting the work as complete.
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.
Check whether a file creation or transformation task actually succeeded after an unclear execution error. Inspect output files and their contents to distinguish success, partial completion, and failure before deciding whether to retry.
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.
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.
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.
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.
Continue file reading and data processing when execute_code_sandbox or read_file fails. This skill runs multiline Python through run_shell, with examples for text, JSON, spreadsheets, PDF and Word documents, plus basic summaries and grouped calculations.
Run Python through a saved script when execute_code_sandbox or shell_agent repeatedly fails. The workflow writes code to a file, executes it through run_shell, and checks errors and expected outputs such as spreadsheets or documents.
Handle merged cells before filling Excel templates with openpyxl, a Python library for spreadsheets. This skill shows how to inspect merged ranges, unmerge the required areas, write values, and save the workbook without merged-cell write errors.
Check files created or edited by another agent, subprocess, or tool against explicit requirements. Verify the actual location, structure, counts, and key fields, then rerun with absolute paths when the results contradict the completion report.
Find, organize, share, copy, and export Google Drive files through one plugin. For document, spreadsheet, and presentation work, it identifies the target file and routes summaries or edits to the appropriate specialized skill.
Create, reply to, and resolve comments on Google Drive files, including Docs, Sheets, and Slides. Include exact quotes, cell ranges, or slide numbers so readers can locate feedback even when comments appear without an attached location.
Route data analysis requests to focused workflows for metric checks, business decisions, charts, dashboards, and reports. Identify usable data sources and guide the next step, with delivery choices based on the available environment.