{"passport":{"unfragile":{"@version":"1.0","version":"2026-05","artifact":{"id":"vscode-rubberduck-rubberduck-vscode","slug":"rubberduck-chatgpt-for-visual-studio-code","name":"Rubberduck - ChatGPT for Visual Studio Code","type":"extension","url":"https://marketplace.visualstudio.com/items?itemName=Rubberduck.rubberduck-vscode","page_url":"https://unfragile.ai/rubberduck-chatgpt-for-visual-studio-code","categories":["code-editors"],"tags":["ai","chatgpt","code explanation","codex","copilot","gpt","keybindings","openai"],"pricing":{"model":"freemium","free":true,"starting_price":null},"status":"active","verified":false},"capabilities":[{"id":"vscode-rubberduck-rubberduck-vscode__cap_0","uri":"capability://code.generation.editing.context.aware.code.generation.from.natural.language","name":"context-aware code generation from natural language","description":"Generates new code snippets based on natural language descriptions by sending the user's intent and current editor selection context to OpenAI's API, then inserting the generated code at the cursor position or displaying it in the sidebar. The extension reads the active editor's selected text to provide code context, enabling the model to generate syntactically appropriate code for the detected language. Generation is triggered via keyboard shortcut (Ctrl+Alt+G), command palette, or toolbar button.","intents":["I need to write a function to handle X but don't want to type it all out","Generate boilerplate code for a common pattern in my current file","Create a code snippet based on a description without leaving the editor"],"best_for":["solo developers building features quickly","teams prototyping MVP functionality","developers unfamiliar with a language or framework"],"limitations":["No multi-file context awareness — only uses current editor selection, not project structure or imports","Generated code quality depends entirely on OpenAI model capabilities and prompt clarity","No syntax validation before insertion — generated code may contain errors requiring manual fixes","Experimental Llama.cpp mode with CodeLlama-7B-Instruct produces lower-quality output than OpenAI","Rate-limited by OpenAI API quotas if using free tier"],"requires":["VS Code (minimum version unknown, likely 1.50+)","OpenAI API key with active credits, OR local Llama.cpp setup with CodeLlama-7B-Instruct model (~7GB download)","Internet connectivity for OpenAI mode"],"input_types":["natural language description (text)","current editor selection (code context)"],"output_types":["code snippet (inserted at cursor or shown in sidebar)"],"categories":["code-generation-editing","ai-assisted-development"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"vscode-rubberduck-rubberduck-vscode__cap_1","uri":"capability://code.generation.editing.inline.code.editing.with.diff.preview.and.approval.workflow","name":"inline code editing with diff preview and approval workflow","description":"Modifies selected code by sending the selection and user-provided editing instructions to OpenAI, receiving a modified version, and displaying it in a side-by-side diff viewer before applying changes. The user reviews the proposed changes and explicitly clicks 'Apply' to accept them, preventing accidental code replacement. Triggered via Ctrl+Alt+E keyboard shortcut or context menu. The diff viewer uses VS Code's native diff rendering with optional syntax highlighting toggled via the `rubberduck.syntaxHighlighting.useVisualStudioCodeColors` setting.","intents":["Refactor selected code according to specific instructions without manually rewriting it","Apply style or naming convention changes to a code block","Transform code from one pattern to another (e.g., callback to async/await)","Review AI-suggested changes before accepting them into my codebase"],"best_for":["developers who want AI-assisted refactoring with human approval gates","teams with code review practices who want to preview changes before committing","developers learning new patterns who want to see before/after transformations"],"limitations":["Requires explicit code selection — cannot edit entire files without selecting them first","Diff viewer theme compatibility issues — syntax highlighting 'might not work with all themes' per documentation","No undo integration with VS Code's native undo stack — changes applied directly to editor","Single-selection editing only — cannot batch-edit multiple code blocks in one operation","No git integration — changes not automatically staged or committed"],"requires":["VS Code (minimum version unknown)","OpenAI API key with active credits, OR Llama.cpp local setup","Code selection in active editor"],"input_types":["selected code (text)","editing instructions (natural language)"],"output_types":["diff visualization (side-by-side comparison)","modified code (inserted into editor on approval)"],"categories":["code-generation-editing","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"vscode-rubberduck-rubberduck-vscode__cap_10","uri":"capability://tool.use.integration.keyboard.shortcut.driven.command.access.with.platform.specific.bindings","name":"keyboard