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The extension captures the highlighted code, constructs a prompt asking for explanation, and displays results in a new VS Code tab without modifying the original file. This preserves the user's workflow by keeping explanations separate from source code.","intents":["I need to understand what this code block does","I want to document legacy code I just inherited","I'm learning a new language and need line-by-line walkthroughs"],"best_for":["junior developers learning codebases","teams onboarding new members to legacy systems","developers reviewing unfamiliar code during code review"],"limitations":["Only analyzes selected code blocks, not full file context or project structure","Results appear in new tabs requiring manual copy/paste to preserve explanations","No caching of explanations — each selection triggers a new API call and incurs token costs","Cannot analyze code across multiple files or understand project-level dependencies"],"requires":["VS Code installed","OpenAI API key from https://platform.openai.com/account/api-keys","Active internet connection to reach OpenAI API","Code selection in editor (minimum 1 character)"],"input_types":["code (any language supported by OpenAI models)"],"output_types":["text (natural language explanation)"],"categories":["code-generation-editing","developer-tools"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"vscode-manassahu-openai-developer__cap_1","uri":"capability://code.generation.editing.interactive.debugging.assistance.via.code.selection","name":"interactive debugging assistance via code selection","description":"Accepts user-selected code blocks and sends them to OpenAI's API with a debugging-focused prompt to identify logical errors, runtime issues, or edge cases. The extension constructs a request asking 'why is this code not working' and returns analysis in a new tab. Unlike static linters, this uses natural language reasoning to identify semantic bugs, missing null checks, or algorithmic flaws that syntax checkers miss.","intents":["I have a bug in my code and can't figure out why it's not working","I need help understanding why my function returns unexpected results","I want to identify potential runtime errors before testing"],"best_for":["developers debugging production issues","QA engineers analyzing failing code paths","junior developers learning debugging techniques"],"limitations":["Requires manual code selection — cannot automatically detect errors across a file","No access to runtime state, variable values, or stack traces — analysis is static","May produce false positives or miss context-dependent bugs without full project understanding","Each debugging query consumes tokens; no caching or learning from previous fixes","Cannot execute code or test proposed fixes automatically"],"requires":["VS Code installed","OpenAI API key configured","Active internet connection","Code selection in editor"],"input_types":["code (any language)"],"output_types":["text (debugging analysis and suggestions)"],"categories":["code-generation-editing","planning-reasoning"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"vscode-manassahu-openai-developer__cap_2","uri":"capability://text.generation.language.free.form.conversational.q.a.with.model.switching","name":"free-form conversational q&a with model switching","description":"Provides a command-palette-triggered chat interface that accepts arbitrary user questions and routes them to either ChatGPT (GPT-3.5) or Codex based on user preference. The extension maintains a conversation session within a VS Code tab, sending each user message to the OpenAI API and streaming or displaying responses. Users can switch between models via settings without restarting the extension, enabling experimentation with different reasoning styles (ChatGPT for general knowledge, Codex for code-specific queries).","intents":["I want to ask ChatGPT questions without leaving my editor","I need quick answers about programming concepts or syntax","I want to compare how ChatGPT and Codex respond to the same question"],"best_for":["developers who spend most time in VS Code and want to minimize context switching","teams experimenting with different OpenAI models for different tasks","developers building AI-assisted workflows within their editor"],"limitations":["Conversation history is not persisted between sessions — each VS Code restart loses chat context","No built-in conversation memory or summarization — long conversations may exceed token limits","Model switching requires manual preference change; no per-query model selection","Responses limited by maxTokens setting (default 1024) — long-form answers may be truncated","No integration with code context unless user manually pastes code into the chat"],"requires":["VS Code installed","OpenAI API key configured","Active internet connection","Model selection via settings (ChatGPT or Codex)"],"input_types":["text (natural language questions)"],"output_types":["text (natural language responses)"],"categories":["text-generation-language","planning-reasoning"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"vscode-manassahu-openai-developer__cap_3","uri":"capability://image.visual.text.to.image.generation.with.dall.e.backend","name":"text-to-image generation with dall-e backend","description":"Accepts text descriptions via command palette and generates images using OpenAI's image generation API (likely DALL-E, though not explicitly documented). The extension sends the user's text prompt to OpenAI, retrieves the generated image URL, and displays it in a new VS Code tab or opens it in the default