{"passport":{"unfragile":{"@version":"1.0","version":"2026-05","artifact":{"id":"awesome-roocode","slug":"roocode","name":"RooCode","type":"agent","url":"https://github.com/RooCodeInc/Roo-Code","page_url":"https://unfragile.ai/roocode","categories":["code-editors"],"tags":[],"pricing":{"model":"open_source","free":true,"starting_price":null},"status":"active","verified":false},"capabilities":[{"id":"awesome-roocode__cap_0","uri":"capability://tool.use.integration.multi.provider.ai.model.orchestration.with.streaming.response.handling","name":"multi-provider ai model orchestration with streaming response handling","description":"Roo Code implements a provider-agnostic API handler architecture that abstracts OpenAI, Anthropic, Google, and local model APIs behind a unified interface. The system handles model discovery caching, token usage calculation per provider, and streaming response processing with real-time token counting. The ClineProvider core orchestrator routes requests to the appropriate provider based on user configuration, manages authentication profiles, and normalizes responses across different API schemas.","intents":["Switch between Claude, GPT-4, Gemini, and local models without changing agent logic","Track token usage and costs per provider for billing and optimization","Stream model responses in real-time to the UI without buffering entire outputs","Discover available models and their capabilities dynamically from provider APIs"],"best_for":["Teams evaluating multiple AI providers and wanting to switch without code changes","Developers building cost-aware agents that need per-provider token tracking","Organizations with multi-model strategies (fallback, load-balancing, A/B testing)"],"limitations":["Provider API schema differences require normalization layer that adds ~50-100ms per request","Token counting accuracy varies by provider (some use approximate counts vs exact)","Model discovery caching can become stale if new models are released mid-session","Streaming response handling requires provider-specific chunk parsing logic"],"requires":["API keys for at least one provider (OpenAI, Anthropic, Google, or local Ollama instance)","VS Code 1.80+","Node.js 18+"],"input_types":["text prompts","system messages","message history with tool calls"],"output_types":["streamed text tokens","structured tool calls","token usage metadata"],"categories":["tool-use-integration","ai-provider-abstraction"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-roocode__cap_1","uri":"capability://tool.use.integration.native.tool.calling.with.mcp.integration.and.approval.based.execution","name":"native tool calling with mcp integration and approval-based execution","description":"Roo Code implements a two-tier tool system: native tools (file operations, terminal commands, code execution) registered in a schema-based function registry, plus Model Context Protocol (MCP) tools that extend capabilities through external servers. Tools are executed only after user approval (configurable per tool or auto-approve for trusted operations), with results formatted and returned to the AI model for further reasoning. The tool architecture includes safety guardrails, result formatting, and error handling with retry logic.","intents":["Let the AI agent read/write files, run tests, and execute terminal commands with user oversight","Extend agent capabilities via MCP servers (e.g., database queries, API calls, custom tools)","Approve or reject tool calls before execution to maintain control over agent actions","Auto-approve safe operations (file reads, specific commands) while requiring approval for risky ones"],"best_for":["Developers who want autonomous agents but need approval gates for safety","Teams integrating custom tools via MCP servers","Projects requiring audit trails of all agent actions (file changes, commands run)"],"limitations":["Tool approval UI blocks agent execution until user responds (no async approval queuing)","MCP tool discovery requires manual server configuration; no auto-discovery mechanism","File operation tools are sandboxed to workspace root; cannot access system files outside project","Terminal command execution inherits VS Code's terminal environment; may lack system PATH context"],"requires":["VS Code 1.80+","Node.js 18+","MCP servers must be running separately if using MCP tools"],"input_types":["tool schemas (JSON)","file paths","shell commands","MCP server configurations"],"output_types":["file contents","command output","tool execution results","error messages"],"categories":["tool-use-integration","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-roocode__cap_10","uri":"capability://automation.workflow.settings.ui.and.configuration.management.with.provider.profiles","name":"settings ui and configuration management with provider profiles","description":"Roo Code provides a settings UI for configuring AI providers, models, auto-approval rules, context management, and experimental features. Settings are organized into tabs (providers, models, auto-approve, context, terminal, checkpoints, notifications, experimental). Provider configuration supports multiple profiles (e.g., 'development', 'production') with different API keys and models. Settings are persisted to VS Code's configuration storage and can be synced