shortcut-driven command access with platform-specific bindings","description":"Provides platform-specific keyboard shortcuts for common actions (Chat, Generate Code, Edit Code) that trigger commands without opening the command palette. Shortcuts are: Chat (Ctrl+Alt+C / Ctrl+Cmd+C), Generate (Ctrl+Alt+G / Ctrl+Cmd+G), Edit (Ctrl+Alt+E / Ctrl+Cmd+E), with Windows/Linux and Mac variants. Shortcuts are customizable via VS Code's standard keybinding configuration. This enables power users to access features without mouse interaction or command palette navigation.","intents":["Quickly generate code without opening the command palette","Edit selected code with a single keyboard shortcut","Start a new chat conversation without leaving the keyboard","Customize shortcuts to match my existing muscle memory"],"best_for":["power users who prefer keyboard-driven workflows","developers with existing keybinding muscle memory","teams standardizing on keyboard shortcuts for consistency"],"limitations":["Shortcuts may conflict with other VS Code extensions or user customizations","Platform-specific bindings require users to remember different shortcuts on Windows/Mac","No discoverable shortcut hints in the UI — users must memorize or look up shortcuts","Customization requires manual editing of keybindings.json — not user-friendly for non-technical users"],"requires":["VS Code","Knowledge of keyboard shortcuts (or willingness to customize keybindings)"],"input_types":["keyboard input"],"output_types":["command execution (code generation, editing, chat)"],"categories":["tool-use-integration","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"vscode-rubberduck-rubberduck-vscode__cap_2","uri":"capability://text.generation.language.code.explanation.and.documentation.generation","name":"code explanation and documentation generation","description":"Analyzes selected code by sending it to OpenAI and returns a natural language explanation of what the code does, its purpose, and how it works. The explanation is displayed in the sidebar chat panel, allowing developers to understand unfamiliar code without leaving the editor. Triggered via command palette or context menu. Supports any language that VS Code can syntax-highlight, though explanation quality depends on the model's training data for that language.","intents":["Understand what a code snippet does without reading through it line-by-line","Learn how a complex algorithm or pattern works","Generate documentation or comments for existing code","Onboard to a new codebase by understanding key functions"],"best_for":["junior developers learning from existing codebases","teams documenting legacy code","developers context-switching between projects","non-native English speakers who prefer AI-generated explanations"],"limitations":["Explanations are only as accurate as the OpenAI model's understanding — may contain inaccuracies for obscure or domain-specific code","No multi-file context — cannot explain code that depends on imports or external functions without those being visible","Explanations are generic and not tailored to project-specific conventions or business logic","No integration with code comments — cannot update existing documentation automatically"],"requires":["VS Code","OpenAI API key, OR Llama.cpp local setup","Code selection in active editor"],"input_types":["selected code (text)"],"output_types":["natural language explanation (text in sidebar chat)"],"categories":["text-generation-language","code-generation-editing"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"vscode-rubberduck-rubberduck-vscode__cap_3","uri":"capability://code.generation.editing.automated.test.case.generation","name":"automated test case generation","description":"Generates test code for selected code by sending it to OpenAI and returning test cases in the sidebar. The specific test framework and language are inferred from the selected code's context. Tests are displayed in the chat panel and can be copied or inserted into the editor. Implementation details of test framework selection are not documented, suggesting automatic detection based on file type or imports.","intents":["Generate unit tests for a function I just wrote","Create test cases covering common edge cases and error conditions","Quickly scaffold test files without manually writing boilerplate","Ensure code coverage for critical functions"],"best_for":["developers practicing test-driven development","teams with strict code coverage requirements","developers new to testing frameworks"],"limitations":["Test framework selection mechanism is undocumented — may generate tests for wrong framework if context is ambiguous","Generated tests may not cover all edge cases or business logic requirements","No integration with test runners — tests must be manually copied and executed","No validation that generated tests actually pass against the code","Limited to single-function testing — cannot generate integration or end-to-end tests"],"requires":["VS