{"passport":{"unfragile":{"@version":"1.0","version":"2026-05","artifact":{"id":"tool_commander-gpt","slug":"commander-gpt","name":"Commander GPT","type":"product","url":"https://www.commandergpt.app","page_url":"https://unfragile.ai/commander-gpt","categories":["app-builders"],"tags":[],"pricing":{"model":"paid","free":false,"starting_price":null},"status":"active","verified":false},"capabilities":[{"id":"tool_commander-gpt__cap_0","uri":"capability://tool.use.integration.system.wide.hotkey.triggered.ai.chat.access","name":"system-wide hotkey-triggered ai chat access","description":"Implements a global keyboard shortcut (likely registered at OS level via native APIs) that spawns a floating chat window from any application without requiring browser navigation or context switching. The hotkey handler intercepts keystrokes at the system level, maintains a persistent background daemon, and surfaces a lightweight chat interface that overlays the current application. This architecture eliminates the friction of switching to a browser tab or web application.","intents":["I want to ask Claude/GPT a quick question without leaving my IDE or document editor","I need instant AI assistance while working in any desktop application","I want to reduce the time between thinking of a query and getting an AI response"],"best_for":["power users working in multiple desktop applications simultaneously","developers who context-switch frequently between coding, documentation, and communication tools","knowledge workers who need sub-second access to AI without workflow interruption"],"limitations":["Hotkey conflicts with application-specific shortcuts may require manual rebinding","Floating window may obscure content in full-screen applications or games","System-level keyboard hook requires elevated permissions, which some corporate environments restrict","Latency depends on background daemon responsiveness and network conditions"],"requires":["macOS 10.13+ or Windows 10+","Active internet connection for API calls to OpenAI/Anthropic backend","System permissions to register global keyboard hooks","Valid API credentials or subscription token"],"input_types":["text query","selected text from active application","clipboard content"],"output_types":["text response","formatted markdown","code snippets"],"categories":["tool-use-integration","desktop-native"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_commander-gpt__cap_1","uri":"capability://text.generation.language.multi.turn.conversational.chat.with.context.retention","name":"multi-turn conversational chat with context retention","description":"Maintains a conversation history within a session, allowing follow-up questions that reference previous messages without re-stating context. The implementation likely stores conversation state in memory (or local SQLite) and sends the full conversation history with each API request to maintain coherence. The UI renders messages in a scrollable thread format with speaker attribution and timestamps, enabling natural dialogue flow.","intents":["I want to have a back-and-forth conversation with AI, not just one-shot queries","I need the AI to remember what I asked earlier in the conversation","I want to refine or follow up on previous responses without restating the full context"],"best_for":["users engaged in exploratory problem-solving or brainstorming sessions","developers debugging issues through iterative questioning","content creators refining ideas through dialogue"],"limitations":["Context window is limited by the underlying model (GPT-4 has 8K-128K tokens depending on version), so very long conversations may be truncated or summarized","No persistent storage across application restarts unless explicitly saved—conversation history is lost on close","Sending full conversation history with each request increases API costs and latency proportionally to conversation length","No built-in conversation branching or version control for exploring alternative response paths"],"requires":["Active API connection to OpenAI or Anthropic","Sufficient API quota/credits for token consumption","Model context window of at least 4K tokens"],"input_types":["text message","follow-up query","clarification request"],"output_types":["text response","code blocks","formatted markdown"],"categories":["text-generation-language","memory-knowledge"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_commander-gpt__cap_10","uri":"capability://text.generation.language.customizable.system.prompts.and.persona.configuration","name":"customizable system prompts and persona configuration","description":"Allows users to define custom system prompts or 'personas' that modify the AI's behavior and response style for specific use cases. The implementation stores persona definitions (system prompt, model preferences, temperature/top-p settings) in a configuration file or database, provides a UI for creating/editing personas, and applies the selected persona to all subsequent requests. Users can create personas like 'Code Reviewer', 'Technical Writer', 'Brainstorming Partner', etc., each with tailored instructions and parameters.","intents":["I want the AI to act as a code reviewer and provide specific feedback on my code","I need the AI to write in a specific tone or style for my use case","I want to create a reusable configuration for a specific type of task"],"best_for":["power users who use Commander GPT for multiple distinct use cases","teams with specific communication or coding standards