{"passport":{"unfragile":{"@version":"1.0","version":"2026-05","artifact":{"id":"github-ai-shifu--chatall","slug":"ai-shifu--chatall","name":"ChatALL","type":"webapp","url":"https://chatall.ai","page_url":"https://unfragile.ai/ai-shifu--chatall","categories":["chatbots-assistants"],"tags":["bingchat","chatbot","chatgpt","desktop-app","electron","electron-app","generative-ai","gpt-4o","hacktoberfest","linux","macos","vuejs3","vuetify3","windows"],"pricing":{"model":"open_source","free":true,"starting_price":null},"status":"active","verified":false},"capabilities":[{"id":"github-ai-shifu--chatall__cap_0","uri":"capability://tool.use.integration.concurrent.multi.bot.prompt.dispatch.with.unified.message.queue","name":"concurrent multi-bot prompt dispatch with unified message queue","description":"Sends a single user prompt to 30+ AI bots simultaneously through a debounced message queue system that batches updates and persists state to IndexedDB. Uses Vuex mutations to coordinate state changes across multiple bot instances, with IPC handlers managing bot-specific connection protocols (API keys, web sessions, proxy settings). The queue.js module implements debounced persistence to prevent excessive database writes while maintaining consistency across the Electron main and renderer processes.","intents":["I want to send one prompt to ChatGPT, Claude, and Bard at the same time and see all responses","I need to compare how different models answer the same question without switching between tabs","I want to batch-test a prompt across multiple AI services to find the best performer"],"best_for":["LLM enthusiasts comparing model outputs","AI researchers benchmarking model behavior","prompt engineers optimizing for multiple backends"],"limitations":["Rate limiting per bot API may cause staggered response times (some bots respond in 2s, others in 10s+)","Web-based bot connections require browser automation which adds 500ms-2s overhead per bot","No built-in request deduplication — identical prompts sent to same bot multiple times will execute separately","Message queue debouncing introduces up to 1s latency before persistence to IndexedDB"],"requires":["Electron runtime (Node.js backend + Chromium renderer)","Valid API keys or web credentials for each bot service","IndexedDB support in Chromium renderer (automatic in Electron)","Network connectivity to each bot's endpoint"],"input_types":["text (user prompt)","structured metadata (bot selection array, conversation context)"],"output_types":["streaming text responses from each bot","structured message objects with bot ID, timestamp, content"],"categories":["tool-use-integration","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github-ai-shifu--chatall__cap_1","uri":"capability://text.generation.language.multi.column.side.by.side.response.comparison.layout","name":"multi-column side-by-side response comparison layout","description":"Renders bot responses in configurable 1, 2, or 3-column layouts using Vue.js components with CSS Grid, enabling visual comparison of identical prompts across different models. The UI layer (App.vue, SettingsModal.vue) manages column count state through Vuex mutations, with responsive design adapting to window resize events. Each column independently streams responses from its assigned bot, with scroll synchronization and message threading support via the message display system.","intents":["I want to see ChatGPT and Claude answers side-by-side for the same question","I need to compare writing styles across 3 different models simultaneously","I want to evaluate which bot gives the most detailed response for my use case"],"best_for":["researchers comparing model outputs qualitatively","content creators choosing between AI assistants","developers debugging prompt behavior across backends"],"limitations":["3-column layout requires minimum 1920px width; below 1024px collapses to single column","Scroll synchronization between columns has ~50ms latency due to Vue reactivity debouncing","No built-in diff highlighting — users must manually compare text differences","Column width is fixed; no resizable column dividers for custom proportions"],"requires":["Vue.js 3 renderer process","CSS Grid support (all modern browsers)","Minimum 2 bots configured and authenticated"],"input_types":["column count selection (1, 2, or 3)","bot assignment to columns","message stream from each bot"],"output_types":["rendered HTML with CSS Grid layout","synchronized scroll position across columns"],"categories":["text-generation-language","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github-ai-shifu--chatall__cap_10","uri":"capability://memory.knowledge.conversation.threading.and.message.organization","name":"conversation threading and message organization","description":"Organizes messages into threaded conversations with support for branching (multiple responses to the same prompt). Each message is linked to a parent message via a thread ID, enabling tree-like conversation structures. The message display system renders threads with visual indentation and parent-child relationships. Users can view the full conversation history or focus on a specific thread. Threading is persisted in IndexedDB with the messages and threads tables.","intents":["I want to explore alternative responses by branching from a previous message","I need to see