{"passport":{"unfragile":{"@version":"1.0","version":"2026-05","artifact":{"id":"vscode-bini-vscode-gemini-assistant","slug":"gemini-assistant","name":"Gemini Assistant","type":"extension","url":"https://marketplace.visualstudio.com/items?itemName=Bini.vscode-gemini-assistant","page_url":"https://unfragile.ai/gemini-assistant","categories":["code-editors"],"tags":["ai","assistant","code completion","code generation","code review","coding","gemini","google","llm"],"pricing":{"model":"freemium","free":true,"starting_price":null},"status":"active","verified":false},"capabilities":[{"id":"vscode-bini-vscode-gemini-assistant__cap_0","uri":"capability://code.generation.editing.selected.code.analysis.with.gemini","name":"selected-code-analysis-with-gemini","description":"Analyzes user-selected code snippets by capturing the current editor selection and sending it to Google's Gemini API via authenticated REST calls, returning markdown-formatted analysis rendered in a dedicated sidebar panel. The extension integrates with VS Code's context menu to trigger analysis without requiring manual copy-paste, maintaining the selection state and file context during the API round-trip.","intents":["I want to understand what this code block does without leaving the editor","I need to review a specific function for bugs or inefficiencies","I want to ask the AI about a code snippet I just selected"],"best_for":["solo developers debugging unfamiliar code","code reviewers seeking quick explanations of complex logic","learners studying codebases they don't own"],"limitations":["Analysis limited to selected text only — cannot automatically infer dependencies or imports from other files","No caching of analysis results — each selection triggers a new API call, increasing latency and quota consumption","Context window limited to selected code; cannot reference project-wide patterns or architectural decisions","Markdown rendering in sidebar may truncate very long responses or complex formatting"],"requires":["VS Code (minimum version unknown, likely 1.50+)","Google Gemini API key with valid authentication","Internet connectivity to reach Google's API endpoints","Selected code in active editor (non-empty selection)"],"input_types":["text (code selection from editor)"],"output_types":["text (markdown-formatted analysis)"],"categories":["code-generation-editing","code-review"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"vscode-bini-vscode-gemini-assistant__cap_1","uri":"capability://code.generation.editing.full.file.code.analysis","name":"full-file-code-analysis","description":"Extends selection-based analysis to entire file contents by reading the active editor's full buffer and submitting it to Gemini for comprehensive analysis. The extension handles file-level context by capturing the complete source code and sending it as a single API request, enabling broader pattern recognition and architectural feedback compared to snippet-level analysis.","intents":["I want to understand the overall structure and purpose of this entire file","I need architectural feedback on how this file fits into the codebase","I want to identify code smells or refactoring opportunities across the whole file"],"best_for":["developers refactoring large functions or classes","architects reviewing module-level design","teams establishing code quality standards"],"limitations":["File size limits imposed by Gemini API token window (typically 1M tokens for gemini-2.0-flash, but practical limit lower for cost/latency)","No multi-file dependency analysis — cannot correlate patterns across imported modules or related files","Analysis does not track file history or git context; cannot suggest improvements based on recent changes","Large files may timeout or incur high API costs depending on model selection"],"requires":["VS Code (minimum version unknown)","Google Gemini API key with sufficient quota","Active file open in editor with readable content","File size within Gemini API token limits (estimated <100KB for practical use)"],"input_types":["text (entire file buffer from active editor)"],"output_types":["text (markdown-formatted file-level analysis)"],"categories":["code-generation-editing","code-review"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"vscode-bini-vscode-gemini-assistant__cap_2","uri":"capability://text.generation.language.conversational.code.questioning","name":"conversational-code-questioning","description":"Enables developers to ask natural language questions about code by composing queries in the sidebar panel and receiving Gemini-generated responses. The extension maintains a conversation history within the sidebar, allowing follow-up questions that reference previous context, with responses rendered as markdown in the panel. Each query is sent to Gemini with the current editor context (selected code or file, depending on user action).","intents":["I want to ask why this code is written this way","I need to understand the intent behind a specific algorithm","I want to ask follow-up questions about code without reselecting it"],"best_for":["developers learning unfamiliar codebases through dialogue","teams documenting implicit knowledge through Q&A","junior developers seeking mentorship-style guidance"],"limitations":["Conversation history is local to the sidebar and not persisted across VS Code sessions unless manually exported to HTML","No automatic