{"passport":{"unfragile":{"@version":"1.0","version":"2026-05","artifact":{"id":"github-iofficeai--aionui","slug":"iofficeai--aionui","name":"AionUi","type":"agent","url":"https://www.aionui.com","page_url":"https://unfragile.ai/iofficeai--aionui","categories":["ai-agents"],"tags":["acp","ai","ai-agent","chat","chatbot","claude-code","clawd","clawdbot","codex","cowork","gemini","gemini-cli","llm","nano-banana","office","openclaw","opencode","skills","webui"],"pricing":{"model":"open_source","free":true,"starting_price":null},"status":"active","verified":false},"capabilities":[{"id":"github-iofficeai--aionui__cap_0","uri":"capability://tool.use.integration.multi.protocol.agent.orchestration.with.unified.interface","name":"multi-protocol agent orchestration with unified interface","description":"AionUi implements a protocol-agnostic agent abstraction layer that bridges multiple AI agent standards (ACP, Codex, OpenClaw, Gemini CLI) through a common message transformation pipeline. The system uses event-driven communication with a message transformation pipeline that normalizes inputs from heterogeneous agent protocols into a unified conversation data model, then routes outputs back to the appropriate protocol handler. This enables seamless switching between agents without UI changes.","intents":["I want to use Claude Code, Gemini CLI, and OpenClaw agents interchangeably in the same workspace","I need a single interface to orchestrate multiple AI agent protocols without rewriting integrations","I want to switch between different agent backends mid-conversation based on task requirements"],"best_for":["AI researchers evaluating multiple agent protocols","Teams building agent-based automation platforms","Developers migrating between different AI agent ecosystems"],"limitations":["Protocol normalization adds ~50-100ms latency per message transformation","Agent-specific features not present in all protocols may be degraded or unavailable","Requires explicit protocol configuration per agent instance; no automatic protocol detection"],"requires":["Node.js 18+ (Electron runtime)","API keys for target agent protocols (Gemini, Claude, etc.)","TypeScript 5.0+ for extension development"],"input_types":["text prompts","code snippets","file paths","structured agent commands"],"output_types":["agent responses","tool invocations","file write operations","structured conversation logs"],"categories":["tool-use-integration","multi-agent-orchestration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github-iofficeai--aionui__cap_1","uri":"capability://automation.workflow.electron.based.multi.process.agent.execution.with.privilege.separation","name":"electron-based multi-process agent execution with privilege separation","description":"AionUi uses Electron's multi-process architecture to isolate high-privilege system operations (Main process) from the UI renderer and AI orchestration tasks. The Main process handles file system access, native module loading, and system-level tool execution, while the Renderer process manages UI state and the WebUI server handles remote agent communication. Inter-process communication (IPC) uses a request-response pattern with explicit permission gates for sensitive operations.","intents":["I need agents to safely access the file system without exposing the entire system to untrusted code","I want to run AI agents 24/7 without blocking the UI or crashing the entire application","I need to support both desktop and remote (mobile/browser) agent access from a single codebase"],"best_for":["Desktop application developers building agent-based tools","Teams requiring 24/7 agent execution with UI responsiveness","Organizations needing cross-platform (macOS, Windows, Linux) agent deployment"],"limitations":["IPC overhead adds ~10-20ms per cross-process call; high-frequency operations (>100/sec) may bottleneck","Native module rebuilding required for each platform; adds 5-10 minutes to build pipeline","Electron bundle size ~150MB; not suitable for lightweight CLI-only deployments"],"requires":["Electron 25.0+","Node.js 18+ for native module compilation","macOS 10.13+, Windows 7+, or Linux with glibc 2.28+"],"input_types":["file paths","system commands","IPC messages","native module calls"],"output_types":["file system operations","process execution results","system resource metrics","IPC response messages"],"categories":["automation-workflow","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github-iofficeai--aionui__cap_10","uri":"capability://text.generation.language.real.time.message.rendering.with.streaming.response.support","name":"real-time message rendering with streaming response support","description":"AionUi implements a message rendering system that displays agent responses in real-time as they stream from the model, with support for markdown formatting, code syntax highlighting, and