the full conversation context for a specific response","I want to organize my chat into logical threads for different topics"],"best_for":["researchers exploring multiple response paths","users iterating on prompts with different variations","teams analyzing conversation branching patterns"],"limitations":["Threading UI is complex; visual representation may be confusing for deep trees (>5 levels)","No built-in thread merging — separate threads cannot be combined","Thread navigation requires manual selection; no automatic breadcrumb trails","Persisting thread structure adds ~50ms overhead per message write"],"requires":["IndexedDB for storing thread relationships","Vuex state management for thread navigation"],"input_types":["parent message ID","new message content","thread metadata"],"output_types":["threaded message tree","visual thread representation"],"categories":["memory-knowledge","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github-ai-shifu--chatall__cap_11","uri":"capability://automation.workflow.dark.mode.and.light.mode.theme.switching.with.os.integration","name":"dark mode and light mode theme switching with os integration","description":"Provides dark and light UI themes with automatic detection of system theme preference via native OS APIs. The main process (background.js) queries the system theme using Electron's nativeTheme API and communicates it to the renderer via IPC. Users can override the system preference with manual theme selection, which is persisted in Vuex state. Theme switching is instant and affects all UI components via CSS variables.","intents":["I want dark mode to match my OS preference automatically","I need to switch between dark and light themes without restarting the app","I want the UI to respect my system accessibility settings"],"best_for":["users with accessibility needs (dark mode reduces eye strain)","users with OS theme preferences","teams with diverse accessibility requirements"],"limitations":["Bot responses are rendered as-is; no theme-aware formatting for code blocks","CSS variable switching adds ~10ms latency per theme change","No custom theme support; only dark and light modes available","System theme detection may fail on some Linux distributions"],"requires":["Electron nativeTheme API","CSS variable support in browser"],"input_types":["system theme preference (dark/light)","user theme override (dark/light/auto)"],"output_types":["CSS variables for theme colors","rendered UI with theme applied"],"categories":["automation-workflow","safety-moderation"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github-ai-shifu--chatall__cap_12","uri":"capability://automation.workflow.keyboard.shortcuts.and.hotkey.management","name":"keyboard shortcuts and hotkey management","description":"Provides keyboard shortcuts for common actions (send message, new chat, switch bots, etc.) with customizable hotkey bindings. Shortcuts are defined in configuration and registered with the Electron main process, enabling global hotkeys that work even when the window is not focused. The UI displays shortcut hints next to buttons. Hotkey bindings are persisted in Vuex state and can be customized via settings.","intents":["I want to send a message with Ctrl+Enter instead of clicking the send button","I need global hotkeys to switch between bots without clicking","I want to customize keyboard shortcuts to match my muscle memory"],"best_for":["power users optimizing for keyboard-driven workflows","developers with strong hotkey preferences","accessibility users relying on keyboard navigation"],"limitations":["Global hotkeys may conflict with other applications","Hotkey customization requires application restart to take effect","No hotkey conflict detection — users can accidentally override system shortcuts","Limited to Electron-supported hotkey syntax; some OS-specific shortcuts may not work"],"requires":["Electron globalShortcut API","Hotkey configuration in settings"],"input_types":["hotkey combination (e.g., 'Ctrl+Enter')","action name (e.g., 'send-message')"],"output_types":["hotkey event triggered","action executed"],"categories":["automation-workflow","safety-moderation"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github-ai-shifu--chatall__cap_13","uri":"capability://automation.workflow.application.auto.update.checking.and.version.management","name":"application auto-update checking and version management","description":"Checks for new application versions on startup and periodically in the background, with user-facing notifications for available updates. The update system compares the current version (from package.json) with the latest release on GitHub, displaying a notification if an update is available. Users can manually trigger update checks via settings. Update installation requires manual download and installation; no automatic patching.","intents":["I want to know when a new version of ChatALL is available","I need to check for security updates and bug fixes","I want to stay on the latest version without manual checking"],"best_for":["users wanting to stay current with latest features","teams managing ChatALL deployments","security-conscious users tracking bug fixes"],"limitations":["No automatic updates — users must manually download and install new versions","Update checks require network connectivity to GitHub","No rollback