context refresh — follow-up questions use the last selected code, not the current selection","Chat history export to HTML is static; cannot re-import or continue conversations from exported files","No multi-turn reasoning or memory of earlier questions in the same session beyond sidebar display"],"requires":["VS Code (minimum version unknown)","Google Gemini API key","Internet connectivity","Code selection or open file to provide context for questions"],"input_types":["text (natural language question from user)"],"output_types":["text (markdown-formatted conversational response)"],"categories":["text-generation-language","planning-reasoning"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"vscode-bini-vscode-gemini-assistant__cap_3","uri":"capability://tool.use.integration.multi.model.selection.with.custom.fallback","name":"multi-model-selection-with-custom-fallback","description":"Provides a dropdown configuration interface in VS Code Settings to select from six pre-configured Google Gemini models (gemini-2.5-pro-exp-03-25, gemma-3-27b-it, gemini-2.0-flash, gemini-2.0-flash-lite, gemini-pro) plus a 'Custom' option that allows users to specify arbitrary model names. The extension routes all API requests through the selected model, enabling developers to trade off cost, latency, and capability without code changes.","intents":["I want to use a faster, cheaper model for simple code questions","I need the most capable model for complex architectural analysis","I want to test a new Gemini model without reinstalling the extension"],"best_for":["cost-conscious developers optimizing API spend","teams experimenting with new Gemini model releases","developers with access to private or fine-tuned Gemini models"],"limitations":["Model selection is global — cannot vary by file type, project, or query complexity","Custom model names are not validated; invalid model names will fail silently at API call time","No fallback mechanism if selected model is unavailable or deprecated","Switching models requires restarting VS Code or manually triggering a settings reload","No cost estimation or quota tracking per model; developers must monitor API usage externally"],"requires":["VS Code Settings UI access","Valid Google Gemini API key with access to selected model","For custom models: knowledge of exact model name and API availability"],"input_types":["configuration (dropdown selection or text input for custom model)"],"output_types":["configuration (model name stored in VS Code settings)"],"categories":["tool-use-integration","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"vscode-bini-vscode-gemini-assistant__cap_4","uri":"capability://tool.use.integration.api.key.based.authentication.with.settings.storage","name":"api-key-based-authentication-with-settings-storage","description":"Implements authentication to Google's Gemini API by storing an API key in VS Code's settings system (via the 'Gemini Assistant: Api Key' configuration field). The extension reads this key on startup and includes it in all API requests to authenticate with Google's servers. The key is stored in VS Code's local settings file, with encryption status unknown.","intents":["I want to authenticate with my Google Gemini API account","I need to rotate my API key without reinstalling the extension","I want to use different API keys for different VS Code workspaces"],"best_for":["individual developers with personal Gemini API accounts","teams using a shared API key across multiple developers"],"limitations":["API key stored in plaintext or with unknown encryption in VS Code settings — potential security risk if settings file is exposed","No built-in key rotation or expiration management — developers must manually update settings when keys are revoked","No per-workspace or per-project key isolation — same key used for all files and projects in VS Code instance","No audit logging of API key usage or access; cannot track which queries consumed quota","Settings file is typically readable by other processes on the same machine, increasing exposure risk"],"requires":["Valid Google Gemini API key from Google Cloud Console","VS Code Settings UI access (Ctrl+, or Cmd+,)","Internet connectivity to validate key with Google's API"],"input_types":["text (API key string)"],"output_types":["configuration (key stored in settings.json)"],"categories":["tool-use-integration","safety-moderation"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"vscode-bini-vscode-gemini-assistant__cap_5","uri":"capability://text.generation.language.markdown.rendered.response.display","name":"markdown-rendered-response-display","description":"Formats all Gemini API responses as markdown and renders them in a dedicated sidebar panel with full markdown support (headers, code blocks, lists, links, etc.). The extension parses the API response text and applies markdown rendering rules, displaying formatted output in the panel UI rather than raw text. Code blocks within responses are syntax-highlighted based on language hints.","intents":["I want to read AI responses with proper formatting and code examples","I need to see code suggestions with syntax highlighting","I want to copy formatted code blocks from AI responses"],"best_for":["developers who prefer formatted output over raw text","teams sharing code suggestions via screenshot or export","developers copying code blocks from AI responses"],"limitations":["Markdown