{"passport":{"unfragile":{"@version":"1.0","version":"2026-05","artifact":{"id":"vscode-genieai-chatgpt-vscode","slug":"chatgpt-genie-ai","name":"ChatGPT - Genie AI","type":"extension","url":"https://marketplace.visualstudio.com/items?itemName=genieai.chatgpt-vscode","page_url":"https://unfragile.ai/chatgpt-genie-ai","categories":["code-editors"],"tags":["ai","bard","chatgpt","codex","copilot","find bugs","gpt","gpt3","gpt3.5","gpt4","gpt4o","keybindings","lamda","openai","testing"],"pricing":{"model":"freemium","free":true,"starting_price":null},"status":"active","verified":false},"capabilities":[{"id":"vscode-genieai-chatgpt-vscode__cap_0","uri":"capability://text.generation.language.multi.turn.conversational.code.analysis.with.streaming.responses","name":"multi-turn conversational code analysis with streaming responses","description":"Maintains persistent, multi-turn conversations within a VS Code sidebar panel that streams responses token-by-token from OpenAI or Azure OpenAI APIs. The extension preserves conversation history to disk in a local state store, enabling users to resume previous discussions across editor sessions. Streaming is implemented with cancellation support to allow users to stop token generation mid-response, reducing API costs for long-running queries.","intents":["I want to ask my AI pair programmer about code patterns without leaving the editor","I need to continue a previous conversation about a bug I was debugging yesterday","I want to see the AI's response appear in real-time as it generates tokens"],"best_for":["solo developers building features iteratively with AI guidance","teams learning new codebases through conversational exploration","developers who want persistent context across multiple work sessions"],"limitations":["Conversation context is limited by the selected model's token window (GPT-3.5-turbo: 4k, GPT-4: 8k-128k); older conversations may be truncated if context exceeds limits","No automatic context pruning or summarization — users must manually manage conversation length to avoid token exhaustion","Streaming cancellation stops token generation but does not refund already-consumed tokens from the OpenAI API","Conversation storage is unencrypted on local disk; sensitive code or API keys in chat history are stored in plaintext"],"requires":["VS Code 1.50+ (assumed minimum, not explicitly documented)","Valid OpenAI API key or Azure OpenAI Service credentials","Internet connectivity to reach OpenAI or Azure endpoints","Disk space for local conversation history storage (typically <100MB for thousands of conversations)"],"input_types":["natural language text (user queries)","code snippets (pasted or selected from editor)","error messages (from VS Code Problems window)"],"output_types":["streamed text responses","code suggestions","explanations and analysis"],"categories":["text-generation-language","memory-knowledge"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"vscode-genieai-chatgpt-vscode__cap_1","uri":"capability://code.generation.editing.editor.integrated.code.generation.with.one.click.file.creation","name":"editor-integrated code generation with one-click file creation","description":"Generates new code files directly into the VS Code workspace by sending the current editor context and user prompt to the selected LLM model, then automatically creates the file with the generated content. The extension integrates with VS Code's file creation APIs to place generated files in the workspace root or a user-specified directory, bypassing manual file creation steps.","intents":["I want to generate a new component or utility file without manually creating the file first","I need to scaffold boilerplate code (e.g., React component, test file) with one click","I want the AI to create a new file based on my current code context"],"best_for":["developers scaffolding new files in greenfield projects","teams standardizing on AI-generated boilerplate to reduce setup time","developers working in languages with verbose boilerplate (Java, C#, TypeScript)"],"limitations":["File creation is synchronous and blocks the editor UI during generation; no background task queue for batch file creation","No built-in conflict detection — if a file with the same name exists, the extension will overwrite it without warning","Generated files are not automatically formatted according to workspace `.prettierrc` or `.editorconfig` settings; manual formatting required","No template system — each file generation starts from scratch rather than using project-specific templates or patterns"],"requires":["VS Code 1.50+","Valid OpenAI API key or Azure OpenAI credentials","Write permissions to the VS Code workspace directory","Selected LLM model configured in extension settings"],"input_types":["natural language prompt (e.g., 'Create a React component for a user profile card')","current editor context (optional, can be included in prompt)","file type or language specification (inferred from prompt or