who want consistent AI behavior","developers building custom AI workflows on top of Commander GPT"],"limitations":["System prompt engineering requires expertise; poorly designed prompts may produce inconsistent results","No versioning or rollback for persona definitions; changes are permanent","Personas are stored locally; no sharing or collaboration on persona definitions","Model parameters (temperature, top-p) are global; no per-request overrides","No built-in testing or validation framework for persona effectiveness"],"requires":["Local storage for persona definitions (JSON or database)","UI for persona creation and editing","Understanding of prompt engineering best practices"],"input_types":["system prompt text","model selection","temperature/top-p parameters","persona name and description"],"output_types":["persona configuration","modified AI responses based on persona"],"categories":["text-generation-language","planning-reasoning"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_commander-gpt__cap_11","uri":"capability://text.generation.language.streaming.response.rendering.with.real.time.token.display","name":"streaming response rendering with real-time token display","description":"Displays AI responses as they are generated token-by-token, rather than waiting for the complete response. The implementation uses server-sent events (SSE) or WebSocket streaming from the API, renders tokens incrementally to the UI as they arrive, and displays a live token counter showing tokens consumed and estimated cost. This provides immediate feedback and allows users to stop generation early if the response is going in an unwanted direction.","intents":["I want to see the AI response appear in real-time instead of waiting for the full response","I need to stop generation early if the response is going off-track","I want to monitor token consumption and cost in real-time"],"best_for":["users who want immediate feedback and responsiveness","cost-conscious users who want to monitor API spending","developers debugging AI behavior who need to see generation in progress"],"limitations":["Streaming adds complexity to error handling; partial responses may be incomplete if the stream is interrupted","Token counter is an estimate; actual token count may differ from displayed count","Stopping generation mid-stream may result in incomplete or malformed output","Streaming requires API support; not all providers or models support streaming","Real-time rendering may cause UI jank if tokens arrive faster than the UI can render"],"requires":["API support for streaming responses (OpenAI, Anthropic, etc. support this)","WebSocket or SSE connection to API","UI framework capable of incremental rendering"],"input_types":["streaming response from API","token count metadata"],"output_types":["incrementally rendered text","live token counter","stop generation button"],"categories":["text-generation-language","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_commander-gpt__cap_2","uri":"capability://text.generation.language.ai.powered.content.creation.and.generation","name":"ai-powered content creation and generation","description":"Provides templates and prompts for generating written content (emails, blog posts, social media, code comments) by accepting user input and delegating to the underlying LLM with pre-crafted system prompts optimized for each content type. The implementation likely includes a prompt library indexed by content category, parameter injection for tone/length/style, and output formatting specific to each template. Users select a template, fill in variables, and receive generated content ready for editing or publishing.","intents":["I need to write an email but don't know how to phrase it professionally","I want to generate multiple variations of social media copy to test engagement","I need help writing documentation or code comments quickly"],"best_for":["non-technical users who need writing assistance","content creators and marketers generating bulk copy variations","developers documenting code or writing commit messages"],"limitations":["Generated content may require significant editing to match brand voice or specific requirements","Template library is fixed and may not cover niche use cases","No A/B testing framework built-in—users must manually compare variations","Quality depends heavily on template prompt engineering; poorly designed prompts produce generic output","No fact-checking or verification; generated content may contain hallucinations or inaccuracies"],"requires":["API access to text generation model (GPT-4 or Claude)","Template definitions stored locally or fetched from backend","Sufficient API quota for generation requests"],"input_types":["template selection","parameter values (tone, length, audience, topic)","optional seed text or outline"],"output_types":["generated text","multiple variations","formatted markdown or plain text"],"categories":["text-generation-language","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_commander-gpt__cap_3","uri":"capability://text.generation.language.multi.language.translation.with.context.preservation","name":"multi-language translation with context preservation","description":"Accepts text in one language and translates it to a target language using the underlying LLM, with options to preserve formatting, tone, and technical terminology. The implementation sends the source text with a translation-specific system prompt that instructs the model to maintain context, idioms, and