mechanism — downgrading requires manual installation","Update notifications may be missed if users ignore them"],"requires":["Network connectivity to GitHub API","package.json with version field"],"input_types":["current version (from package.json)","GitHub API response with latest release"],"output_types":["update notification","download link to new version"],"categories":["automation-workflow","safety-moderation"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github-ai-shifu--chatall__cap_14","uri":"capability://tool.use.integration.langchain.integration.for.model.agnostic.prompt.execution","name":"langchain integration for model-agnostic prompt execution","description":"Integrates LangChain library to support AI models without native SDKs, using LangChain's unified interface for prompt execution and response parsing. LangChain abstracts provider-specific APIs (OpenAI, Anthropic, Hugging Face, etc.) into a common interface, enabling ChatALL to support models beyond those with dedicated integrations. Bot implementations can use LangChain's LLM classes, chains, and agents for complex prompt workflows. LangChain integration adds ~200-500ms overhead per request due to abstraction layers.","intents":["I want to use open-source models (Llama, Mistral) that don't have native ChatALL support","I need to build complex prompt chains with multiple steps and tool use","I want to leverage LangChain's ecosystem of agents and memory systems"],"best_for":["developers integrating custom or open-source models","teams building complex prompt workflows","researchers experimenting with LangChain features"],"limitations":["LangChain abstraction adds 200-500ms latency per request","Not all LangChain features are exposed in ChatALL UI","LangChain dependency increases bundle size by ~5MB","Some LangChain models require additional API keys or setup"],"requires":["LangChain library (included in dependencies)","Model-specific API key or endpoint (varies by model)","Network connectivity to model endpoint"],"input_types":["prompt text","LangChain model configuration","optional chain or agent definition"],"output_types":["model response text","structured output from chains"],"categories":["tool-use-integration","planning-reasoning"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github-ai-shifu--chatall__cap_15","uri":"capability://tool.use.integration.openai.compatible.api.support.with.custom.endpoint.configuration","name":"openai-compatible api support with custom endpoint configuration","description":"Supports OpenAI-compatible APIs (e.g., local LLMs running on OpenAI-compatible servers, Azure OpenAI) by allowing users to configure custom API endpoints. The OpenAI bot implementation accepts a custom base URL parameter, enabling connection to any OpenAI-compatible server. This enables users to run local models (via llama.cpp, vLLM, etc.) or use alternative providers (Azure, Replicate) without modifying code. API key and endpoint are persisted in bot configuration.","intents":["I want to use a local LLM (Llama 2) running on my machine via OpenAI-compatible API","I need to use Azure OpenAI instead of the public OpenAI API","I want to test against a custom LLM endpoint without modifying ChatALL code"],"best_for":["developers running local LLMs","enterprises using Azure OpenAI","researchers testing custom model endpoints"],"limitations":["Custom endpoints must implement OpenAI API specification exactly; deviations cause failures","No endpoint health checking — invalid endpoints fail silently","No load balancing across multiple endpoints","Custom endpoints may have different rate limits or response formats"],"requires":["OpenAI-compatible API endpoint (URL)","Valid API key for the endpoint","Network connectivity to the endpoint"],"input_types":["custom API endpoint URL","API key","model name"],"output_types":["streaming or non-streaming response from endpoint"],"categories":["tool-use-integration","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github-ai-shifu--chatall__cap_2","uri":"capability://tool.use.integration.bot.abstraction.layer.with.pluggable.provider.integrations","name":"bot abstraction layer with pluggable provider integrations","description":"Defines a Bot base class hierarchy that abstracts heterogeneous AI service APIs (OpenAI, Anthropic, Bing, LangChain, Chinese services) into a unified interface with send(), onMessage(), and onError() methods. Each bot subclass implements provider-specific authentication (API keys, OAuth, web scraping), request formatting, and response parsing. The system uses LangChain integration for models without native SDKs, with fallback to direct HTTP calls for services like Bing Chat. Bot configuration is persisted in Vuex state and IndexedDB, enabling dynamic bot registration without code changes.","intents":["I want to add a new AI bot (e.g., Llama 2) without modifying core application code","I need to support both API-based and web-based bot connections transparently","I want to handle authentication failures and retry logic consistently across all bots"],"best_for":["developers extending ChatALL with custom bot providers","teams integrating proprietary LLM APIs","maintainers adding support for new AI services"],"limitations":["Web-based bot implementations (Bing, web scraping) break when providers change HTML structure or add anti-bot measures","LangChain