explicit)"],"output_types":["generated source code file","file path confirmation in editor"],"categories":["code-generation-editing","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"vscode-genieai-chatgpt-vscode__cap_10","uri":"capability://code.generation.editing.language.agnostic.code.analysis.and.generation.across.40.languages","name":"language-agnostic code analysis and generation across 40+ languages","description":"Supports code analysis and generation for 40+ programming languages (JavaScript, Python, Java, C++, Go, Rust, etc.) by leveraging the underlying LLM's multilingual code understanding. The extension does not perform language-specific parsing or validation — instead, it sends raw code to the LLM and relies on the model's training data to understand syntax and semantics. Language detection is implicit based on file extension or user specification.","intents":["I want to generate code in a language I'm not familiar with","I need the AI to refactor code in multiple languages within the same project","I want to learn a new language by asking the AI to explain code patterns"],"best_for":["polyglot developers working across multiple languages","teams with mixed-language codebases (e.g., Python backend + JavaScript frontend)","developers learning new languages with AI guidance"],"limitations":["Language support is limited by the LLM's training data — obscure or newly-released languages may have poor code generation quality","No language-specific linting or validation — generated code may not follow language conventions or best practices","Error diagnosis relies on error messages from language servers — if the language server is not configured, error analysis is unavailable","Code generation quality varies significantly by language — GPT-4 is stronger in Python and JavaScript than in Rust or Go","No syntax highlighting or language-specific formatting for generated code — users must manually format or rely on workspace formatters"],"requires":["VS Code 1.50+","Valid OpenAI API key","File extension or language specification to identify the target language","Optional: language server for error diagnosis (e.g., TypeScript, Pylint)"],"input_types":["code in any supported language","natural language instruction (language-agnostic)","error messages from language servers"],"output_types":["generated code in the target language","explanations and analysis (language-agnostic)"],"categories":["code-generation-editing"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"vscode-genieai-chatgpt-vscode__cap_11","uri":"capability://memory.knowledge.local.conversation.persistence.with.unencrypted.disk.storage","name":"local conversation persistence with unencrypted disk storage","description":"Stores all conversations to the local file system in an unencrypted format, allowing users to resume conversations across editor sessions without relying on cloud storage or external services. Conversation data is serialized to disk automatically after each message, and users can browse saved conversations in the sidebar. The storage location is managed by VS Code's extension storage API, typically in the user's home directory under `.vscode/extensions/genieai.chatgpt-vscode-*/`.","intents":["I want to continue a conversation about a bug I was debugging yesterday","I need to keep a local record of my AI-assisted development without uploading to the cloud","I want to switch between multiple conversations without losing context"],"best_for":["developers who prefer local-first data storage over cloud-based conversation history","teams with data residency requirements that prohibit cloud storage","developers who want to version-control or archive conversations locally"],"limitations":["Conversations are stored in plaintext without encryption — sensitive code or API keys in chat history are exposed to local file system access","No automatic backup or redundancy — conversations are lost if the local storage directory is deleted or corrupted","Storage location is not user-configurable — conversations are stored in VS Code's extension directory, which may be on a slow or space-constrained drive","No compression or deduplication — large conversation histories can consume significant disk space (potentially hundreds of MB)","Conversation data is not synced across devices — users cannot access conversations on different machines unless they manually export and import"],"requires":["VS Code 1.50+","Disk space for conversation storage (typically <100MB for thousands of conversations)","Write permissions to the VS Code extension storage directory","No cloud connectivity required (conversations are purely local)"],"input_types":["conversation turns (user messages and AI responses)","metadata (timestamps, model used, token count)"],"output_types":["serialized conversation data on disk","conversation list in sidebar"],"categories":["memory-knowledge","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"vscode-genieai-chatgpt-vscode__cap_12","uri":"capability://code.generation.editing.test.generation.and.code.quality.analysis","name":"test