image viewer. This enables developers to quickly prototype UI mockups, generate placeholder graphics, or visualize design concepts without leaving the editor.","intents":["I need to generate a quick placeholder image for a UI mockup","I want to visualize a design concept without opening Photoshop","I need to create graphics for documentation or presentations"],"best_for":["full-stack developers prototyping UIs","technical writers creating visual documentation","designers collaborating with developers in VS Code"],"limitations":["Image generation model is not explicitly specified (assumed DALL-E based on OpenAI product line)","No image editing capabilities — generated images cannot be modified within the extension","Results are URLs or external files; no built-in image storage or version history","Image generation is significantly more expensive than text API calls (OpenAI charges per image)","No batch image generation or style/quality parameters exposed in the UI","Generated images may have copyright or licensing restrictions depending on OpenAI's terms"],"requires":["VS Code installed","OpenAI API key with image generation credits","Active internet connection","Text description of desired image"],"input_types":["text (image description/prompt)"],"output_types":["image (URL or file path to generated image)"],"categories":["image-visual","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"vscode-manassahu-openai-developer__cap_4","uri":"capability://automation.workflow.configurable.model.selection.and.token.management","name":"configurable model selection and token management","description":"Exposes VS Code settings to allow users to switch between ChatGPT (GPT-3.5) and Codex models, configure maximum token output (default 1024), and adjust temperature (if fully implemented). The extension reads these settings at runtime and routes API requests to the selected model with the specified parameters. This enables users to optimize for different use cases: ChatGPT for general reasoning, Codex for code-specific tasks, and token limits to control costs and response length.","intents":["I want to use Codex for code generation but ChatGPT for general questions","I need to limit response length to avoid token overages","I want to experiment with different temperature settings for more/less creative responses"],"best_for":["teams experimenting with different OpenAI models","developers managing API costs and token budgets","users optimizing for specific use cases (code vs. general knowledge)"],"limitations":["Temperature setting documentation is incomplete — full range and default value unknown","Model switching requires manual preference change; no per-query model selection","Token limit applies globally to all queries; no per-capability customization","No cost estimation or token usage tracking within the extension — users must monitor OpenAI dashboard","Settings require VS Code restart or manual reload to take effect (standard VS Code behavior)"],"requires":["VS Code 1.0+ (assumed, not explicitly specified)","Access to VS Code Preferences (Ctrl+,)","Understanding of OpenAI model differences and token economics"],"input_types":["configuration (model selection, numeric token limit, temperature value)"],"output_types":["configuration (applied settings affecting all subsequent API calls)"],"categories":["automation-workflow","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"vscode-manassahu-openai-developer__cap_5","uri":"capability://tool.use.integration.api.key.management.with.secure.local.storage","name":"api key management with secure local storage","description":"Provides a command-palette command ('OpenAI Developer: Change API Key') that prompts users to enter or update their OpenAI API key. The extension stores the key locally in VS Code's secure storage (using VS Code's built-in secrets API) and retrieves it for each API request without exposing it in logs or settings files. On first use, the extension prompts for an API key if none is configured, enabling zero-friction onboarding.","intents":["I need to configure my OpenAI API key to use this extension","I want to rotate my API key without editing config files","I need to ensure my API key is stored securely and not exposed in version control"],"best_for":["individual developers setting up the extension for the first time","teams managing API keys across multiple developers","security-conscious users who want to avoid storing secrets in plain text"],"limitations":["API key is stored locally in VS Code; if VS Code is compromised, the key is exposed","No key rotation or expiration management — users must manually update keys via command palette","No audit logging of API key usage or access — users cannot track who used the key when","Key is tied to VS Code installation; switching machines requires re-entering the key","No support for environment variables or .env files — only VS Code's secrets storage"],"requires":["VS Code installed","OpenAI API key from https://platform.openai.com/account/api-keys","Access to VS Code command palette (Ctrl+Shift+P)"],"input_types":["text (OpenAI API key string)"],"output_types":["configuration (stored API key, used for all subsequent API calls)"],"categories":["tool-use-integration","safety-moderation"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"vscode-manassahu-openai-developer__cap_6","uri":"capability://code.generation.editing.multi.language.code.analysis.and.explanation","name":"multi-language code analysis and explanation","description":"Accepts code in any programming language supported by OpenAI's models (Python, JavaScript, Java, C++, Go, Rust, etc.) and