style. The UI likely includes language pair selection, tone/formality options, and side-by-side source/target display for verification.","intents":["I need to translate a document or email into another language while preserving tone","I want to translate technical documentation without losing precision","I need quick translation of multiple short texts (chat messages, social posts)"],"best_for":["multilingual teams collaborating across language barriers","content creators localizing content for international audiences","developers translating documentation or error messages"],"limitations":["LLM-based translation may struggle with rare languages, dialects, or highly technical jargon","No glossary or terminology database to enforce consistent translation of domain-specific terms","Context-dependent idioms or cultural references may be mistranslated","No human review workflow—users must manually verify translations for accuracy","Pricing scales with text length; translating large documents may be expensive"],"requires":["API access to multilingual LLM (GPT-4 or Claude supports 100+ languages)","Source and target language codes","Sufficient API quota for translation requests"],"input_types":["plain text","formatted text with markup","code with comments"],"output_types":["translated text","formatted text preserving original structure","side-by-side comparison view"],"categories":["text-generation-language"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_commander-gpt__cap_4","uri":"capability://code.generation.editing.code.generation.and.completion.with.language.support","name":"code generation and completion with language support","description":"Generates code snippets or completes partial code based on natural language descriptions or incomplete code context. The implementation accepts code context (selected code, file content, or language specification) and a natural language request, then delegates to the LLM with a code-generation system prompt. The output is syntax-highlighted and can be inserted directly into the editor or copied to clipboard. Likely supports multiple languages (Python, JavaScript, Go, etc.) with language-specific prompt optimization.","intents":["I need to write a function but don't remember the exact syntax","I want to generate boilerplate code for a common pattern","I need to refactor or optimize existing code"],"best_for":["developers working across multiple programming languages","teams with junior developers who need code generation assistance","rapid prototyping scenarios where speed matters more than optimization"],"limitations":["Generated code may not follow project-specific conventions or style guides","No static analysis or linting—generated code may have bugs or security issues","Limited context awareness; if the full codebase context isn't provided, generated code may duplicate existing utilities","No dependency management; generated code may import libraries not in the project","Quality varies significantly based on prompt clarity and code context provided"],"requires":["API access to code-capable LLM (GPT-4, Claude, or Codex)","Language specification or file extension detection","Optional: project context or style guide as system prompt"],"input_types":["natural language description","partial code with cursor position","selected code for refactoring","language specification"],"output_types":["code snippet","complete function","refactored code","syntax-highlighted text"],"categories":["code-generation-editing"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_commander-gpt__cap_5","uri":"capability://tool.use.integration.api.integration.with.multiple.llm.providers","name":"api integration with multiple llm providers","description":"Abstracts the underlying LLM provider (OpenAI GPT-4, Anthropic Claude, potentially others) behind a unified interface, allowing users to switch providers or models without changing the UI. The implementation likely includes a provider registry, credential management for API keys, and a request/response adapter layer that normalizes different API schemas. Users select their preferred provider and model in settings, and the app routes all requests through the appropriate API endpoint with proper authentication and error handling.","intents":["I want to use Claude instead of GPT-4 for better reasoning","I need to switch providers based on cost or availability","I want to use a local model (Ollama) instead of cloud APIs"],"best_for":["users who want flexibility in model selection based on task requirements","teams evaluating multiple LLM providers for cost/performance tradeoffs","developers building on top of Commander GPT who need provider abstraction"],"limitations":["Different providers have different rate limits, pricing, and capability levels—no automatic optimization","API key management requires secure storage; if keys are stored locally, they're vulnerable to compromise","Provider-specific features (vision, function calling, streaming) may not be fully abstracted, requiring conditional code","Switching providers mid-conversation may produce inconsistent responses due to model differences","No built-in cost tracking or budget management across providers"],"requires":["API keys for at least one supported provider (OpenAI, Anthropic, etc.)","Network connectivity to provider endpoints","Secure credential storage mechanism (OS keychain or encrypted local storage)"],"input_types":["provider selection","model name","API key/credentials"],"output_types":["normalized