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.
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Recover from failed file and directory operations by switching to run_shell, a shell command tool. Create nested folders, write files, and verify each result before continuing with tasks that depend on those files.
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Generate DOCX, PDF, and HTML from Markdown through separate, observable conversion steps. The workflow replaces problematic characters for PDF output, captures error messages, and switches PDF engines when needed to troubleshoot document generation failures.
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Extract text from Word DOCX files with shell commands when python-docx is unavailable. The workflow reads the document’s XML content, removes tags, optionally cleans whitespace, and saves plain text for inspection or further use.
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Extract text from Word DOCX files with unzip and sed, command-line utilities, when Python document libraries are unavailable. Read the document’s main text, remove XML tags, clean whitespace, and save the extracted content.
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Investigate Python failures in a sandbox, an isolated execution environment, by capturing partial logs, testing functions separately, and checking output files one at a time. Use the findings to identify failing steps and rebuild a working script.
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Extract text, tables, and headings from Word documents when standard file reading tools fail. The workflow uses Python and python-docx through run_shell to recover document content for further review or analysis.
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Analyze agent runs that fail before any work begins. By checking execution counts, tool calls, outputs, and conversation logs, this skill classifies startup failures and directs investigation toward system setup, resources, or input processing.
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Produce a master track and separate audio parts through a structured Python workflow. Apply filters and reverb, export WAV files with consistent settings, package them in a ZIP archive, and check that the deliverables meet the requested specifications.
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Create Excel files with openpyxl, a Python spreadsheet library, by switching to shell execution when sandbox tools fail. Examples cover cell styling, formulas, merged cells, multiple sheets, error reporting, and checking that the output file exists.
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Run Python code through a saved script and shell when repeated sandbox failures point to environment problems. Captures execution output and checks exit codes and expected files to verify whether the task completed.
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Define when a file creation task is complete: the deliverable is saved, contains the required content, and uses the correct format and location. Verify those conditions, then report completion without searching for an unnecessary submission tool.
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Organize patient visit information into a complete SOAP note: reported symptoms, observed findings, clinical assessment, and care plan. Write all four sections into one file, check required content, and explicitly identify missing information.
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Recover from failed code execution by simplifying code, switching to shell commands, or handing complex tasks to shell_agent. Explicit working directories and output checks help keep generated files in the expected location.
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Review an agent’s saved memory alongside project and personal instructions. Receive proposed destinations for useful entries and a cleanup report covering duplicates, outdated facts, conflicts, and unclear items, with approval required before changes.
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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.
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Find reusable skills in OpenSpace's local registry and explore its cloud library when needed. Review matching skills, choose where to import them locally, and decide whether to follow them or delegate the task.
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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.
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Create and check files through shell scripts when code execution tools repeatedly fail. The workflow verifies working directories, handles script quoting and permissions, and inspects outputs such as PDFs and DOCX documents for file size, type, and structure.
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Continue Python tasks when the e2b sandbox, an isolated execution environment, is unavailable. Guides switching from execute_code_sandbox to run_shell, preparing dependencies, checking execution results, and saving intermediate data between calls.
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Inspect unfamiliar Excel workbooks before building extraction scripts. Map sheets, headers, columns, and row patterns, then use those findings to distinguish actual records from summaries and blank rows when extracting data.
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Recover from failed Excel creation or editing by switching from execute_code_sandbox to shell_agent. It guides clear task descriptions so the agent can install missing libraries, run code, retry errors, and confirm file creation.
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Read or create DOCX documents when standard file tools fail. This fallback extracts text from the document's internal XML and uses python-docx through shell commands to build new files with headings, paragraphs, and tables.
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Extract plain text from Word DOCX files using shell commands first, then switch to Python's built-in ZIP reader if extraction fails or returns nothing. Supports text output without requiring the external python-docx package.
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