interactive UI elements (buttons, forms). The renderer uses a virtual scrolling approach to handle large conversation histories efficiently, with lazy loading of older messages from the database. Streaming responses are buffered and rendered incrementally, with a visual indicator showing when the agent is still generating content.","intents":["I want to see agent responses appear in real-time as they're generated, not wait for the full response","I need code blocks to be syntax-highlighted and copyable without manual formatting","I want to scroll through long conversation histories without the UI becoming sluggish"],"best_for":["Users who value responsive UI and real-time feedback","Developers working with code-generating agents who need syntax highlighting","Teams with long-running conversations that accumulate thousands of messages"],"limitations":["Virtual scrolling adds complexity; jumping to specific messages requires database queries","Streaming response buffering adds ~50-100ms latency before first token appears on screen","Markdown rendering is client-side; complex markdown (tables, nested lists) may render slowly","Code syntax highlighting uses a JavaScript library; languages not in the library render as plaintext"],"requires":["React or similar UI framework for component rendering","Markdown parser (e.g., remark, marked)","Code syntax highlighter (e.g., Prism, highlight.js)"],"input_types":["streaming text responses","markdown content","code blocks with language tags"],"output_types":["rendered HTML","syntax-highlighted code","interactive UI elements"],"categories":["text-generation-language","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github-iofficeai--aionui__cap_11","uri":"capability://automation.workflow.channel.integration.for.multi.platform.conversation.routing","name":"channel integration for multi-platform conversation routing","description":"AionUi implements a channel architecture that routes conversations to different platforms (desktop UI, WebUI, mobile app, CLI) while maintaining unified conversation state. Each channel has a platform-specific message adapter that translates between the unified conversation data model and platform-specific formats. Channels can be enabled/disabled per-conversation, allowing users to choose which platforms can access a conversation.","intents":["I want the same conversation accessible from desktop, mobile, and web without duplication","I need to restrict certain conversations to specific platforms (e.g., keep sensitive conversations on desktop only)","I want platform-specific UI optimizations (mobile uses smaller buttons, desktop uses keyboard shortcuts)"],"best_for":["Teams deploying agents across multiple platforms (desktop, mobile, web, CLI)","Organizations with platform-specific security requirements","Developers building multi-platform agent applications"],"limitations":["Channel routing adds ~20-30ms overhead per message due to adapter translation","Platform-specific features (e.g., voice input on mobile) require separate channel implementations","Channel state synchronization is eventual-consistent; brief inconsistencies may occur across platforms","No built-in conflict resolution for simultaneous edits on different channels"],"requires":["Channel implementations for target platforms","Unified conversation data model in database","Network connectivity between channels"],"input_types":["platform-specific message formats","channel configuration"],"output_types":["unified conversation state","platform-specific message formats"],"categories":["automation-workflow","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github-iofficeai--aionui__cap_12","uri":"capability://tool.use.integration.extension.system.with.manifest.based.lifecycle.and.sandboxed.permissions","name":"extension system with manifest-based lifecycle and sandboxed permissions","description":"AionUi provides an extension system that allows third-party developers to add new agents, tools, and UI components without modifying the core application. Extensions are defined via a manifest file that declares their capabilities, required permissions, and lifecycle hooks. The extension sandbox enforces permission scoping (e.g., an extension can access files only in a specific directory) and provides a stable API for accessing core functionality. Extensions are loaded at startup and can be enabled/disabled per-user.","intents":["I want to extend AionUi with custom agents or tools without forking the codebase","I need to share extensions with team members while ensuring they don't access sensitive data","I want to install extensions from a marketplace without worrying about security"],"best_for":["Developers building custom agents or tools for AionUi","Organizations building internal agent extensions","Teams distributing extensions via a marketplace or package