integration adds 200-500ms overhead per request due to abstraction layers","No built-in rate limiting per bot — relies on provider-side throttling","Authentication state is stored in memory; session expiration requires manual re-login"],"requires":["JavaScript/Node.js runtime","Bot-specific SDK or HTTP client (axios, node-fetch)","Valid credentials (API key, username/password, or OAuth token)","Network access to bot endpoint"],"input_types":["bot configuration object (name, type, credentials)","prompt text","conversation history (optional)"],"output_types":["streaming text response","error objects with retry metadata"],"categories":["tool-use-integration","memory-knowledge"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github-ai-shifu--chatall__cap_3","uri":"capability://memory.knowledge.local.chat.history.persistence.with.indexeddb.and.dexie.orm","name":"local chat history persistence with indexeddb and dexie orm","description":"Persists all chat sessions, messages, and bot responses to IndexedDB using the Dexie ORM library, with tables for chats, messages, and threads. The Vuex store coordinates state changes through mutations that trigger debounced writes to IndexedDB via queue.js, preventing excessive database operations. Chat history is loaded on application startup and kept in-memory for fast access, with lazy-loading of older messages when users scroll. All data is stored locally on the user's machine; no cloud synchronization.","intents":["I want to keep a searchable history of all my prompts and bot responses","I need to resume a conversation with multiple bots from where I left off","I want to export my chat history for analysis or backup"],"best_for":["users prioritizing privacy (no cloud storage)","researchers analyzing bot behavior over time","developers debugging prompt evolution"],"limitations":["IndexedDB storage is limited to ~50MB per origin in most browsers; large chat histories may exceed quota","No built-in encryption — chat data is stored in plaintext in IndexedDB","No cross-device synchronization — history is local to each machine","Dexie ORM adds ~10-20ms overhead per database operation due to abstraction","No built-in data export to standard formats (JSON, CSV); requires manual extraction"],"requires":["Chromium/Electron with IndexedDB support","Dexie.js library (included in dependencies)","Sufficient disk space for chat history"],"input_types":["message objects (user prompt, bot response, metadata)","chat session metadata (timestamp, bot list)"],"output_types":["IndexedDB records","in-memory chat history array","structured message objects on retrieval"],"categories":["memory-knowledge","data-processing-analysis"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github-ai-shifu--chatall__cap_4","uri":"capability://text.generation.language.multi.language.ui.with.i18n.framework.and.10.language.support","name":"multi-language ui with i18n framework and 10 language support","description":"Implements internationalization (i18n) using Vue.js i18n plugin with JSON translation files for 10 languages (English, Chinese, Japanese, Korean, Spanish, French, German, Italian, Russian, Vietnamese). The i18n/index.js module loads locale files dynamically based on system language detection or user preference, with fallback to English. All UI strings, button labels, and error messages are externalized to translation files, enabling language switching without application restart.","intents":["I want to use ChatALL in my native language (Chinese, Japanese, Korean, etc.)","I need to switch languages mid-session without restarting the app","I want to contribute translations for a new language"],"best_for":["international teams using ChatALL","non-English speaking users","open-source contributors adding language support"],"limitations":["Bot responses are not translated — only the UI is localized","Right-to-left (RTL) languages (Arabic, Hebrew) are not supported","Translation files must be manually maintained; no automated translation pipeline","Language switching requires UI re-render, causing ~100ms latency"],"requires":["Vue.js i18n plugin","JSON translation files for target language","Browser locale detection or user preference storage"],"input_types":["locale code (e.g., 'en', 'zh-CN', 'ja')","translation key (e.g., 'button.send')"],"output_types":["localized UI strings","formatted dates/numbers per locale"],"categories":["text-generation-language","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github-ai-shifu--chatall__cap_5","uri":"capability://automation.workflow.cross.platform.desktop.application.with.electron.and.native.os.integration","name":"cross-platform desktop application with electron and native os integration","description":"Packages ChatALL as a native desktop application using Electron, combining a Node.js main process with a Chromium renderer running Vue.js. The main process (background.js) handles window management, IPC communication, system theme detection, proxy configuration, and cookie access via native APIs. The renderer process (App.vue) runs the Vue.js UI and communicates with the main process via IPC for privileged operations. Supports Windows, macOS, and Linux with platform-specific installers.","intents":["I want to run ChatALL as a native desktop app without opening a browser tab","I need to use system proxy settings and