generation and code quality analysis","description":"Generates unit tests, integration tests, or test cases based on existing code by sending the code and a test generation prompt to the LLM. The extension can analyze code for potential bugs, edge cases, or quality issues and suggest test cases to cover them. Generated tests are returned as code snippets that users can apply to their test files using the diff-and-apply mechanism.","intents":["I want to generate unit tests for a function without writing them manually","I need to identify edge cases and generate test cases to cover them","I want the AI to suggest tests for untested code in my project"],"best_for":["developers improving code coverage with AI-generated tests","teams enforcing test-driven development practices","developers learning testing patterns by examining AI-generated test cases"],"limitations":["Generated tests are not automatically executed — users must manually run tests to verify they pass","Test generation quality depends on the code's clarity and the LLM's understanding of the testing framework — poorly-documented code may result in poor tests","No framework-specific optimization — generated tests may not follow the team's testing conventions or use the preferred assertion library","Generated tests may have false positives or false negatives — they require manual review before being committed","No integration with test runners — generated tests are returned as code snippets, not automatically added to the test suite"],"requires":["VS Code 1.50+","Valid OpenAI API key","Code to generate tests for (function, class, or module)","Optional: knowledge of the testing framework used in the project"],"input_types":["source code (function, class, or module)","optional: existing test examples (for style matching)","optional: test framework specification (e.g., Jest, pytest, JUnit)"],"output_types":["generated test code","test case suggestions","edge case analysis"],"categories":["code-generation-editing","planning-reasoning"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"vscode-genieai-chatgpt-vscode__cap_13","uri":"capability://code.generation.editing.bug.detection.and.code.review.assistance","name":"bug detection and code review assistance","description":"Analyzes code for potential bugs, security vulnerabilities, performance issues, or code smell by sending code snippets to the LLM. The extension can review code in the editor, analyze error messages, or examine diffs to identify issues and suggest fixes. Code review is conversational — users can ask follow-up questions about detected issues and request explanations or alternative solutions.","intents":["I want the AI to review my code for bugs before committing","I need to identify security vulnerabilities in my code","I want to understand why a particular code pattern is problematic"],"best_for":["developers performing self-code-review before submitting pull requests","teams augmenting human code review with AI analysis","developers learning code quality best practices through AI feedback"],"limitations":["Bug detection is heuristic-based and may miss subtle bugs or false positives — AI suggestions require human verification","Security analysis is limited to common vulnerability patterns — zero-day vulnerabilities or framework-specific issues may not be detected","No integration with static analysis tools (e.g., SonarQube, Checkmarx) — analysis is purely LLM-based without formal verification","Context is limited to the selected code — cross-file bugs or architectural issues may not be detected","No severity classification — all detected issues are presented equally without prioritization"],"requires":["VS Code 1.50+","Valid OpenAI API key","Code to review (function, class, file, or diff)","Optional: knowledge of the codebase's architecture and dependencies"],"input_types":["source code (any language)","error messages or stack traces","diffs (for change review)"],"output_types":["bug and vulnerability suggestions","code quality feedback","explanations and fix recommendations"],"categories":["code-generation-editing","planning-reasoning"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"vscode-genieai-chatgpt-vscode__cap_2","uri":"capability://code.generation.editing.side.by.side.diff.visualization.with.one.click.code.application","name":"side-by-side diff visualization with one-click code application","description":"Generates code modifications and displays them in VS Code's built-in diff viewer, showing original code on the left and AI-suggested changes on the right. Users can review the diff and apply changes with a single click, which updates the editor buffer. The extension uses VS Code's `TextEditor.edit()` API to apply changes atomically, ensuring undo/redo compatibility.","intents":["I want to see exactly what the AI is changing before applying it to my code","I need to refactor a