across devices if VS Code settings sync is enabled.","intents":["Configure API keys and select models for different AI providers","Set up auto-approval rules for safe operations (file reads, specific commands)","Customize context management settings (max tokens, auto-include diagnostics)","Enable/disable experimental features and configure advanced options"],"best_for":["Teams managing multiple AI providers and wanting to switch between them","Developers who want to auto-approve safe operations but require approval for risky ones","Organizations needing to configure Roo Code consistently across team members"],"limitations":["Settings UI is built in React; requires webview rendering which adds latency","Provider profiles are stored in VS Code settings; no encryption for API keys","Auto-approval rules are simple patterns; no complex conditional logic","Settings changes require extension reload to take effect (no hot reload)"],"requires":["VS Code 1.80+","Node.js 18+"],"input_types":["API keys","model names","auto-approval rules","context settings"],"output_types":["configuration JSON","provider profiles","settings metadata"],"categories":["automation-workflow","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-roocode__cap_11","uri":"capability://automation.workflow.cloud.platform.integration.with.task.sharing.and.authentication","name":"cloud platform integration with task sharing and authentication","description":"Roo Code integrates with a cloud platform for task sharing, synchronization, and authentication. Tasks can be shared with team members via cloud links, and task execution can be synchronized across devices. The system supports MDM (Mobile Device Management) integration for enterprise authentication. Cloud service architecture includes task persistence, user authentication, and team collaboration features. Tasks are uploaded to the cloud and can be accessed from any device with the same account.","intents":["Share long-running tasks with team members for collaborative debugging","Sync task execution across multiple devices (laptop, desktop, etc.)","Authenticate with enterprise SSO via MDM integration","Access task history and results from any device"],"best_for":["Teams collaborating on complex tasks and needing to share progress","Enterprises with MDM requirements for authentication","Developers working across multiple devices who want task sync"],"limitations":["Cloud integration requires account creation and login; adds authentication overhead","Task sharing is cloud-dependent; no local-only sharing mechanism","Cloud sync can introduce latency and consistency issues if network is unreliable","MDM integration is enterprise-only; not available for individual users"],"requires":["VS Code 1.80+","Node.js 18+","Cloud account (Roo Code cloud platform)","Internet connection for cloud sync"],"input_types":["task data","user credentials","team information"],"output_types":["cloud task links","sync status","authentication tokens"],"categories":["automation-workflow","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-roocode__cap_12","uri":"capability://text.generation.language.internationalization.i18n.with.documentation.and.ui.localization","name":"internationalization (i18n) with documentation and ui localization","description":"Roo Code implements comprehensive internationalization with localized documentation (README, guides) and UI strings in 10+ languages (Chinese, Japanese, Korean, Spanish, French, German, Portuguese, Turkish, Vietnamese, Polish, Catalan). The i18n system uses a translation file structure and integrates with the webview UI to display localized strings. Documentation is translated and maintained per language, and the UI automatically detects the VS Code language setting to display the appropriate locale.","intents":["Use Roo Code in your native language (Chinese, Japanese, Korean, Spanish, etc.)","Read documentation in your preferred language","Have the UI automatically adapt to your VS Code language setting"],"best_for":["International teams using Roo Code in non-English environments","Organizations deploying Roo Code to non-English-speaking regions","Developers who prefer to work in their native language"],"limitations":["Translation quality depends on translator expertise; some technical terms may be mistranslated","Adding new UI strings requires updating all language files; can be maintenance burden","Documentation translations can become out of sync with English version","Language detection is based on VS Code setting; no per-user language override"],"requires":["VS Code 1.80+","Node.js 18+"],"input_types":["UI strings","documentation files"],"output_types":["localized UI","translated documentation"],"categories":["text-generation-language","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-roocode__cap_13","uri":"capability://automation.workflow.cli.application.for.headless.task.execution.and.automation","name":"cli application for headless task execution and automation","description":"Roo Code includes a CLI application that enables headless task execution without the VS Code UI. The CLI supports task execution modes, configuration via command-line arguments or config files, and output formatting (JSON, text). The CLI can be integrated into CI/CD pipelines, scheduled jobs, or automation