cookies from my browser","I want dark mode that respects my OS theme preference"],"best_for":["users preferring native desktop applications","teams with strict browser security policies","developers needing offline-capable AI chat tool"],"limitations":["Electron bundle size is ~150MB, making installation slower than web apps","IPC communication between main and renderer processes adds ~5-10ms latency per call","Cookie access requires explicit user permission and may fail on some OS configurations","Proxy settings are read-only; changes require application restart","No automatic updates; users must manually download new versions"],"requires":["Windows 7+, macOS 10.13+, or Linux (Ubuntu 18.04+)","~200MB free disk space","Electron runtime (bundled in installer)"],"input_types":["system theme preference","proxy configuration","browser cookies"],"output_types":["native window with Chromium renderer","system tray integration (optional)"],"categories":["automation-workflow","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github-ai-shifu--chatall__cap_6","uri":"capability://memory.knowledge.prompt.management.with.save.reuse.and.organization","name":"prompt management with save, reuse, and organization","description":"Allows users to save frequently-used prompts to a local prompt library, with tagging and search capabilities. Saved prompts are persisted in Vuex state and IndexedDB, enabling quick insertion into the chat input. The SettingsModal.vue component provides UI for managing prompt collections. Prompts can be organized by category tags and searched by keyword, reducing repetitive typing for common queries.","intents":["I want to save my best prompts and reuse them across multiple conversations","I need to organize prompts by category (e.g., 'writing', 'coding', 'analysis')","I want to search my prompt library to find a previously-saved query"],"best_for":["prompt engineers optimizing queries","content creators with template prompts","researchers running standardized tests across models"],"limitations":["No prompt versioning — overwriting a prompt loses the previous version","No collaborative prompt sharing — prompts are local to each user","Search is basic keyword matching; no semantic search or similarity ranking","No prompt analytics — no tracking of which prompts are most effective"],"requires":["IndexedDB for local storage","Vuex state management"],"input_types":["prompt text","category tags","search keywords"],"output_types":["saved prompt objects","search results array"],"categories":["memory-knowledge","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github-ai-shifu--chatall__cap_7","uri":"capability://safety.moderation.bot.authentication.and.credential.management.with.secure.storage","name":"bot authentication and credential management with secure storage","description":"Manages authentication credentials for 30+ AI services (API keys, OAuth tokens, usernames/passwords) with secure storage in IndexedDB and in-memory caching. The bot system handles provider-specific auth flows: API key validation for OpenAI/Anthropic, OAuth for some services, and web session management for browser-based bots. Credentials are validated on bot initialization and cached in memory to avoid repeated authentication. Failed authentication triggers error handling with user-facing prompts to re-enter credentials.","intents":["I want to securely store my ChatGPT API key without typing it every time","I need to authenticate with multiple AI services using different credential types","I want to know if my bot credentials are expired or invalid"],"best_for":["users managing multiple AI service subscriptions","developers testing against multiple API keys","teams sharing ChatALL instances with different credentials"],"limitations":["Credentials are stored in plaintext in IndexedDB — no encryption at rest","No credential rotation or expiration tracking","OAuth tokens are cached in memory; session loss requires re-authentication","Web-based bot authentication (Bing, Bard) relies on browser cookies, which may expire unexpectedly","No audit log of credential access or usage"],"requires":["Valid API key or account credentials for each bot service","IndexedDB for persistent storage","Network connectivity to bot endpoints for validation"],"input_types":["API key (string)","OAuth token (string)","username/password (tuple)","browser cookies (from system)"],"output_types":["authentication status (valid/invalid/expired)","error messages with remediation steps"],"categories":["safety-moderation","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github-ai-shifu--chatall__cap_8","uri":"capability://tool.use.integration.proxy.configuration.and.network.request.routing","name":"proxy configuration and network request routing","description":"Allows users to configure HTTP/HTTPS proxy settings for all bot API requests, with support for proxy authentication (username/password). Proxy configuration is persisted in IndexedDB and loaded on application startup. The main process (background.js) provides IPC handlers to read and save proxy settings, which are then applied to all HTTP clients (axios, node-fetch) used by bot implementations. Supports both system proxy detection and manual proxy configuration.","intents":["I need to route all bot requests through a corporate proxy","I want to use a VPN or proxy to access