function and want to compare the original vs. AI-suggested version","I want to apply a bug fix suggested by the AI with one click"],"best_for":["developers who prioritize code review and safety over speed","teams with code review policies requiring visibility into AI-generated changes","developers learning from AI suggestions by comparing original and refactored code"],"limitations":["Diff viewer is read-only — users cannot edit the suggested code within the diff view; they must apply it first and then edit","Multi-file diffs are not supported — only single-file changes can be visualized and applied","Diff generation is not incremental — each new suggestion replaces the previous diff, with no history of past suggestions","Large diffs (>10,000 lines) may cause performance degradation in the diff viewer due to VS Code's rendering limitations"],"requires":["VS Code 1.50+","Valid OpenAI API key","An open editor with code content","Sufficient context window in the selected model to process the full file"],"input_types":["current editor file content","natural language instruction (e.g., 'refactor this function to use async/await')","optional: specific line range or selection"],"output_types":["diff visualization (original vs. suggested)","applied code changes to editor buffer"],"categories":["code-generation-editing","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"vscode-genieai-chatgpt-vscode__cap_3","uri":"capability://code.generation.editing.compile.time.error.diagnosis.and.quick.fix.generation","name":"compile-time error diagnosis and quick-fix generation","description":"Integrates with VS Code's Problems window to detect compile-time errors and warnings, then sends the error message, file context, and code snippet to the LLM to generate explanations and suggested fixes. The extension registers Quick Fix actions in the Problems panel, allowing users to apply AI-suggested fixes directly from the error diagnostic. Fixes are applied using the same diff-and-apply mechanism as code modification.","intents":["I see a TypeScript error in the Problems window and want the AI to explain what went wrong","I want the AI to suggest a fix for a linting error without leaving the editor","I need to understand why my code is failing to compile and get a quick fix"],"best_for":["developers learning new languages or frameworks by understanding compiler errors","teams using strict linting rules who want AI-assisted compliance","developers debugging type errors in TypeScript or similar statically-typed languages"],"limitations":["Only works with errors/warnings that appear in VS Code's Problems window — requires a language server or linter integration (e.g., ESLint, TypeScript, Pylint)","Error diagnosis is context-limited to the file containing the error; cross-file type errors may not be fully understood by the LLM","Quick fixes are generated based on the error message alone; if the error message is cryptic or non-standard, the AI may produce incorrect suggestions","No validation that the suggested fix actually resolves the error — users must manually verify that the fix works","Can be disabled via `genieai.quickFix.enable` setting, but there is no per-error-type granularity (all-or-nothing toggle)"],"requires":["VS Code 1.50+","Valid OpenAI API key","A language server or linter configured in the workspace (e.g., TypeScript, ESLint, Pylint)","At least one error or warning in the Problems window"],"input_types":["error/warning message from VS Code diagnostics","file content surrounding the error","error line number and column"],"output_types":["natural language explanation of the error","suggested code fix","diff visualization of the fix"],"categories":["code-generation-editing","planning-reasoning"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"vscode-genieai-chatgpt-vscode__cap_4","uri":"capability://text.generation.language.git.aware.commit.message.generation.from.staged.changes","name":"git-aware commit message generation from staged changes","description":"Analyzes staged files in the git index by reading the git diff output, then sends the diff to the LLM to generate a semantically meaningful commit message. The extension integrates with VS Code's Source Control panel and can be invoked via the command palette (`Genie: Generate a commit message`) or a custom keybinding. Generated messages follow conventional commit format (e.g., 'feat: add user authentication') and can be customized via the `genieai.promptPrefix.commit-message` setting.","intents":["I want to generate a commit message based on my staged changes without writing it manually","I need to follow conventional commit format and want the AI to enforce it","I want to customize the commit message template for my team's standards"],"best_for":["developers working in git-based workflows who want to save time on commit messages","teams enforcing conventional commits or semantic versioning","developers who struggle to write clear, descriptive commit