API response","error handling and fallback logic"],"categories":["tool-use-integration","memory-knowledge"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_commander-gpt__cap_6","uri":"capability://tool.use.integration.floating.window.ui.with.persistent.session.management","name":"floating window ui with persistent session management","description":"Renders a lightweight, always-on-top floating window that persists across application switches and desktop changes. The window maintains its position and size preferences, supports minimize/maximize/close actions, and can be resized or repositioned by the user. The implementation likely uses Electron's BrowserWindow API with custom window chrome, stores window state in local preferences, and restores it on app launch. The floating window design minimizes screen real estate usage while keeping AI assistance immediately accessible.","intents":["I want the AI chat window to stay visible while I work in other applications","I need to resize or reposition the chat window to avoid blocking my content","I want the chat window to remember its position and size between sessions"],"best_for":["users with multi-monitor setups who want AI assistance on one screen while working on another","power users who want persistent AI access without cluttering their workspace","developers who need quick reference while coding"],"limitations":["Floating window may be obscured by full-screen applications or games","Window state persistence is OS-specific; behavior may differ on macOS vs Windows","Always-on-top behavior may interfere with other floating windows or system notifications","Resizing/repositioning the window requires manual adjustment; no smart layout management","Memory overhead of maintaining a persistent window process"],"requires":["Electron framework (or equivalent native window management API)","Local storage for window state preferences","OS support for always-on-top windows (all modern OS support this)"],"input_types":["window position/size adjustments","minimize/maximize/close actions"],"output_types":["persistent window state","UI rendering in floating window"],"categories":["tool-use-integration","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_commander-gpt__cap_7","uri":"capability://tool.use.integration.clipboard.integration.for.quick.text.input.output","name":"clipboard integration for quick text input/output","description":"Automatically detects and offers to process clipboard content (selected text from any application) as input to AI queries, and provides one-click copying of AI responses back to clipboard. The implementation monitors the clipboard for changes or provides a UI button to paste clipboard content, and stores AI responses in clipboard on user action. This enables workflows like 'select text in editor → hotkey → AI processes it → paste response back'.","intents":["I want to quickly ask the AI about text I just selected without typing it out","I need to copy the AI response directly into my document or editor","I want to process multiple pieces of text through the AI without manual copy-paste"],"best_for":["users who work with text-heavy applications (editors, browsers, email clients)","developers who want to quickly refactor or review code snippets","content creators who need rapid iteration on written content"],"limitations":["Clipboard monitoring may have privacy implications; users should understand what data is being accessed","Large clipboard content may exceed API token limits","Clipboard integration is OS-specific; behavior may differ on macOS vs Windows","No clipboard history; only the current clipboard content is accessible","Pasting AI response may overwrite user's current clipboard content, losing previous data"],"requires":["OS clipboard API access (requires system permissions)","Text content in clipboard","Active API connection for processing"],"input_types":["clipboard text content","selected text from active application"],"output_types":["clipboard text (AI response)","formatted text ready for pasting"],"categories":["tool-use-integration","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_commander-gpt__cap_8","uri":"capability://text.generation.language.response.formatting.and.syntax.highlighting","name":"response formatting and syntax highlighting","description":"Automatically detects code blocks, markdown formatting, and structured data in AI responses and renders them with appropriate syntax highlighting, indentation, and visual formatting. The implementation likely uses a markdown parser (e.g., markdown-it) to identify code blocks, detects the language from fence markers or context, and applies syntax highlighting using a library like Highlight.js. Lists, tables, and other markdown elements are rendered with appropriate styling. Users can copy formatted code directly or export responses in multiple formats.","intents":["I want code in the AI response to be syntax-highlighted so I can read it easily","I need to copy code from the response without losing formatting","I want the response to be readable with proper markdown rendering"],"best_for":["developers who receive code in AI responses and need to understand it quickly","users who want professional-looking formatted output for sharing or documentation","teams who need to export AI responses in multiple formats (HTML, PDF, Markdown)"],"limitations":["Syntax highlighting is language-specific; if the language isn't detected correctly, highlighting may be wrong","Complex markdown