scripts. Task execution via CLI follows the same task lifecycle and tool execution as the webview, but without user approval gates (configurable via auto-approve settings).","intents":["Run Roo Code tasks in CI/CD pipelines for automated code generation or testing","Execute tasks on a schedule (e.g., nightly refactoring, dependency updates)","Integrate Roo Code into custom automation scripts","Get structured output (JSON) from task execution for further processing"],"best_for":["Teams integrating Roo Code into CI/CD pipelines","Developers automating code generation or maintenance tasks","Organizations running scheduled tasks (nightly builds, dependency updates)"],"limitations":["CLI has no user approval gates; all operations are auto-approved (requires careful configuration)","CLI output is text or JSON; no interactive UI for debugging","CLI requires local installation; no cloud-based CLI execution","CLI task execution is synchronous; no async task queuing"],"requires":["Node.js 18+","Roo Code CLI installed globally or locally","Configuration file or command-line arguments"],"input_types":["task descriptions","configuration files","command-line arguments"],"output_types":["task execution logs","JSON output","exit codes"],"categories":["automation-workflow","code-generation-editing"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-roocode__cap_14","uri":"capability://data.processing.analysis.evaluation.framework.for.benchmarking.agent.performance","name":"evaluation framework for benchmarking agent performance","description":"Roo Code includes an evaluation framework for benchmarking agent performance on coding tasks. The framework supports running predefined evaluation suites, measuring success rates, execution time, and token usage. Evaluations can be configured to test different models, providers, and configurations. Results are collected and can be analyzed to identify performance regressions or improvements. The evaluation system integrates with the task execution engine and captures detailed metrics.","intents":["Benchmark Roo Code performance on standard coding tasks","Compare different models and providers to identify the best configuration","Detect performance regressions when updating the agent","Measure token usage and costs for different task types"],"best_for":["Teams evaluating Roo Code before deployment","Developers optimizing agent performance","Organizations comparing AI providers and models"],"limitations":["Evaluation suites are predefined; creating custom evaluations requires code changes","Evaluation results are sensitive to model randomness; multiple runs needed for statistical significance","Evaluation framework is local-only; no cloud-based evaluation service","Metrics are limited to success rate, time, and tokens; no qualitative evaluation"],"requires":["Node.js 18+","Roo Code source code (evaluation framework is in the repo)","API keys for providers being evaluated"],"input_types":["evaluation configurations","task definitions","model/provider selections"],"output_types":["evaluation results (JSON)","performance metrics","comparison reports"],"categories":["data-processing-analysis","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-roocode__cap_2","uri":"capability://automation.workflow.task.lifecycle.management.with.checkpoints.and.persistence","name":"task lifecycle management with checkpoints and persistence","description":"Roo Code manages autonomous coding tasks through a task stack system where each task can spawn subtasks, with full lifecycle tracking (creation, execution, completion, error recovery). Tasks are persisted to disk and restored on extension reload, enabling long-running work across sessions. The checkpoint system captures task state at key points, allowing rollback to previous checkpoints if the agent makes mistakes. Task history is maintained in dual storage (in-memory for current session, disk for persistence).","intents":["Run multi-step coding tasks that span hours or days without losing progress","Rollback agent changes to a previous checkpoint if it goes off track","Resume interrupted tasks from where they left off after VS Code restart","Track task execution history and debug what the agent did at each step"],"best_for":["Long-running refactoring or migration tasks that span multiple sessions","Teams needing audit trails of agent actions for compliance","Developers debugging agent behavior by reviewing task history"],"limitations":["Checkpoint rollback requires re-executing from checkpoint; no true state snapshots of file system","Task persistence uses local disk storage; no cloud sync for multi-device workflows","Subtask nesting depth is unlimited but deep nesting can make history UI unwieldy","Checkpoint creation is manual or event-based; no automatic checkpoints at fixed intervals"],"requires":["VS Code 1.80+","Writable workspace directory for task persistence","Node.js 18+"],"input_types":["task descriptions","user instructions","code context"],"output_types":["task execution logs","checkpoint metadata","task history JSON"],"categories":["automation-workflow","planning-reasoning"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-roocode__cap_3","uri":"capability://memory.knowledge.context.window.management.with.mention.based.file.folder.inclusion","name":"context