messages"],"limitations":["Only analyzes staged changes (git index) — unstaged changes are ignored, which may miss important context","Commit message generation is based on diffs alone; if the diff is unclear or lacks context, the generated message may be generic or inaccurate","No integration with git hooks (pre-commit, commit-msg) — the generated message must be manually copied into the commit dialog","Large diffs (>50KB) may exceed the LLM's context window, resulting in truncated or incomplete analysis","Can be disabled via `genieai.enableGenerateCommitMessage` setting, but there is no per-repository configuration"],"requires":["VS Code 1.50+","Valid OpenAI API key","A git repository initialized in the workspace","At least one staged file in the git index","Git CLI available in the system PATH"],"input_types":["git diff output (staged changes only)","optional: custom prompt prefix from settings"],"output_types":["generated commit message (text)","optional: formatted according to conventional commits"],"categories":["text-generation-language","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"vscode-genieai-chatgpt-vscode__cap_5","uri":"capability://tool.use.integration.multi.model.llm.selection.with.openai.and.azure.openai.support","name":"multi-model llm selection with openai and azure openai support","description":"Allows users to select from a curated list of OpenAI models (GPT-4o, GPT-4 Turbo, GPT-3.5-turbo, o1-preview, o1-mini) or deploy custom models via Azure OpenAI Service. The extension stores the selected model in VS Code settings and routes all API calls through the chosen model's endpoint. Model selection is configurable via the extension settings UI, with fallback to a default model if none is explicitly selected.","intents":["I want to use GPT-4o for complex code generation tasks but GPT-3.5-turbo for simple queries to save costs","I need to use Azure OpenAI Service instead of the public OpenAI API for compliance reasons","I want to switch between models without restarting the editor"],"best_for":["developers optimizing for cost vs. quality by switching models per task","enterprises using Azure OpenAI Service for data residency or compliance","teams experimenting with different models to find the best fit for their workflow"],"limitations":["Model selection is global — all conversations and code generation use the same model; no per-task model selection","o1-preview and o1-mini have 'usage tier limitations' (not detailed in documentation), which may restrict availability based on account status","No automatic model fallback if the selected model is unavailable or rate-limited; users must manually switch models","Model-specific features (e.g., vision capabilities, function calling) are not explicitly documented, so users may attempt unsupported operations","Azure OpenAI configuration method is not documented; users must manually configure endpoint and deployment name (mechanism unknown)"],"requires":["VS Code 1.50+","Valid API key for OpenAI or Azure OpenAI Service","Internet connectivity to the selected API endpoint","For Azure: Azure OpenAI Service deployment with the desired model"],"input_types":["model name selection (from dropdown or settings)","API key (OpenAI or Azure)"],"output_types":["selected model identifier (stored in settings)","API endpoint configuration"],"categories":["tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"vscode-genieai-chatgpt-vscode__cap_6","uri":"capability://text.generation.language.custom.system.message.and.prompt.template.configuration","name":"custom system message and prompt template configuration","description":"Allows users to define a custom system message via the `genieai.systemMessage` setting, which is prepended to every conversation and code generation request. Additionally, commit message generation can be customized via `genieai.promptPrefix.commit-message`, enabling teams to enforce specific conventions or add context (e.g., 'Always include Jira ticket ID'). These settings are stored in VS Code's user or workspace settings, allowing per-project customization.","intents":["I want to set a system message that tells the AI to follow my team's coding standards","I need to customize commit message generation to include Jira ticket IDs","I want to configure the AI's behavior differently for different projects"],"best_for":["teams standardizing AI behavior across developers via workspace settings","developers who want to inject domain-specific context (e.g., 'You are a Python expert') into every request","organizations enforcing compliance or security policies via AI configuration"],"limitations":["System message is applied globally to all conversations — no per-conversation override","Prompt templates are limited to commit message generation; other features (code generation, error diagnosis) do not support customization","No validation of custom prompts — malformed or contradictory prompts may produce unexpected results","System message is stored in plaintext