Coding standards, frameworks, refactoring, and code review (16.5K skills)
Run Python through run_shell when code execution tools repeatedly fail. This workflow embeds a multiline script directly in a shell command, supporting tasks such as CSV conversion and PDF generation while checking execution output.
Recover Python tasks when execute_code_sandbox fails with errors or timeouts. Install required packages, run the code through run_shell, and inspect messages and generated files to check the result.
Continue Python tasks when sandbox execution fails by saving code as a script and running it through run_shell. The workflow covers dependencies, execution checks, and output verification for PDFs, image processing, data analysis, and file operations.
Run Python code directly on the host when repeated e2b sandbox failures block execution. The skill explains saving scripts, launching them through the shell, and checking outputs when an isolated environment is unnecessary.
Recover from failed automated file creation with an explicit shell workflow. The skill guides agents through checking folders, writing and running scripts, and inspecting output files to confirm that deliverables were actually created.
Build Web3 applications, combining blockchain contracts with a user interface, in a defined sequence. Organize directories, define interfaces, implement and test contracts, configure wallet connections, build components, and prepare deployment scripts.
Diagnose unclear failures from run_shell commands through a stepwise workflow. Capture error output, verify directories and command availability, check environment variables, and test simpler commands to narrow down problems with paths, permissions, or the execution environment.
Continue Python work when the code sandbox is unavailable by running scripts through run_shell. The workflow covers recognizing connection failures, installing required packages, reading and writing workspace files, and checking execution results.
Run multi-line Python scripts through run_shell when execute_code_sandbox repeatedly fails. The guide explains heredocs, a way to pass blocks of text to a command, with examples for PDF creation, data processing, and inspecting errors.
Continue Python tasks when the sandbox cannot start by switching to run_shell. The workflow covers short scripts, saved script files, library checks, longer timeouts, and output verification for tasks such as PDF generation and data processing.
Continue file reading and data processing when read_file or execute_code_sandbox fails. The skill uses run_shell with short Python commands or multiline scripts to inspect files, parse data, and save transformed output.
Recover from repeated code execution tool failures by writing a script through the shell and running it with an absolute path. Check output files and investigate syntax, permissions, disk space, or execution errors when needed.
Recover from file creation failures in automated tools by creating directories with shell commands and writing files individually. This workflow separates each step so project structures can be created and checked more easily.
Apply ReportLab’s built-in paragraph styles to PDF titles, headings, and body text. Learn how to reuse existing styles and create named variations without duplicate style names that can cause KeyError exceptions.
Run multiline Python code by saving it to a script file before executing it through the shell. The workflow covers working directories, timeouts, error checks, and optional cleanup to make execution easier to debug.
Run Python through run_shell when execute_code_sandbox fails unexpectedly. The skill explains how to pass multiline code using a heredoc, a shell syntax for inline text, then check standard output and error messages.
Continue library-dependent Python tasks when sandbox execution fails by switching to a shell script. Covers recognizing import errors, preserving script text, checking execution output, and troubleshooting package availability for tasks such as PDF generation or visualization.
Investigate Python script failures by capturing regular output, error details, and exit codes. Log the working directory and resolved file paths to expose missing files, permission problems, missing modules, or differences in automated execution.
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.
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.
Diagnose Python script failures by showing error output and exit codes alongside the working directory and file listing. Use these clues to investigate missing files, missing modules, permission errors, or scripts that produce no output.
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.
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.
Recover Python file-generation tasks when sandbox execution fails by saving a script and running it through the shell, a command interface. Use the workflow for PDFs, document file operations, dependency checks, and output verification.