'python' 검색 결과

Build, extend, or review Python FastMCP servers using documentation for the installed version. Design operations that agents can discover and use, then check input definitions, results, error handling, and representative agent workflows.

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• Building an MCP server with Python FastMCP
• Adding tools, resources, or reusable prompts
• Reviewing input definitions and error handling

Create reusable slash commands for Agent Zero using YAML configuration files paired with text templates or Python scripts. It helps choose project or global scope, update existing commands, and report the saved files and exact command to invoke.

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• Turn repeated requests into reusable slash commands
• Create commands available only within a project
• Create commands shared across projects

Helps implement iii workers in Node.js, browsers, Python, and Rust with language-specific guidance on installation, function registration, calls, data channels, and logging. Explains package choices and connection constraints for each environment.

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• Choosing the iii SDK for a runtime
• Implementing asynchronous calls in Python
• Connecting a browser app to backend functions

Add or improve Google-style docstrings, the explanations embedded in Python code, for modules and classes. Document constructor arguments, public methods, configuration fields, and enum values while preserving existing documentation that already meets the project’s conventions.

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• Document a Python module
• Explain constructor arguments and public methods
• Describe configuration fields and enum values

Import a four-wheel FBX vehicle into a CARLA source build, configure its physics, wheels, and animation, and register it for the Python API. Verify that the resulting vehicle can spawn, drive, and steer.

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• Importing a custom van or truck into CARLA
• Registering a vehicle for spawning through the Python API
• Checking why an imported vehicle will not drive or steer

Run Python code and Shell commands in an isolated Cube Sandbox environment. The skill covers file access, host directory mounting, network restrictions, and pausing and resuming execution while preserving the sandbox's memory state.

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• Running untrusted code in an isolated environment
• Reading and writing sandbox files
• Restricting outbound network access

Work around file-writing errors caused by quotes, backticks, or JavaScript template literals using a temporary Python script. The workflow includes reading back each saved file to check its contents and removing the helper script afterward.

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• Recovering from write_file errors
• Saving TypeScript files containing template literals
• Writing multiple files with mixed quote styles

Write large text files when write_file or shell_agent fails because of content size limits. The fallback passes multiline content through run_shell to Python, with guidance on escaping characters and checking the saved file.

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• Saving large source files after a write_file failure
• Writing long JSON or Markdown files
• Handling content with complex shell escaping

Save large text files when write_file or shell_agent encounters payload size limits. Create the parent directory first, write the content with Python through run_shell, and verify the resulting file.

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• Saving large source files after write errors
• Writing files into new nested directories
• Saving long JSON or Markdown content

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.

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• Resume Python work after repeated e2b errors
• Run a saved script to create an Excel file
• Investigate sandbox timeouts and connection failures

Move Python execution to saved script files when execute_code_sandbox repeatedly fails or becomes unstable. The skill covers writing single or multiple files, running them through run_shell, inspecting outputs and errors, and removing temporary scripts afterward.

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• Switch execution methods after repeated sandbox failures
• Run Python code split across multiple files
• Process JSON input and write CSV output

Read, write, and transform workspace files by running Python through run_shell when execute_code_sandbox cannot access them. The workflow covers explicit file paths, batch processing, error handling, and checking generated outputs.

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• Reading configuration files in the workspace
• Transforming CSV or JSON data files
• Processing multiple text files in a batch

Inspect PowerPoint files when standard readers fail by using python-pptx through the shell. Produce structured results showing slide counts, titles, and shape counts to check presentation structure before delivery.

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• Inspecting PowerPoint files that standard readers cannot open
• Checking slide counts against requirements
• Finding slides without titles

Debug PowerPoint generation with python-pptx, a Python library for presentations. Follow a sequence of installation checks, minimal tests, error logging, and fixes for tables and charts, then inspect the generated slides.

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• Diagnosing errors in PowerPoint generation
• Fixing table and chart code
• Saving detailed error logs

Inspect PowerPoint files with python-pptx when standard readers fail or return incomplete information. Retrieve slide counts and titles, compare them with presentation requirements, and report missing or problematic content without installing PowerPoint.

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• Inspecting PPTX files that standard readers cannot open
• Checking that the slide count matches requirements
• Comparing slide titles with required topics

Generate PDF documents when sandbox execution fails with unclear errors. Check available Python libraries, switch to direct shell execution, and verify the resulting file while collecting error details to help diagnose problems.

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• Generating a PDF after sandbox execution fails
• Checking PDF libraries and choosing an alternative
• Verifying generated PDFs and investigating errors

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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• Reading DOCX files without python-docx
• Saving Word document text to a text file
• Extracting text where extra packages cannot be installed

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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• Reading Word documents after file tool failures
• Extracting table contents from Word documents
• Listing headings or numbered paragraphs

Create, edit, or validate Jupyter notebooks for SQL and Python analysis. Organize data sources, assumptions, calculations, and findings into a readable document that others can review and rerun, with execution gaps clearly identified.

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• Preparing an analysis notebook for handoff
• Organizing experiment logs and data-quality checks
• Making existing notebooks easier to read and rerun

Check the SenseNova-Skills installation, Python dependencies, and environment variables before using other skills. Prompt for missing configuration, save supplied values to a .env file, and reload settings or suggest restarting the agent.

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• Checking setup before using SenseNova-Skills
• Finding missing Python dependencies
• Entering and saving missing API configuration

Build MCP servers, which connect AI agents to external services, using TypeScript or Python. Plan API access, design understandable tools and structured responses, implement authentication and error handling, and check behavior with the intended client.

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• Building an MCP server for an external service
• Designing tool names, inputs, and responses for agents
• Implementing an MCP server in TypeScript or Python

Use SymPy in Python to solve equations, simplify formulas, calculate derivatives and integrals, and work with matrices. Keep exact results such as fractions and square roots, then turn expressions into executable code or LaTeX.

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• Solve equations and verify the solutions
• Calculate derivatives, integrals, and limits
• Find matrix eigenvalues and inverse matrices

Write MATLAB or GNU Octave scripts for matrix calculations, data analysis, signal processing, and scientific plots. The skill also helps explain syntax and functions, convert code between MATLAB and Python, and run scripts when an interpreter is installed.

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• Analyzing experimental CSV data and saving plots
• Solving matrix equations and differential equations
• Analyzing signal frequencies and applying filters

Organize research code, datasets, and outputs with consistent folders and script names. Provides Python and Stata templates, processing stage numbers, and guidance for paths, logs, and documentation so collaborators can follow the workflow.

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• Setting up folders for a new research project
• Standardizing Python and Stata script names
• Separating raw, intermediate, and cleaned datasets