in VS Code settings; sensitive information (e.g., API keys, internal guidelines) should not be included","No template variables or dynamic substitution — prompts are static strings without support for file names, branch names, or other context"],"requires":["VS Code 1.50+","Access to VS Code settings (user or workspace level)","Understanding of prompt engineering to write effective custom messages"],"input_types":["custom system message (text)","custom commit message prompt prefix (text)"],"output_types":["modified API requests with custom system message prepended","customized commit messages following the template"],"categories":["text-generation-language","planning-reasoning"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"vscode-genieai-chatgpt-vscode__cap_7","uri":"capability://memory.knowledge.conversation.history.export.and.markdown.serialization","name":"conversation history export and markdown serialization","description":"Exports all saved conversations to markdown format, allowing users to archive, share, or version-control their chat history. The export includes the full conversation thread with timestamps, model information, and code snippets. Conversations are stored locally on disk in an unencrypted format, and the extension provides a bulk export feature to save all conversations to a single markdown file or individual files per conversation.","intents":["I want to export a conversation about a bug fix to share with my team","I need to archive my conversations for compliance or documentation purposes","I want to version-control my AI-assisted development process"],"best_for":["teams documenting AI-assisted development decisions","developers maintaining a knowledge base of AI-generated solutions","organizations with compliance requirements to archive AI interactions"],"limitations":["Exported markdown is static — changes to the original conversation do not update the export","No built-in import functionality — exported conversations cannot be re-imported into the extension","Conversations are stored unencrypted on disk; sensitive code or API keys in chat history are exposed to local file system access","Export format is not standardized or documented — markdown structure may change between extension versions","No selective export — bulk export exports all conversations; individual conversation export is not documented"],"requires":["VS Code 1.50+","At least one saved conversation in the extension's local storage","Disk space to store exported markdown files","Write permissions to the export destination directory"],"input_types":["conversation history (stored locally)","export destination path (optional, defaults to user's home directory)"],"output_types":["markdown file(s) containing conversation transcripts","optional: metadata (timestamps, model used, token count)"],"categories":["memory-knowledge","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"vscode-genieai-chatgpt-vscode__cap_8","uri":"capability://memory.knowledge.editor.context.injection.with.file.selection.and.code.snippets","name":"editor context injection with file selection and code snippets","description":"Allows users to include the current editor file content, selected code snippets, or specific line ranges in their prompts to the AI. The extension automatically includes editor context when generating code or analyzing errors, and users can explicitly select code to include additional context. Context is sent as part of the API request to the LLM, enabling the AI to provide file-aware suggestions.","intents":["I want to ask the AI about a specific function in my file without copying and pasting it","I need the AI to understand the full file context when suggesting refactorings","I want to select a code snippet and ask the AI to explain or improve it"],"best_for":["developers working with large files who want to provide focused context","teams using the AI for code review and analysis within the editor","developers learning code patterns by asking the AI about specific snippets"],"limitations":["Context is limited by the selected model's token window — large files may be truncated or excluded entirely","No automatic context pruning — users must manually manage context size to avoid token exhaustion","Context is sent in plaintext to the OpenAI API — sensitive code or credentials in the file are transmitted unencrypted","No cross-file context — the AI cannot automatically include related files or dependencies; users must manually copy context from other files","Context injection is implicit for some features (error diagnosis, code generation) but explicit for others (chat), leading to inconsistent behavior"],"requires":["VS Code 1.50+","Valid OpenAI API key","An open editor with code content","Sufficient token budget in the selected model to accommodate file context"],"input_types":["full editor file content (automatic)","selected code snippet (explicit selection)","line range (optional, for focused context)"],"output_types":["API