geo-restricted AI services","I need to debug network requests by routing them through a proxy analyzer"],"best_for":["enterprise users behind corporate firewalls","users in regions with geo-restrictions on AI services","developers debugging network issues"],"limitations":["Proxy settings are read-only in the UI; changes require application restart","No proxy authentication caching — credentials are re-entered on each session","Web-based bot connections (Bing, Bard) may not respect proxy settings due to browser automation limitations","No proxy failover or load balancing across multiple proxies"],"requires":["Valid proxy server address (hostname:port)","Proxy authentication credentials (if required)","Network connectivity to proxy server"],"input_types":["proxy URL (string)","proxy username (string, optional)","proxy password (string, optional)"],"output_types":["proxy configuration object","validation status (connected/failed)"],"categories":["tool-use-integration","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github-ai-shifu--chatall__cap_9","uri":"capability://text.generation.language.streaming.response.rendering.with.real.time.message.updates","name":"streaming response rendering with real-time message updates","description":"Renders bot responses in real-time as they stream from the API, using Vue.js reactive data binding to update the UI incrementally. Each bot's response is streamed to a message object in Vuex state, with the UI component re-rendering on each chunk received. The message display system handles markdown rendering, code syntax highlighting, and text formatting. Streaming is non-blocking; the UI remains responsive while responses are being received.","intents":["I want to see bot responses appear in real-time instead of waiting for the full response","I need to read and react to partial responses while the bot is still generating","I want to stop a response mid-stream if it's going in the wrong direction"],"best_for":["users impatient for full responses","researchers analyzing response generation patterns","developers debugging prompt behavior in real-time"],"limitations":["Streaming requires API support (not all bot APIs support streaming)","Vue.js reactivity adds ~20-50ms latency per chunk due to virtual DOM reconciliation","No built-in response cancellation — stopping a stream requires closing the connection","Markdown rendering is done client-side, adding ~100ms overhead for large responses"],"requires":["Bot API with streaming support (Server-Sent Events or chunked HTTP)","Vue.js 3 for reactive updates"],"input_types":["streaming text chunks from bot API","message metadata (bot ID, timestamp)"],"output_types":["rendered HTML with markdown and syntax highlighting","real-time UI updates"],"categories":["text-generation-language","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0}],"trust":{"score":40,"verified":false,"data_access_risk":"high","permissions":["Electron runtime (Node.js backend + Chromium renderer)","Valid API keys or web credentials for each bot service","IndexedDB support in Chromium renderer (automatic in Electron)","Network connectivity to each bot's endpoint","Vue.js 3 renderer process","CSS Grid support (all modern browsers)","Minimum 2 bots configured and authenticated","IndexedDB for storing thread relationships","Vuex state management for thread navigation","Electron nativeTheme API"],"failure_modes":["Rate limiting per bot API may cause staggered response times (some bots respond in 2s, others in 10s+)","Web-based bot connections require browser automation which adds 500ms-2s overhead per bot","No built-in request deduplication — identical prompts sent to same bot multiple times will execute separately","Message queue debouncing introduces up to 1s latency before persistence to IndexedDB","3-column layout requires minimum 1920px width; below 1024px collapses to single column","Scroll synchronization between columns has ~50ms latency due to Vue reactivity debouncing","No built-in diff highlighting — users must manually compare text differences","Column width is fixed; no resizable column dividers for custom proportions","Threading UI is complex; visual representation may be confusing for deep trees (>5 levels)","No built-in thread merging — separate threads cannot be combined","builder identity is not verified yet","no observed match outcomes yet"],"rank_breakdown":{"adoption":0.3736309232449235,"quality":0.5,"ecosystem":0.6000000000000001,"match_graph":0.25,"freshness":0.6,"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":"2026-05-24T12:16:21.549Z","last_scraped_at":"2026-05-03T13:58:21.998Z","last_commit":"2026-02-11T18:21:27Z"},"community":{"stars":16368,"forks":1725,"weekly_downloads":null,"model_downloads":null,"model_likes":null}},"distribution":{"claim_url":"https://unfragile.ai/submit?claim=ai-shifu--chatall","compare_url":"https://unfragile.ai/compare?artifact=ai-shifu--chatall"}},"signature":"YpvsdNuzyAzv7g6n9As+I/atBI00oGNIYW8oK2LwfYLWW8w70Q/yDQOZ2Vxo11pRGUYUayrNDSgiSfXvoQ/DDw==","signedAt":"2026-06-20T20:19:27.108Z","signedBy":"unfragile.ai","version":1},"_links":{"self":"https://unfragile.ai/api/v1/passport/ai-shifu--chatall","artifact":"https://unfragile.ai/ai-shifu--chatall","verify":"https://unfragile.ai/api/v1/verify?slug=ai-shifu--chatall","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"}}