manager"],"limitations":["Manifest-based permissions are coarse-grained; no fine-grained permission control (e.g., read-only file access)","Extension sandbox is process-level; extensions can still access shared memory or environment variables","No built-in extension versioning or dependency management; breaking API changes affect all extensions","Extension loading at startup adds ~100-500ms to application startup time per extension"],"requires":["Extension manifest (JSON)","TypeScript or JavaScript implementation","Node.js 18+ for extension development"],"input_types":["extension manifest","extension code","permission declarations"],"output_types":["loaded extensions","extension API access","permission enforcement"],"categories":["tool-use-integration","safety-moderation"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github-iofficeai--aionui__cap_13","uri":"capability://memory.knowledge.conversation.initialization.with.context.injection.and.memory.priming","name":"conversation initialization with context injection and memory priming","description":"AionUi implements a conversation initialization system that prepares agents for a new conversation by injecting context (workspace files, recent history, user preferences) and priming their memory with relevant information. The system uses a context builder that collects relevant files, previous conversation summaries, and user-defined context, then passes this to the agent as part of the initial system prompt. Context injection is configurable per-conversation, allowing users to control what information agents see.","intents":["I want agents to understand my project context without me having to explain it every time","I need agents to remember relevant information from previous conversations","I want to control what context agents can access for privacy and performance reasons"],"best_for":["Developers working on long-running projects who want agents to maintain context","Teams sharing agents across multiple conversations with different contexts","Organizations with privacy requirements that restrict what context agents can access"],"limitations":["Context collection adds ~500ms-2s overhead to conversation initialization depending on workspace size","Large context (>100KB) may exceed model token limits, requiring automatic summarization","Context staleness: file changes after initialization are not reflected in agent memory","No automatic context relevance filtering; users must manually select relevant context"],"requires":["Workspace files for context collection","Previous conversation history in database","Agent model with sufficient token budget for context"],"input_types":["workspace directory","conversation history","user-defined context"],"output_types":["primed agent memory","injected system prompt","context metadata"],"categories":["memory-knowledge","planning-reasoning"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github-iofficeai--aionui__cap_14","uri":"capability://data.processing.analysis.conversation.data.model.with.message.transformation.pipeline","name":"conversation data model with message transformation pipeline","description":"AionUi uses a unified conversation data model that normalizes messages from heterogeneous agent protocols into a common format, with a message transformation pipeline that handles serialization, deserialization, and protocol-specific metadata preservation. The data model tracks message provenance (which agent/user produced it), tool invocations, and file modifications, enabling rich conversation analysis and replay. The transformation pipeline is extensible, allowing new protocols to be added without modifying the core data model.","intents":["I want to store conversations in a format that's independent of the agent protocol used","I need to analyze conversations to understand agent behavior and decision-making","I want to replay conversations or export them in different formats without data loss"],"best_for":["Researchers analyzing agent behavior and decision-making","Teams building agent-based products that need to support multiple protocols","Organizations with data retention and export requirements"],"limitations":["Message transformation pipeline adds ~50-100ms latency per message due to serialization","Protocol-specific metadata may be lost during normalization if not explicitly preserved","Conversation replay requires re-executing tools; results may differ if external state has changed","Data model schema changes require migration of existing conversations"],"requires":["Database schema for storing unified conversation model","Message transformation implementations for each protocol","TypeScript types for conversation data model"],"input_types":["protocol-specific messages","tool invocations","file modifications"],"output_types":["unified conversation format","conversation metadata","exportable conversation