request with context prepended","file-aware AI suggestions"],"categories":["memory-knowledge","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"vscode-genieai-chatgpt-vscode__cap_9","uri":"capability://automation.workflow.streaming.response.cancellation.with.token.cost.optimization","name":"streaming response cancellation with token cost optimization","description":"Implements token-level cancellation for streaming responses, allowing users to stop the AI mid-generation by clicking a cancel button or pressing Escape. When cancelled, the extension stops consuming tokens from the OpenAI API, reducing costs for long-running or verbose responses. Cancellation is implemented via the OpenAI streaming API's abort mechanism, which closes the HTTP connection and stops token generation.","intents":["I want to stop the AI from generating a long response that's going in the wrong direction","I need to save API costs by cancelling verbose or repetitive responses","I want to interrupt the AI and ask a follow-up question without waiting for the full response"],"best_for":["developers optimizing API costs by cancelling unnecessary token generation","users with limited API budgets who want fine-grained control over token consumption","developers iterating quickly and wanting to interrupt long responses"],"limitations":["Cancellation stops token generation but does not refund already-consumed tokens — partial responses are still billed","No token count estimation before generation — users cannot predict response length before committing to the request","Cancellation is manual — no automatic timeout or max-token limits to prevent runaway responses","Cancelled responses are not saved to conversation history — users lose the partial response if they want to review it later"],"requires":["VS Code 1.50+","Valid OpenAI API key with active billing","An active streaming response in progress","Keyboard or mouse input to trigger cancellation"],"input_types":["streaming response from OpenAI API","user cancellation signal (Escape key or cancel button)"],"output_types":["aborted HTTP connection to OpenAI","partial response text (if any tokens were generated before cancellation)"],"categories":["automation-workflow","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0}],"trust":{"score":53,"verified":false,"data_access_risk":"high","permissions":["VS Code 1.50+ (assumed minimum, not explicitly documented)","Valid OpenAI API key or Azure OpenAI Service credentials","Internet connectivity to reach OpenAI or Azure endpoints","Disk space for local conversation history storage (typically <100MB for thousands of conversations)","VS Code 1.50+","Valid OpenAI API key or Azure OpenAI credentials","Write permissions to the VS Code workspace directory","Selected LLM model configured in extension settings","Valid OpenAI API key","File extension or language specification to identify the target language"],"failure_modes":["Conversation context is limited by the selected model's token window (GPT-3.5-turbo: 4k, GPT-4: 8k-128k); older conversations may be truncated if context exceeds limits","No automatic context pruning or summarization — users must manually manage conversation length to avoid token exhaustion","Streaming cancellation stops token generation but does not refund already-consumed tokens from the OpenAI API","Conversation storage is unencrypted on local disk; sensitive code or API keys in chat history are stored in plaintext","File creation is synchronous and blocks the editor UI during generation; no background task queue for batch file creation","No built-in conflict detection — if a file with the same name exists, the extension will overwrite it without warning","Generated files are not automatically formatted according to workspace `.prettierrc` or `.editorconfig` settings; manual formatting required","No template system — each file generation starts from scratch rather than using project-specific templates or patterns","Language support is limited by the LLM's training data — obscure or newly-released languages may have poor code generation quality","No language-specific linting or validation — generated code may not follow language conventions or best practices","builder identity is not verified yet","no observed match outcomes yet"],"rank_breakdown":{"adoption":0.8,"quality":0.5,"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":"2026-05-03T15:20:29.937Z","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=chatgpt-genie-ai","compare_url":"https://unfragile.ai/compare?artifact=chatgpt-genie-ai"}},"signature":"W5i6X/+6+/hUJHwaTv5cjDcrE6Iy7x/vW1Tt/BkKlsHisQybLAFLyTzizC40ij81mxYjud+pwsHvxUVY17QxDA==","signedAt":"2026-06-20T16:17:33.773Z","signedBy":"unfragile.ai","version":1},"_links":{"self":"https://unfragile.ai/api/v1/passport/chatgpt-genie-ai","artifact":"https://unfragile.ai/chatgpt-genie-ai","verify":"https://unfragile.ai/api/v1/verify?slug=chatgpt-genie-ai","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"}}