or nested structures may not render perfectly","No support for custom themes or color schemes beyond built-in defaults","Rendering performance may degrade with very long responses containing many code blocks","Copy-paste of formatted code may include extra whitespace or formatting artifacts"],"requires":["Markdown parser library (e.g., markdown-it)","Syntax highlighting library (e.g., Highlight.js) with language support","CSS for rendering styled output"],"input_types":["raw AI response text","markdown-formatted text","code blocks with language markers"],"output_types":["HTML-rendered response","syntax-highlighted code","formatted markdown","copyable plain text"],"categories":["text-generation-language","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_commander-gpt__cap_9","uri":"capability://memory.knowledge.conversation.history.export.and.management","name":"conversation history export and management","description":"Allows users to save, export, and manage conversation histories in multiple formats (JSON, Markdown, PDF, plain text). The implementation stores conversation metadata (timestamp, model used, tokens consumed) alongside message content, provides a file browser UI for selecting conversations to export, and uses format-specific exporters to generate output. Users can organize conversations by tags or folders, search conversation history, and delete conversations to manage storage.","intents":["I want to save this conversation for future reference or sharing","I need to export a conversation as a document for a report or presentation","I want to search through my past conversations to find a previous solution"],"best_for":["users who use Commander GPT for research or problem-solving and need to archive results","teams who need to share AI-generated content with colleagues","developers who want to document solutions or code snippets from conversations"],"limitations":["Conversation storage is local; no cloud sync or backup unless manually configured","Export formats may lose formatting or interactive elements (e.g., code execution)","No built-in search across conversations; users must manually browse or use OS file search","Storage grows over time; no automatic cleanup or archival of old conversations","Exporting large conversations to PDF may produce very long documents"],"requires":["Local file system access for saving conversations","Export format libraries (e.g., jsPDF for PDF export)","Sufficient disk space for conversation storage"],"input_types":["conversation selection","export format choice","optional metadata (tags, description)"],"output_types":["JSON file with full conversation data","Markdown file with formatted content","PDF document with styling","plain text file"],"categories":["memory-knowledge","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0}],"trust":{"score":43,"verified":false,"data_access_risk":"high","permissions":["macOS 10.13+ or Windows 10+","Active internet connection for API calls to OpenAI/Anthropic backend","System permissions to register global keyboard hooks","Valid API credentials or subscription token","Active API connection to OpenAI or Anthropic","Sufficient API quota/credits for token consumption","Model context window of at least 4K tokens","Local storage for persona definitions (JSON or database)","UI for persona creation and editing","Understanding of prompt engineering best practices"],"failure_modes":["Hotkey conflicts with application-specific shortcuts may require manual rebinding","Floating window may obscure content in full-screen applications or games","System-level keyboard hook requires elevated permissions, which some corporate environments restrict","Latency depends on background daemon responsiveness and network conditions","Context window is limited by the underlying model (GPT-4 has 8K-128K tokens depending on version), so very long conversations may be truncated or summarized","No persistent storage across application restarts unless explicitly saved—conversation history is lost on close","Sending full conversation history with each request increases API costs and latency proportionally to conversation length","No built-in conversation branching or version control for exploring alternative response paths","System prompt engineering requires expertise; poorly designed prompts may produce inconsistent results","No versioning or rollback for persona definitions; changes are permanent","builder identity is not verified yet","no observed match outcomes yet"],"rank_breakdown":{"adoption":0.36666666666666664,"quality":0.78,"ecosystem":0.15000000000000002,"match_graph":0.25,"freshness":0.75,"weights":{"adoption":0.25,"quality":0.25,"ecosystem":0.1,"match_graph":0.35,"freshness":0.05}},"observed_outcomes":{"matches":0,"success_rate":0,"avg_confidence":0,"top_intents":[],"last_matched_at":null},"maintenance":{"status":"active","updated_at":"2026-05-24T12:16:29.717Z","last_scraped_at":"2026-04-05T13:23:42.552Z","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=commander-gpt","compare_url":"https://unfragile.ai/compare?artifact=commander-gpt"}},"signature":"p2WXB1W8Ap5JoS6Kjsnud59pp76yU1w8OOK0rUW5FXhnMvyoqFNBLu+pANwAEcz8b4dMEzq6SkAe9OyNWzcwDA==","signedAt":"2026-06-21T01:12:07.921Z","signedBy":"unfragile.ai","version":1},"_links":{"self":"https://unfragile.ai/api/v1/passport/commander-gpt","artifact":"https://unfragile.ai/commander-gpt","verify":"https://unfragile.ai/api/v1/verify?slug=commander-gpt","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"}}