logs"],"categories":["data-processing-analysis","memory-knowledge"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github-iofficeai--aionui__cap_2","uri":"capability://planning.reasoning.built.in.gemini.and.rust.based.aionrs.agent.execution.without.external.cli","name":"built-in gemini and rust-based aionrs agent execution without external cli","description":"AionUi bundles native implementations of the Gemini agent and aionrs (a Rust-based agent runtime) directly into the application, eliminating the need for external CLI tools or separate agent installations. The Gemini agent uses Google's native SDK with full file access and tool scheduling capabilities, while aionrs provides a lightweight, compiled agent runtime. Both are initialized during application startup and managed through a unified agent lifecycle manager that handles model configuration, API key rotation, and tool registry updates.","intents":["I want to run AI agents without installing separate CLI tools or managing external processes","I need agents with native file access and scheduling capabilities built-in, not as plugins","I want zero-configuration agent setup that works immediately after app installation"],"best_for":["Non-technical users who want agents without CLI complexity","Teams deploying agents to machines without package manager access","Developers building agent-based products who want to avoid dependency hell"],"limitations":["Bundled agents increase application size by ~50-80MB per agent runtime","aionrs is Rust-compiled; updates require full application rebuild, not hot-patching","Gemini agent tied to Google's API; no fallback if Google services are unavailable","Limited customization of bundled agent behavior without forking the application"],"requires":["Google API key for Gemini agent","Sufficient disk space for bundled runtimes (~100MB)","Network connectivity for API calls"],"input_types":["text prompts","file paths","tool definitions","configuration objects"],"output_types":["agent responses","file operations","scheduled task results","tool invocation logs"],"categories":["planning-reasoning","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github-iofficeai--aionui__cap_3","uri":"capability://tool.use.integration.model.configuration.and.api.key.management.with.rotation.support","name":"model configuration and api key management with rotation support","description":"AionUi provides a centralized model configuration system that manages API keys, model selection, and provider credentials for multiple AI backends (OpenAI, Anthropic, Google, etc.). The system implements secure API key rotation with automatic fallback to backup keys, encrypted storage in the local database, and per-conversation model override capabilities. Configuration changes are persisted to the database and broadcast to all agent instances via event-driven updates.","intents":["I want to manage API keys for multiple AI providers in one place without hardcoding them","I need to rotate API keys without restarting agents or losing conversation context","I want to use different models for different conversations or tasks without reconfiguring the app"],"best_for":["Teams managing multiple API accounts across different AI providers","Organizations with API key rotation policies for security compliance","Developers building multi-tenant agent platforms"],"limitations":["API key encryption uses local machine key; keys are not portable across devices","No built-in key expiration tracking; relies on provider-side key management","Model override per-conversation adds ~5-10ms lookup overhead per request","No audit trail of which user rotated which key in team mode"],"requires":["API keys from target providers (OpenAI, Anthropic, Google, etc.)","Local database write access for encrypted key storage","Network connectivity to validate keys on configuration"],"input_types":["API key strings","model identifiers","provider configuration objects"],"output_types":["validated configuration","key rotation confirmations","model availability lists"],"categories":["tool-use-integration","safety-moderation"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github-iofficeai--aionui__cap_4","uri":"capability://automation.workflow.cron.based.scheduled.task.execution.for.24.7.agent.automation","name":"cron-based scheduled task execution for 24/7 agent automation","description":"AionUi implements a cron scheduler that allows agents to execute tasks on a recurring schedule without user interaction, enabling true 24/7 automation workflows. The scheduler stores cron expressions in the database, evaluates them at runtime, and triggers agent execution with pre-configured prompts and tool access. Scheduled tasks run in the background without blocking the UI, with execution logs persisted to the database for audit and debugging.","intents":["I want agents to run automated tasks on a