rendering may not support all GitHub Flavored Markdown extensions (tables, strikethrough, etc.)","Very long responses may be truncated or cause performance issues in the sidebar panel","Code block syntax highlighting depends on VS Code's built-in language detection; custom or obscure languages may not highlight correctly","No copy-to-clipboard button for individual code blocks; requires manual selection and copy","Markdown rendering is one-way — cannot edit formatted responses or re-send modified versions"],"requires":["VS Code (minimum version unknown, likely 1.50+ for markdown support)","Gemini API response in text format"],"input_types":["text (markdown-formatted response from Gemini API)"],"output_types":["rendered markdown (displayed in sidebar panel)"],"categories":["text-generation-language","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"vscode-bini-vscode-gemini-assistant__cap_6","uri":"capability://automation.workflow.chat.history.export.to.html","name":"chat-history-export-to-html","description":"Captures the entire conversation history from the sidebar panel and exports it as a static HTML file that can be saved to disk. The export includes all user queries and Gemini responses in chronological order, preserving markdown formatting and code blocks. The exported HTML file is self-contained and can be opened in any web browser for review or sharing.","intents":["I want to save a record of my conversation with the AI for future reference","I need to share code suggestions and explanations with my team","I want to archive conversations for compliance or documentation purposes"],"best_for":["teams documenting code review discussions","developers maintaining knowledge bases of AI-assisted solutions","organizations with audit or compliance requirements"],"limitations":["Exported HTML is static and cannot be re-imported into the extension — conversations cannot be resumed from exports","No option to export partial history (e.g., last 10 messages) — export is all-or-nothing","HTML export does not include metadata (timestamps, model used, API costs) — only conversation text","No built-in version control or diff tracking for exported histories","Exported files are not encrypted; sensitive code or API keys in conversations are exposed in plaintext HTML"],"requires":["Active conversation history in the sidebar panel","File system write access to save HTML file","Web browser to view exported HTML"],"input_types":["conversation history (from sidebar panel)"],"output_types":["file (HTML document)"],"categories":["automation-workflow","memory-knowledge"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"vscode-bini-vscode-gemini-assistant__cap_7","uri":"capability://automation.workflow.sidebar.panel.persistent.ui","name":"sidebar-panel-persistent-ui","description":"Provides a dedicated sidebar panel in VS Code that displays Gemini responses, maintains conversation history, and serves as the primary UI for interacting with the extension. The panel persists across file switches and editor actions, allowing developers to reference previous responses while working on code. The panel includes controls for triggering analysis, composing queries, and exporting history.","intents":["I want a persistent place to see AI responses without opening new windows","I need to reference previous AI suggestions while editing code","I want to keep my conversation history visible while working"],"best_for":["developers who prefer sidebar-based tools over modal dialogs","teams using multiple VS Code extensions that compete for screen space","developers with small monitors or limited screen real estate"],"limitations":["Sidebar panel takes up screen space (typically 300-400px width) that could be used for code editing","Panel content is not synchronized across multiple VS Code windows — each window has its own history","No option to dock panel in different locations (e.g., bottom panel) — fixed to sidebar","Panel state is not persisted across VS Code restarts — history is lost unless manually exported","Very long conversations may cause the panel to become sluggish or unresponsive"],"requires":["VS Code (minimum version unknown, likely 1.50+ for sidebar panel support)","Sufficient screen width to accommodate sidebar without excessive code editor compression"],"input_types":["user interaction (clicks, text input in panel)"],"output_types":["rendered ui (sidebar panel with conversation history and controls)"],"categories":["automation-workflow","text-generation-language"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"vscode-bini-vscode-gemini-assistant__cap_8","uri":"capability://automation.workflow.context.menu.integration.for.code.selection","name":"context-menu-integration-for-code-selection","description":"Integrates with VS Code's right-click context menu to trigger code analysis on selected text without requiring command palette or keyboard shortcuts. When a user right-clicks on selected code, the extension adds menu items that send the selection to Gemini for analysis or questioning. The context menu integration is automatically registered when the extension loads.","intents":["I want to analyze code with a single right-click without typing commands","I need quick access to AI analysis without memorizing keyboard shortcuts","I want to trigger analysis on code I just selected without additional steps"],"best_for":["developers