Code","OpenAI API key, OR Llama.cpp local setup","Code selection in active editor"],"input_types":["selected code (text)"],"output_types":["test code (text in sidebar chat, copyable)"],"categories":["code-generation-editing","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"vscode-rubberduck-rubberduck-vscode__cap_4","uri":"capability://code.generation.editing.bug.detection.and.code.analysis","name":"bug detection and code analysis","description":"Analyzes selected code for potential bugs, security issues, or logic errors by sending it to OpenAI and returning identified problems in the sidebar chat. The analysis is performed on the selected code only, without access to the broader codebase or runtime context. Results are presented as a list of issues with explanations, allowing developers to review and decide whether to fix them.","intents":["Find potential bugs in code before committing or testing","Identify security vulnerabilities or unsafe patterns","Catch logic errors or edge cases I might have missed","Get a second opinion on code correctness"],"best_for":["developers practicing code review on their own work","teams without dedicated security review processes","developers learning to identify common bug patterns"],"limitations":["Analysis is static and context-free — cannot detect runtime errors or bugs that depend on external state","No access to type information, imports, or dependencies — may miss bugs related to incorrect API usage","False positives are common — AI may flag code as buggy when it's actually correct","False negatives are possible — subtle bugs may be missed","No integration with linters or static analysis tools — duplicates functionality of existing tools","Cannot detect performance issues or algorithmic inefficiencies"],"requires":["VS Code","OpenAI API key, OR Llama.cpp local setup","Code selection in active editor"],"input_types":["selected code (text)"],"output_types":["bug report (text list in sidebar chat)"],"categories":["code-generation-editing","safety-moderation"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"vscode-rubberduck-rubberduck-vscode__cap_5","uri":"capability://text.generation.language.error.message.diagnosis.and.troubleshooting","name":"error message diagnosis and troubleshooting","description":"Analyzes error messages (compiler errors, runtime exceptions, stack traces) provided by the user and returns explanations and potential fixes in the sidebar chat. The user pastes or describes the error, and OpenAI provides context about what caused it and how to resolve it. This capability bridges the gap between error output and actionable solutions without requiring manual documentation lookup.","intents":["Understand what a cryptic error message means","Get suggestions for fixing a compilation or runtime error","Troubleshoot exceptions without searching Stack Overflow","Learn why a specific error occurred in my code"],"best_for":["developers new to a language or framework","teams dealing with unfamiliar error messages","developers debugging in real-time without external resources"],"limitations":["Diagnosis accuracy depends on error message completeness — truncated or obfuscated errors may produce incorrect suggestions","No access to actual code causing the error — suggestions are generic and may not apply to specific implementation","Cannot execute code to reproduce the error — diagnosis is based on error text alone","May suggest fixes that don't work if the error message is misleading or from an unfamiliar tool","No integration with debuggers or runtime environments"],"requires":["VS Code","OpenAI API key, OR Llama.cpp local setup","Error message or stack trace (provided as text input)"],"input_types":["error message or stack trace (text)"],"output_types":["diagnosis and suggested fixes (text in sidebar chat)"],"categories":["text-generation-language","planning-reasoning"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"vscode-rubberduck-rubberduck-vscode__cap_6","uri":"capability://text.generation.language.conversational.code.assistance.with.session.memory","name":"conversational code assistance with session memory","description":"Maintains a multi-turn conversation in the sidebar panel where users can ask questions about code, request explanations, discuss design decisions, and iterate on solutions. Each conversation thread maintains context across multiple exchanges, allowing follow-up questions and refinements. Conversations are stored in the sidebar and can be reviewed or continued later. The extension sends conversation history to OpenAI to maintain context, enabling coherent multi-turn interactions.","intents":["Have a back-and-forth discussion about code design or architecture","Ask follow-up questions to refine generated code or explanations","Iterate on solutions through multiple rounds of feedback","Maintain a record of design decisions and discussions for future reference"],"best_for":["developers who prefer conversational interaction over one-off commands","teams discussing code design or architecture