window management with mention-based file/folder inclusion","description":"Roo Code manages LLM context windows through a mention system where users explicitly include files, folders, or environment diagnostics via @-mentions in the chat. The system tracks context usage, calculates remaining tokens, and prevents context overflow by warning users when approaching limits. Context mentions are processed to extract file paths, resolve them relative to workspace, and include file contents or folder structure summaries in the prompt. Environment diagnostics (Node version, installed packages, etc.) can be auto-included based on settings.","intents":["Include specific files in the AI context without sending the entire codebase","Reference folders and have the agent understand their structure without listing every file","Auto-include environment diagnostics (package.json, Node version) for context-aware suggestions","See remaining context tokens and know when you're approaching the model's limit"],"best_for":["Developers working on large codebases who need selective context inclusion","Teams using smaller context windows (Claude 3.5 Sonnet, GPT-4 Turbo) and needing to optimize","Projects where environment context (dependencies, versions) is critical for agent decisions"],"limitations":["Context mentions are manual; no automatic codebase indexing to suggest relevant files","Folder mentions include only structure summary, not full file contents (can miss important code)","Context window calculation is approximate; actual token count may vary by provider","No semantic search to find related files; users must know what to mention"],"requires":["VS Code 1.80+","Node.js 18+"],"input_types":["file paths","folder paths","environment variable names","@-mention syntax"],"output_types":["file contents","folder structure summaries","environment diagnostics","context usage metrics"],"categories":["memory-knowledge","context-management"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-roocode__cap_4","uri":"capability://planning.reasoning.codebase.aware.system.prompt.generation.with.modes.and.custom.instructions","name":"codebase-aware system prompt generation with modes and custom instructions","description":"Roo Code generates dynamic system prompts based on the current codebase, project structure, and user-selected mode (e.g., 'architect', 'test-writer', 'debugger'). The prompt assembly system combines base instructions, mode-specific guidelines, custom rules, and skill descriptions into a coherent system message. The system detects project type (Node.js, Python, web, etc.) and includes relevant tool descriptions and best practices. Custom instructions can be added per project or globally, and slash commands allow mode switching mid-conversation.","intents":["Have the AI understand your project structure and conventions without explaining them each time","Switch agent behavior (architect vs test-writer vs debugger) via slash commands","Add custom rules (e.g., 'always use TypeScript strict mode') that persist across conversations","Auto-detect project type and include relevant tool descriptions and best practices"],"best_for":["Teams with consistent coding standards who want the agent to follow them automatically","Developers switching between different types of tasks (coding, testing, debugging) in one session","Projects with complex conventions that are hard to explain verbally"],"limitations":["System prompt generation is static per mode; no dynamic prompt adaptation based on task progress","Custom instructions are free-form text; no validation that they're actually followed by the model","Mode switching requires slash command; no automatic mode detection based on user intent","Project type detection is heuristic-based (looking for package.json, requirements.txt, etc.); can misidentify hybrid projects"],"requires":["VS Code 1.80+","Node.js 18+"],"input_types":["project files (package.json, tsconfig.json, etc.)","custom instruction text","mode selection"],"output_types":["system prompt string","mode-specific guidelines","tool descriptions"],"categories":["planning-reasoning","text-generation-language"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-roocode__cap_5","uri":"capability://planning.reasoning.ask.say.pattern.for.interactive.agent.user.collaboration","name":"ask/say pattern for interactive agent-user collaboration","description":"Roo Code implements an ask/say pattern where the agent can ask the user for clarification or approval before proceeding, and say messages to provide status updates or explanations. The agent uses special message types to request user input (ask) or provide information (say), which are displayed in the chat UI with appropriate styling. This enables interactive workflows where the agent pauses for user feedback rather than making autonomous decisions. Ask messages can include multiple choice options or free-form input fields.","intents":["Have the agent ask for clarification when the task is ambiguous","Get approval from the user before making major changes","Receive status updates and explanations from the agent during long-running tasks","Provide feedback to the agent mid-task without restarting"],"best_for":["Workflows requiring user oversight and approval at key decision points","Tasks where the agent