who prefer mouse-based workflows over keyboard shortcuts","teams with mixed technical backgrounds (non-power-users)","developers analyzing code in unfamiliar projects"],"limitations":["Context menu adds visual clutter to the right-click menu, especially if other extensions also add items","Menu items only appear when code is selected — no option to analyze without selection","No keyboard shortcut alternative documented — developers must use right-click or command palette","Context menu items are not customizable or removable without disabling the extension","Right-click menu may be slow to appear if many extensions are installed"],"requires":["VS Code (minimum version unknown, likely 1.50+ for context menu API)","Code selection in active editor (non-empty selection required)"],"input_types":["user interaction (right-click on selected code)"],"output_types":["context menu items (triggering analysis or questioning)"],"categories":["automation-workflow","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"vscode-bini-vscode-gemini-assistant__cap_9","uri":"capability://tool.use.integration.gemini.api.request.routing","name":"gemini-api-request-routing","description":"Handles the low-level mechanics of sending code and queries to Google's Gemini API, including request formatting, authentication header injection, and response parsing. The extension constructs API requests with the selected model, API key, and user input, sends them over HTTPS to Google's endpoints, and parses JSON responses. Error handling for API failures is not documented.","intents":["I want my code analysis to be powered by Google's latest LLM","I need reliable API communication without managing HTTP details","I want to ensure my queries are sent securely to Google's servers"],"best_for":["developers who trust Google's LLM capabilities","teams with existing Google Cloud investments","developers who want to avoid vendor lock-in to OpenAI or Anthropic"],"limitations":["API routing is hardcoded to Google's Gemini endpoints — no option to use alternative providers or self-hosted models","No request batching or caching — each query triggers a separate API call, increasing latency and quota consumption","Error handling for API failures is not documented; developers may not know how to troubleshoot failed requests","No retry logic documented; transient API failures may cause queries to fail without automatic recovery","API rate limits and quota exhaustion behavior are not documented; developers may hit limits unexpectedly"],"requires":["Valid Google Gemini API key","Internet connectivity to reach Google's API endpoints","Selected model must be available in Google's API (not all models may be accessible)"],"input_types":["text (code or query)","configuration (model name, API key)"],"output_types":["text (API response from Gemini)"],"categories":["tool-use-integration","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0}],"trust":{"score":39,"verified":false,"data_access_risk":"high","permissions":["VS Code (minimum version unknown, likely 1.50+)","Google Gemini API key with valid authentication","Internet connectivity to reach Google's API endpoints","Selected code in active editor (non-empty selection)","VS Code (minimum version unknown)","Google Gemini API key with sufficient quota","Active file open in editor with readable content","File size within Gemini API token limits (estimated <100KB for practical use)","Google Gemini API key","Internet connectivity"],"failure_modes":["Analysis limited to selected text only — cannot automatically infer dependencies or imports from other files","No caching of analysis results — each selection triggers a new API call, increasing latency and quota consumption","Context window limited to selected code; cannot reference project-wide patterns or architectural decisions","Markdown rendering in sidebar may truncate very long responses or complex formatting","File size limits imposed by Gemini API token window (typically 1M tokens for gemini-2.0-flash, but practical limit lower for cost/latency)","No multi-file dependency analysis — cannot correlate patterns across imported modules or related files","Analysis does not track file history or git context; cannot suggest improvements based on recent changes","Large files may timeout or incur high API costs depending on model selection","Conversation history is local to the sidebar and not persisted across VS Code sessions unless manually exported to HTML","No automatic context refresh — follow-up questions use the last selected code, not the current selection","builder identity is not verified yet","no observed match outcomes yet"],"rank_breakdown":{"adoption":0.45,"quality":0.3,"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":"2026-05-24T12:16:34.118Z","last_scraped_at":"2026-05-03T15:20:33.198Z","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=gemini-assistant","compare_url":"https://unfragile.ai/compare?artifact=gemini-assistant"}},"signature":"msu0S36pJ/7rIYicg2LTWfSm2fyybXxE8bSsyrdK2ASHLBgqtIjbsXmQbzImoHCRKUhgoOptbg9gaKpVAgiAAg==","signedAt":"2026-06-18T12:55:52.423Z","signedBy":"unfragile.ai","version":1},"_links":{"self":"https://unfragile.ai/api/v1/passport/gemini-assistant","artifact":"https://unfragile.ai/gemini-assistant","verify":"https://unfragile.ai/api/v1/verify?slug=gemini-assistant","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"}}