generates explanations, debugging assistance, or code generation suggestions. The extension does not perform language-specific parsing or AST analysis; instead, it sends raw code text to the OpenAI API, which uses its training data to understand syntax and semantics across languages. This enables a single extension to support dozens of languages without language-specific plugins.","intents":["I need to understand code in a language I don't know well","I want debugging help for code in multiple languages in the same project","I'm learning a new language and need explanations of unfamiliar syntax"],"best_for":["polyglot developers working across multiple languages","teams with codebases in diverse languages (Python backend, JavaScript frontend, Go services)","developers learning new languages and needing contextual explanations"],"limitations":["No language-specific optimizations — analysis quality depends on OpenAI's training data for each language","Cannot perform language-specific refactoring or linting (e.g., PEP-8 for Python)","No syntax highlighting or language-aware formatting in results","Explanations may be less accurate for niche or new languages with limited training data","No integration with language-specific tools (linters, formatters, type checkers)"],"requires":["VS Code installed","OpenAI API key","Code in a language supported by OpenAI models (most mainstream languages)"],"input_types":["code (any language: Python, JavaScript, Java, C++, Go, Rust, etc.)"],"output_types":["text (language-agnostic explanations and suggestions)"],"categories":["code-generation-editing","text-generation-language"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"vscode-manassahu-openai-developer__cap_7","uri":"capability://automation.workflow.tab.based.result.isolation.and.non.destructive.output","name":"tab-based result isolation and non-destructive output","description":"Routes all AI-generated results (explanations, debugging suggestions, image URLs) to new VS Code tabs rather than modifying the user's source files. This design pattern preserves the original code and allows users to review AI suggestions without risk of accidental overwrites. Users can manually copy/paste results back into source files or discard them. The extension never auto-saves or modifies files, maintaining a clear separation between AI suggestions and user-controlled code.","intents":["I want to see AI suggestions without risking changes to my code","I need to compare multiple AI suggestions side-by-side","I want to preserve AI explanations for documentation without modifying source files"],"best_for":["developers who prioritize code safety and want to review changes before applying them","teams with strict code review processes that require human approval before changes","users who want to preserve AI suggestions as documentation"],"limitations":["Results in new tabs require manual copy/paste to apply changes — no one-click apply","No diff view or merge tool to compare original code with AI suggestions","Tab proliferation can clutter the editor if users generate many suggestions","No automatic cleanup of old result tabs — users must manually close them","Cannot modify files directly, limiting automation potential for code generation workflows"],"requires":["VS Code installed","Manual copy/paste workflow to apply changes"],"input_types":["code (selected from editor)"],"output_types":["text (displayed in new VS Code tab)"],"categories":["automation-workflow","safety-moderation"],"confidence":0.5,"matches":0,"success_rate":0}],"trust":{"score":42,"verified":false,"data_access_risk":"high","permissions":["VS Code installed","OpenAI API key from https://platform.openai.com/account/api-keys","Active internet connection to reach OpenAI API","Code selection in editor (minimum 1 character)","OpenAI API key configured","Active internet connection","Code selection in editor","Model selection via settings (ChatGPT or Codex)","OpenAI API key with image generation credits","Text description of desired image"],"failure_modes":["Only analyzes selected code blocks, not full file context or project structure","Results appear in new tabs requiring manual copy/paste to preserve explanations","No caching of explanations — each selection triggers a new API call and incurs token costs","Cannot analyze code across multiple files or understand project-level dependencies","Requires manual code selection — cannot automatically detect errors across a file","No access to runtime state, variable values, or stack traces — analysis is static","May produce false positives or miss context-dependent bugs without full project understanding","Each debugging query consumes tokens; no caching or learning from previous fixes","Cannot execute code or test proposed fixes automatically","Conversation history is not persisted between sessions — each VS Code restart loses chat context","builder identity is not verified yet","no observed match outcomes yet"],"rank_breakdown":{"adoption":0.53,"quality":0.26,"ecosystem":0.35000000000000003,"match_graph":0.25,"freshness":0.9,"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=openai-developer","compare_url":"https://unfragile.ai/compare?artifact=openai-developer"}},"signature":"4L3q6lr9AVYdmwFUOT/uwqvmUBqgQu9T3gF+WFEMGS39GoHEs19N0faB6jkvl9dMCzJftNdldY/u2C3mqmYZCA==","signedAt":"2026-06-15T15:19:08.282Z","signedBy":"unfragile.ai","version":1},"_links":{"self":"https://unfragile.ai/api/v1/passport/openai-developer","artifact":"https://unfragile.ai/openai-developer","verify":"https://unfragile.ai/api/v1/verify?slug=openai-developer","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"}}