needs clarification to proceed correctly","Teams wanting collaborative AI where the agent and human work together iteratively"],"limitations":["Ask messages block agent execution until user responds; no timeout mechanism","Multiple choice options are limited to simple text; no rich UI for complex decisions","User responses are free-form text; no structured input validation","Ask/say pattern adds latency to task execution (waiting for user input)"],"requires":["VS Code 1.80+","Node.js 18+"],"input_types":["agent ask messages","user responses (text or selection)"],"output_types":["say messages","ask messages with options","task continuation based on user input"],"categories":["planning-reasoning","text-generation-language"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-roocode__cap_6","uri":"capability://automation.workflow.error.handling.and.retry.logic.with.exponential.backoff","name":"error handling and retry logic with exponential backoff","description":"Roo Code implements comprehensive error handling across API calls, tool execution, and task management with configurable retry logic. Failed API requests are retried with exponential backoff, tool execution errors are caught and formatted for the AI model to reason about, and task errors trigger recovery workflows. The system distinguishes between recoverable errors (rate limits, timeouts) and fatal errors (invalid API keys, permission denied), applying appropriate retry strategies. Error messages are formatted and included in the message history so the AI can learn from failures.","intents":["Automatically retry failed API calls without user intervention","Handle tool execution errors gracefully and let the agent recover","Distinguish between transient failures (retry) and permanent failures (abort)","Debug task failures by reviewing error messages in the task history"],"best_for":["Long-running tasks that may encounter transient network or API errors","Teams needing resilient agents that recover from failures automatically","Developers debugging agent behavior when things go wrong"],"limitations":["Retry logic is fixed (exponential backoff with max retries); no adaptive retry strategies","Rate limit detection is provider-specific; some providers may not be detected correctly","Exponential backoff can cause long delays for frequently failing operations","Error recovery is automatic for API calls but manual for tool execution (requires user approval)"],"requires":["VS Code 1.80+","Node.js 18+"],"input_types":["API requests","tool execution commands","error responses"],"output_types":["retry attempts","error messages","recovery actions"],"categories":["automation-workflow","safety-moderation"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-roocode__cap_7","uri":"capability://text.generation.language.webview.based.chat.ui.with.message.editing.deletion.and.streaming.display","name":"webview-based chat ui with message editing, deletion, and streaming display","description":"Roo Code implements a React-based webview UI that displays chat messages, tool calls, and agent responses in real-time. The UI supports message editing and deletion (with confirmation), streaming token display as they arrive, and rich formatting for code blocks, tool calls, and mermaid diagrams. The webview communicates with the extension host via a message protocol, synchronizing state bidirectionally. Messages are stored in dual storage (in-memory for UI state, disk for persistence), and the UI updates reactively as new messages arrive.","intents":["See agent responses stream in real-time without waiting for full completion","Edit or delete messages to correct mistakes or remove sensitive information","View tool calls and their results in a structured format","Display code blocks, diagrams, and formatted output from the agent"],"best_for":["Developers who want a modern chat interface for AI agents","Teams needing to edit or delete messages for privacy or correction","Projects requiring rich message formatting (code, diagrams, tables)"],"limitations":["Webview rendering adds ~100-200ms latency compared to native UI","Message editing requires re-sending to the AI model; no local-only edits","Streaming display requires provider support for streaming responses","Dual storage (in-memory + disk) can become out of sync if extension crashes"],"requires":["VS Code 1.80+","Node.js 18+","React 18+ (for webview)"],"input_types":["chat messages","tool call results","streaming tokens"],"output_types":["rendered HTML","formatted code blocks","mermaid diagrams","tool call displays"],"categories":["text-generation-language","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-roocode__cap_8","uri":"capability://planning.reasoning.skills.management.system.with.tool.descriptions.and.guidelines","name":"skills management system with tool descriptions and guidelines","description":"Roo Code maintains a skills system where each tool (native or MCP) has a description, usage guidelines, and examples that are included in the system prompt. Skills are organized by category and can be enabled/disabled per project. The system generates tool descriptions dynamically based on the tool's schema and includes them in the system prompt so the AI understands what tools are available and how to use them. Custom skills can be added