schedule (e.g., daily reports, hourly monitoring) without manual triggering","I need to set up 24/7 automation workflows that don't require keeping the app in focus","I want to see execution logs and results of scheduled agent runs for debugging and compliance"],"best_for":["Teams automating repetitive tasks (data collection, report generation, monitoring)","Developers building agent-based SaaS products with scheduled workflows","Organizations requiring 24/7 agent execution for compliance or operational needs"],"limitations":["Cron scheduler only runs while the application is open; no true background execution if app is closed","Cron expression parsing is standard POSIX; no natural language scheduling (e.g., 'every weekday at 9am')","Scheduled task failures are logged but not automatically retried; requires manual intervention or custom error handling","No distributed scheduling; each instance maintains its own cron state, causing duplicate execution in team mode"],"requires":["Application running continuously (Electron app must stay open)","Database write access for storing cron expressions and logs","Agent configuration with valid API keys for scheduled execution"],"input_types":["cron expressions (e.g., '0 9 * * MON-FRI')","agent prompts","tool configurations"],"output_types":["execution logs","task results","error notifications"],"categories":["automation-workflow","planning-reasoning"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github-iofficeai--aionui__cap_5","uri":"capability://tool.use.integration.webui.server.with.websocket.bridging.for.mobile.and.remote.agent.access","name":"webui server with websocket bridging for mobile and remote agent access","description":"AionUi runs an Express-based WebUI server that exposes agent capabilities via HTTP/WebSocket APIs, enabling remote access from mobile apps, browsers, and other clients. The server implements WebSocket bridging that maintains persistent connections to remote clients, synchronizes conversation state in real-time, and proxies tool execution requests back to the local agent runtime. Authentication uses API tokens stored in the database, with per-token permission scoping for multi-user scenarios.","intents":["I want to access my agents from mobile devices or web browsers, not just the desktop app","I need to share agent access with team members without giving them the desktop application","I want real-time synchronization of agent responses across multiple connected clients"],"best_for":["Teams deploying agents as a shared service accessible from multiple devices","Organizations building mobile-first agent interfaces","Developers integrating AionUi agents into existing web applications"],"limitations":["WebSocket connections add ~50-100ms latency vs local IPC; not suitable for sub-100ms response requirements","Authentication tokens stored in database; no built-in token expiration or revocation mechanism","WebUI server runs on localhost by default; exposing to the internet requires manual reverse proxy setup and TLS configuration","No rate limiting on WebSocket connections; susceptible to DoS attacks without external WAF"],"requires":["Express.js 4.18+","WebSocket library (ws or socket.io)","Network connectivity between client and server","API token for authentication"],"input_types":["HTTP requests (JSON payloads)","WebSocket messages","authentication tokens"],"output_types":["HTTP responses (JSON)","WebSocket events","real-time conversation updates"],"categories":["tool-use-integration","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github-iofficeai--aionui__cap_6","uri":"capability://tool.use.integration.mcp.model.context.protocol.tool.system.integration.with.native.bindings","name":"mcp (model context protocol) tool system integration with native bindings","description":"AionUi integrates the Model Context Protocol (MCP) as a standardized tool interface, allowing agents to invoke tools defined via MCP schemas without hardcoding tool logic. The system implements native bindings for common MCP tools (file operations, web search, code execution) and a plugin registry that dynamically loads external MCP tools at runtime. Tool invocations are routed through a unified tool executor that handles error recovery, timeout management, and result serialization.","intents":["I want agents to use standardized MCP tools without custom integration code","I need to add new tools to agents without modifying the application code","I want agents to safely execute tools with resource limits and error handling"],"best_for":["Teams building extensible agent platforms with plugin ecosystems","Developers standardizing on MCP for tool definitions across multiple agents","Organizations requiring tool sandboxing and resource limits"],"limitations":["MCP schema validation adds ~20-30ms overhead per tool invocation","External MCP tools require separate