decisions","developers using AI as a rubber duck for thinking through problems"],"limitations":["Conversation history is stored locally in VS Code — no cloud sync or cross-device access","Context window is limited by OpenAI's token limits — very long conversations may lose early context","No persistent storage across VS Code sessions — conversations are lost if extension is uninstalled or data is cleared","No collaboration features — conversations are single-user only","No integration with version control — design discussions are not linked to commits or branches"],"requires":["VS Code","OpenAI API key, OR Llama.cpp local setup"],"input_types":["natural language questions and prompts (text)"],"output_types":["conversational responses (text in sidebar chat)"],"categories":["text-generation-language","memory-knowledge"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"vscode-rubberduck-rubberduck-vscode__cap_7","uri":"capability://text.generation.language.custom.conversation.templates.and.prompt.engineering","name":"custom conversation templates and prompt engineering","description":"Allows users to create custom conversation templates that define specific prompts, instructions, or workflows for recurring tasks. Templates can be saved and reused, enabling teams to standardize how they interact with the AI for common tasks like code review, documentation, or refactoring. Implementation details are not documented, but the feature implies a template storage mechanism and template instantiation system. Users can define custom prompts that are sent to OpenAI with predefined context or instructions.","intents":["Create a reusable template for code review that checks specific criteria","Define a standard prompt for generating documentation in my team's style","Build a custom workflow for refactoring that applies consistent patterns","Standardize how the team uses AI for common development tasks"],"best_for":["teams with standardized development practices","organizations wanting to enforce code review standards via AI","developers who repeatedly use the same prompts"],"limitations":["Template creation mechanism is undocumented — unclear how to create or manage templates","No template sharing between users — templates are stored locally per user","No version control for templates — changes to templates are not tracked","No template validation — incorrect templates may produce errors or unexpected results","Limited to text-based prompts — cannot include complex logic or conditional branching"],"requires":["VS Code","OpenAI API key, OR Llama.cpp local setup","Knowledge of prompt engineering (undocumented feature)"],"input_types":["template definition (text/configuration)"],"output_types":["instantiated conversation with predefined context (text in sidebar chat)"],"categories":["text-generation-language","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"vscode-rubberduck-rubberduck-vscode__cap_8","uri":"capability://tool.use.integration.dual.backend.model.switching.between.openai.and.local.llama.cpp","name":"dual-backend model switching between openai and local llama.cpp","description":"Allows users to switch between OpenAI's cloud API and a local Llama.cpp instance running CodeLlama-7B-Instruct via the `Rubberduck: Model` configuration setting. The extension abstracts the backend difference, sending the same prompts to either service and handling responses uniformly. Local mode requires users to install and configure Llama.cpp separately with the CodeLlama model (~7GB download). This capability enables offline operation and cost control at the expense of code quality and speed.","intents":["Run code generation and analysis without sending code to external servers","Reduce API costs by using a local model instead of OpenAI's paid API","Use Rubberduck in offline environments without internet connectivity","Experiment with open-source models as an alternative to proprietary APIs"],"best_for":["organizations with data privacy or security requirements","developers in regions with limited internet connectivity","teams wanting to reduce OpenAI API costs","developers experimenting with open-source LLMs"],"limitations":["Llama.cpp mode is marked 'experimental' — stability and reliability not guaranteed","CodeLlama-7B-Instruct produces significantly lower-quality output than OpenAI models","Requires manual setup of Llama.cpp and model download (~7GB) — not automated","Local execution is slower than cloud API, especially on CPU-only machines","No automatic fallback to OpenAI if local model fails — user must manually switch backends","Limited documentation on Llama.cpp setup and troubleshooting","No support for other local models — only CodeLlama-7B-Instruct is tested"],"requires":["VS Code","For OpenAI: API key with active credits","For Llama.cpp: ModelFusion Llama.cpp installation, CodeLlama-7B-Instruct model (~7GB), sufficient local compute (CPU or GPU)"],"input_types":["model selection (configuration setting)"],"output_types":["AI responses from selected backend (text)"],"categories":["tool-use-integration","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"vscode-rubberduck-rubberduck-vscode__cap_9","uri":"capability://tool.use.integration.vs.code.sidebar.panel.integration.with.persistent.chat.history","name":"vs code sidebar panel integration with persistent chat history","description":"Provides a dedicated sidebar panel in VS Code where all AI interactions (code generation, explanations, tests, bug reports, conversations) are displayed and managed. The panel serves as the primary UI for Rubberduck, showing conversation threads, generated code, and explanations. The sidebar maintains chat history within the session, allowing users to scroll through previous interactions and reference earlier responses. The panel includes toolbar buttons for 'Start new chat' and 'Generate Code' for quick access to common actions.","intents":["View all AI interactions in one organized location without cluttering the editor","Reference previous code generation or explanations without re-running prompts","Manage multiple conversation threads within a single panel","Access AI features via toolbar buttons without memorizing keyboard shortcuts"],"best_for":["developers who prefer UI-driven interaction over command palette","teams wanting a centralized location for AI-assisted development","developers who frequently reference previous AI outputs"],"limitations":["Sidebar panel takes up editor space — reduces available width for code editing","Chat history is not persisted across VS Code sessions — closing the extension loses conversation history","No export or sharing of chat history — conversations cannot be saved or shared with teammates","Limited customization of panel layout or appearance","No integration with VS Code's native chat or comment features"],"requires":["VS Code (minimum version unknown, likely 1.50+)"],"input_types":["user interactions (button clicks, text input)"],"output_types":["sidebar panel UI with chat history and generated content"],"categories":["tool-use-integration","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0}],"trust":{"score":44,"verified":false,"data_access_risk":"moderate","permissions":["VS Code (minimum version unknown, likely 1.50+)","OpenAI API key with active credits, OR local Llama.cpp setup with CodeLlama-7B-Instruct model (~7GB download)","Internet connectivity for OpenAI mode","VS Code (minimum version unknown)","OpenAI API key with active credits, OR Llama.cpp local setup","Code selection in active editor","VS Code","Knowledge of keyboard shortcuts (or willingness to customize keybindings)","OpenAI API key, OR Llama.cpp local setup","Error message or stack trace (provided as text input)"],"failure_modes":["No multi-file context awareness — only uses current editor selection, not project structure or imports","Generated code quality depends entirely on OpenAI model capabilities and prompt clarity","No syntax validation before insertion — generated code may contain errors requiring manual fixes","Experimental Llama.cpp mode with CodeLlama-7B-Instruct produces lower-quality output than OpenAI","Rate-limited by OpenAI API quotas if using free tier","Requires explicit code selection — cannot edit entire files without selecting them first","Diff viewer theme compatibility issues — syntax highlighting 'might not work with all themes' per documentation","No undo integration with VS Code's native undo stack — changes applied directly to editor","Single-selection editing only — cannot batch-edit multiple code blocks in one operation","No git integration — changes not automatically staged or committed","builder identity is not verified yet","no observed match outcomes yet"],"rank_breakdown":{"adoption":0.51,"quality":0.47,"ecosystem":0.35000000000000003,"match_graph":0.25,"freshness":0.75,"weights":{"adoption":0.25,"quality":0.25,"ecosystem":0.15,"match_graph":0.23,"freshness":0.12}},"observed_outcomes":{"matches":0,"success_rate":0,"avg_confidence":0,"top_intents":[],"last_matched_at":null},"maintenance":{"status":"active","updated_at":"2026-05-24T12:16:34.803Z","last_scraped_at":"2026-05-03T15:20:35.026Z","last_commit":null},"community":{"stars":null,"forks":null,"weekly_downloads":null,"model_downloads":null,"model_likes":null}},"distribution":{"claim_url":"https://unfragile.ai/submit?claim=rubberduck-chatgpt-for-visual-studio-code","compare_url":"https://unfragile.ai/compare?artifact=rubberduck-chatgpt-for-visual-studio-code"}},"signature":"r34K37oSJZgh0y3tET2sYb6bfZhWZdkJ4pOdlzhM5GeQ/fy5+H0X25qEojRRSJfWgUIGqczhcrhCxyPX3qEYBg==","signedAt":"2026-06-21T07:46:54.411Z","signedBy":"unfragile.ai","version":1},"_links":{"self":"https://unfragile.ai/api/v1/passport/rubberduck-chatgpt-for-visual-studio-code","artifact":"https://unfragile.ai/rubberduck-chatgpt-for-visual-studio-code","verify":"https://unfragile.ai/api/v1/verify?slug=rubberduck-chatgpt-for-visual-studio-code","publicKey":"https://unfragile.ai/api/v1/trust-passport-public-key","spec":"https://unfragile.ai/trust","schema":"https://unfragile.ai/schema.json","docs":"https://unfragile.ai/docs"}}