via configuration, and skill descriptions are versioned with the extension.","intents":["Ensure the agent knows what tools are available and how to use them correctly","Disable tools that shouldn't be used in certain projects (e.g., disable database tools in frontend-only projects)","Add custom tool descriptions to guide the agent's behavior","Version tool descriptions with the extension to ensure consistency"],"best_for":["Teams with custom tools who need to document them for the agent","Projects where certain tools should be disabled for safety or relevance","Organizations wanting to standardize tool usage across teams"],"limitations":["Tool descriptions are static; no dynamic adaptation based on task context","Skill enabling/disabling is per-project; no per-task granularity","Custom skill descriptions are free-form text; no validation that they're accurate","Tool descriptions are included in every system prompt, increasing token usage"],"requires":["VS Code 1.80+","Node.js 18+"],"input_types":["tool schemas","custom descriptions","skill configuration"],"output_types":["tool descriptions","system prompt sections","skill metadata"],"categories":["planning-reasoning","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-roocode__cap_9","uri":"capability://planning.reasoning.slash.command.system.for.mode.switching.and.special.operations","name":"slash command system for mode switching and special operations","description":"Roo Code implements a slash command system where users can trigger special operations via commands like /architect, /test, /debug, etc. Commands are discovered from the system prompt and mode definitions, and executing a command switches the agent's mode or triggers a specific workflow. The command system integrates with the chat input autocomplete, showing available commands as the user types. Commands can have parameters and are validated before execution.","intents":["Switch agent modes (architect, test-writer, debugger) without restarting the conversation","Trigger special workflows (e.g., /refactor, /optimize) with a single command","Discover available commands via autocomplete in the chat input","Pass parameters to commands (e.g., /test --coverage)"],"best_for":["Developers who frequently switch between different types of tasks","Teams with standardized workflows that can be triggered via commands","Projects where mode switching is common (coding, testing, debugging, optimization)"],"limitations":["Commands are discovered from system prompt; adding new commands requires updating the prompt","Command parameters are free-form text; no structured parameter validation","Command execution is synchronous; no async command queuing","Autocomplete for commands requires the system prompt to be parsed; can be slow for large prompts"],"requires":["VS Code 1.80+","Node.js 18+"],"input_types":["slash command text","command parameters"],"output_types":["mode switch","workflow execution","command results"],"categories":["planning-reasoning","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0}],"trust":{"score":31,"verified":false,"data_access_risk":"high","permissions":["API keys for at least one provider (OpenAI, Anthropic, Google, or local Ollama instance)","VS Code 1.80+","Node.js 18+","MCP servers must be running separately if using MCP tools","Cloud account (Roo Code cloud platform)","Internet connection for cloud sync","Roo Code CLI installed globally or locally","Configuration file or command-line arguments","Roo Code source code (evaluation framework is in the repo)","API keys for providers being evaluated"],"failure_modes":["Provider API schema differences require normalization layer that adds ~50-100ms per request","Token counting accuracy varies by provider (some use approximate counts vs exact)","Model discovery caching can become stale if new models are released mid-session","Streaming response handling requires provider-specific chunk parsing logic","Tool approval UI blocks agent execution until user responds (no async approval queuing)","MCP tool discovery requires manual server configuration; no auto-discovery mechanism","File operation tools are sandboxed to workspace root; cannot access system files outside project","Terminal command execution inherits VS Code's terminal environment; may lack system PATH context","Settings UI is built in React; requires webview rendering which adds latency","Provider profiles are stored in VS Code settings; no encryption for API keys","builder identity is not verified yet","no observed match outcomes yet"],"rank_breakdown":{"adoption":0.05,"quality":0.5,"ecosystem":0.39999999999999997,"match_graph":0.25,"freshness":0.52,"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":"2026-06-17T09:51:04.048Z","last_scraped_at":"2026-05-03T14:00:20.516Z","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=roocode","compare_url":"https://unfragile.ai/compare?artifact=roocode"}},"signature":"DG1m6toHmIcvgGrwBFXZJN7dwAGDX9Lng6eMHz4kKJX0v2q1gsKE4JdRLYyipiRH1PBXSoCz20gMn0gfbRMVCA==","signedAt":"2026-06-21T00:40:30.308Z","signedBy":"unfragile.ai","version":1},"_links":{"self":"https://unfragile.ai/api/v1/passport/roocode","artifact":"https://unfragile.ai/roocode","verify":"https://unfragile.ai/api/v1/verify?slug=roocode","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"}}