process spawning; adds ~100-200ms latency vs native tools","No built-in tool versioning; breaking schema changes can cause silent failures","Tool timeout management is per-invocation; no global resource quotas across concurrent tool calls"],"requires":["MCP tool definitions (JSON schemas)","Tool implementation (native or external process)","Node.js 18+ for MCP protocol support"],"input_types":["MCP schema definitions","tool invocation requests","tool parameters (typed per schema)"],"output_types":["tool results (JSON)","error messages","execution logs"],"categories":["tool-use-integration","code-generation-editing"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github-iofficeai--aionui__cap_7","uri":"capability://planning.reasoning.assistant.presets.and.skills.with.conversation.scoped.configuration","name":"assistant presets and skills with conversation-scoped configuration","description":"AionUi allows users to create and save assistant presets that bundle model selection, system prompts, tool configurations, and skill definitions into reusable profiles. Presets are stored in the database and can be applied per-conversation, with conversation-scoped overrides that don't affect the preset definition. Skills are modular prompt templates that agents can invoke to perform specific tasks (e.g., 'code-review', 'documentation-generation'), with skill parameters that can be customized per invocation.","intents":["I want to create reusable agent configurations for different tasks (coding, writing, analysis) without reconfiguring each time","I need to share assistant presets with team members so everyone uses the same configuration","I want to customize an agent's behavior for a specific conversation without affecting the preset"],"best_for":["Teams standardizing on agent configurations across projects","Developers building agent-based products with customizable personas","Organizations with templated workflows (code review, documentation, testing)"],"limitations":["Preset versioning is not built-in; changing a preset affects all conversations using it retroactively","Skill parameter validation is schema-based; no runtime type checking for complex parameter types","No preset inheritance or composition; each preset is independent, leading to duplication","Conversation-scoped overrides are not persisted; reloading the conversation loses custom settings"],"requires":["Database write access for storing presets and skills","Valid agent configuration (model, API key) for preset execution"],"input_types":["preset definitions (JSON)","skill templates (prompt text with parameters)","conversation-scoped overrides"],"output_types":["applied preset configuration","skill invocation results","customized agent behavior"],"categories":["planning-reasoning","text-generation-language"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github-iofficeai--aionui__cap_8","uri":"capability://planning.reasoning.team.mode.multi.agent.collaboration.with.shared.conversation.context","name":"team mode multi-agent collaboration with shared conversation context","description":"AionUi implements a team mode that allows multiple agents (or multiple instances of the same agent) to collaborate on a single conversation, with shared context and coordinated tool execution. The system uses a conversation data model that tracks which agent produced each message, implements conflict resolution for concurrent tool writes, and provides a UI for monitoring and controlling agent interactions. Team mode requires explicit permission gates for sensitive operations and audit logging of all agent actions.","intents":["I want multiple agents to work together on a complex task, each contributing their expertise","I need to coordinate agent actions to avoid conflicts (e.g., two agents writing to the same file)","I want to see which agent performed which action for debugging and accountability"],"best_for":["Teams building multi-agent systems for complex problem-solving","Organizations requiring agent action audit trails for compliance","Developers researching agent collaboration and emergent behaviors"],"limitations":["Concurrent tool execution requires distributed locking; adds ~100-200ms overhead per operation","Conflict resolution for file writes is last-write-wins; no merge strategies for complex conflicts","Team mode requires explicit permission gates for each agent; adds UI complexity and decision overhead","No built-in agent communication protocol; agents coordinate only through shared conversation context"],"requires":["Multiple agent instances configured and running","Shared database for conversation context and locking","Network connectivity between agents for coordination"],"input_types":["agent prompts","shared conversation context","tool execution requests"],"output_types":["multi-agent conversation logs","conflict resolution decisions","audit logs"],"categories":["planning-reasoning","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github-iofficeai--aionui__cap_9","uri":"capability://tool.use.integration.file.and.workspace.management.with.agent.safe.access.patterns","name":"file and workspace management with agent-safe access patterns","description":"AionUi provides a file and workspace management system that allows agents to read and write files within designated workspace directories, with access control enforced at the IPC layer. The system implements path normalization to prevent directory traversal attacks, file locking to prevent concurrent writes, and a file change watcher that notifies agents of external modifications. Workspace configuration is stored per-conversation, allowing different conversations to operate on different file sets.","intents":["I want agents to safely read and write files in my project without accessing sensitive system directories","I need to prevent agents from accidentally overwriting files or causing conflicts with external editors","I want to track which files agents have modified for version control and debugging"],"best_for":["Developers using agents for code generation and refactoring","Teams building agent-based development tools with file safety requirements","Organizations with strict file access policies for security"],"limitations":["Path normalization adds ~5-10ms overhead per file operation","File locking is process-local; doesn't prevent concurrent writes from external editors","File change watcher has ~100-500ms latency depending on OS file system events","Workspace configuration per-conversation adds complexity; no global workspace definition"],"requires":["Workspace directory with read/write permissions","File system that supports file locking (POSIX or Windows)","Agent configuration with file access permissions"],"input_types":["file paths (relative to workspace)","file contents","file operation requests (read, write, delete)"],"output_types":["file contents","file operation results","file change notifications"],"categories":["tool-use-integration","safety-moderation"],"confidence":0.5,"matches":0,"success_rate":0}],"trust":{"score":53,"verified":false,"data_access_risk":"high","permissions":["Node.js 18+ (Electron runtime)","API keys for target agent protocols (Gemini, Claude, etc.)","TypeScript 5.0+ for extension development","Electron 25.0+","Node.js 18+ for native module compilation","macOS 10.13+, Windows 7+, or Linux with glibc 2.28+","React or similar UI framework for component rendering","Markdown parser (e.g., remark, marked)","Code syntax highlighter (e.g., Prism, highlight.js)","Channel implementations for target platforms"],"failure_modes":["Protocol normalization adds ~50-100ms latency per message transformation","Agent-specific features not present in all protocols may be degraded or unavailable","Requires explicit protocol configuration per agent instance; no automatic protocol detection","IPC overhead adds ~10-20ms per cross-process call; high-frequency operations (>100/sec) may bottleneck","Native module rebuilding required for each platform; adds 5-10 minutes to build pipeline","Electron bundle size ~150MB; not suitable for lightweight CLI-only deployments","Virtual scrolling adds complexity; jumping to specific messages requires database queries","Streaming response buffering adds ~50-100ms latency before first token appears on screen","Markdown rendering is client-side; complex markdown (tables, nested lists) may render slowly","Code syntax highlighting uses a JavaScript library; languages not in the library render as plaintext","builder identity is not verified yet","no observed match outcomes yet"],"rank_breakdown":{"adoption":0.74512654060907,"quality":0.5,"ecosystem":0.6000000000000001,"match_graph":0.25,"freshness":0.75,"weights":{"adoption":0.25,"quality":0.25,"ecosystem":0.1,"match_graph":0.28,"freshness":0.12}},"observed_outcomes":{"matches":0,"success_rate":0,"avg_confidence":0,"top_intents":[],"last_matched_at":null},"maintenance":{"status":"active","updated_at":"2026-05-24T12:16:21.550Z","last_scraped_at":"2026-05-03T13:57:04.027Z","last_commit":"2026-05-03T11:46:19Z"},"community":{"stars":23521,"forks":2079,"weekly_downloads":null,"model_downloads":null,"model_likes":null}},"distribution":{"claim_url":"https://unfragile.ai/submit?claim=iofficeai--aionui","compare_url":"https://unfragile.ai/compare?artifact=iofficeai--aionui"}},"signature":"ix8SKOtI85db/lxJmE0RJcstD2/wCXenJX/L8r6GIU8QlvJFgFfrKHagUg2bTIWXJtTCj6YtceLBvek1RwFjBQ==","signedAt":"2026-06-19T21:51:27.213Z","signedBy":"unfragile.ai","version":1},"_links":{"self":"https://unfragile.ai/api/v1/passport/iofficeai--aionui","artifact":"https://unfragile.ai/iofficeai--aionui","verify":"https://unfragile.ai/api/v1/verify?slug=iofficeai--aionui","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"}}