{"passport":{"unfragile":{"@version":"1.0","version":"2026-05","artifact":{"id":"roo-code","slug":"roo-code","name":"Roo Code","type":"extension","url":"https://marketplace.visualstudio.com/items?itemName=RooVeterinaryInc.roo-cline","page_url":"https://unfragile.ai/roo-code","categories":["code-editors"],"tags":[],"pricing":{"model":"free","free":true,"starting_price":null},"status":"active","verified":false},"capabilities":[{"id":"roo-code__cap_0","uri":"capability://planning.reasoning.mode.based.agentic.code.generation.with.task.specialization","name":"mode-based agentic code generation with task specialization","description":"Roo Code implements a multi-mode architecture where users select specialized AI personas (Code Mode, Architect Mode, Ask Mode, Debug Mode, or custom modes) that pre-configure the LLM's system prompt, context window strategy, and output formatting for specific development tasks. Each mode adjusts how the AI interprets natural language requests and structures responses—Code Mode prioritizes file edits and inline refactoring, Architect Mode focuses on system design and migration planning, Debug Mode emphasizes root cause analysis and logging strategies. The extension routes user input through the selected mode's configuration before sending to the underlying AI provider (OpenAI, Anthropic, Vertex AI), enabling task-specific behavior without requiring users to manually craft detailed prompts.","intents":["I want the AI to focus on quick code edits without over-explaining architecture","I need help planning a system migration and want architectural-level thinking","I want fast answers about my codebase without generating code","I'm debugging an issue and need the AI to suggest logging and tracing strategies","I want to create a custom mode for my team's specific coding standards"],"best_for":["development teams with diverse coding tasks (refactoring, architecture, debugging)","solo developers who want context-aware AI assistance without prompt engineering","teams standardizing on specific AI models or coding patterns via custom modes"],"limitations":["Custom mode creation requires manual configuration—no visual mode builder UI documented","Mode switching requires manual selection in UI; no automatic task detection","Context window limits per mode not documented—unclear if modes adjust context strategy","No mode versioning or rollback—custom modes may break with extension updates"],"requires":["VS Code 1.80+ (minimum version not explicitly stated, inferred from modern extension APIs)","API key for at least one supported provider (OpenAI, Anthropic, or Vertex AI)","Active internet connection for cloud-based AI providers"],"input_types":["natural language instructions","code snippets","file paths and project context"],"output_types":["code edits and file modifications","architectural diagrams or specifications (text-based)","explanations and documentation","debugging suggestions and logging code"],"categories":["planning-reasoning","code-generation-editing"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"roo-code__cap_1","uri":"capability://memory.knowledge.codebase.aware.context.indexing.and.retrieval","name":"codebase-aware context indexing and retrieval","description":"Roo Code maintains an indexed representation of the user's codebase that enables the AI to answer questions about project structure, suggest refactorings across multiple files, and understand dependencies without requiring the user to manually paste code snippets. The extension scans the workspace on startup and during file changes, building an index of file paths, function signatures, and import relationships. When the user asks a question or requests a change, the extension retrieves relevant code context from this index and includes it in the prompt sent to the AI, enabling multi-file awareness and project-level understanding. The indexing strategy and scope (e.g., which file types are indexed, maximum project size) are not documented.","intents":["I want to ask the AI about my codebase structure without manually selecting files","I need the AI to refactor code across multiple files while understanding dependencies","I want to find where a function is used across my project","I need the AI to suggest architectural improvements based on the full codebase"],"best_for":["developers working on medium-to-large codebases (< 100K files, estimated)","teams needing multi-file refactoring with dependency awareness","developers who want codebase Q&A without manual file selection"],"limitations":["Indexing scope and file type filtering not documented—unclear which files are indexed","Maximum project size for indexing not specified—may degrade on very large monorepos","Index refresh strategy unclear—may lag behind rapid file changes","No explicit control over what gets indexed—users cannot exclude directories or file types","Indexing performance impact on VS Code startup time not documented"],"requires":["VS Code workspace with accessible file system","Sufficient disk space for index storage (size not specified)","File system permissions to read project files"],"input_types":["natural language questions about codebase","file paths and function names","refactoring requests"],"output_types":["code suggestions with cross-file awareness","codebase structure summaries","dependency graphs (text-based)","multi-file refactoring plans"],"categories":["memory-knowledge","code-generation-editing"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"roo-code__cap_10","uri":"capability://code.generation.editing.file.operation.automation.with.ai.driven.refactoring.across.projects","name":"file operation automation with ai-driven refactoring across projects","description":"Roo Code enables the AI to perform file operations (create, delete, rename, move) as part of refactoring workflows, allowing large-scale code reorganization without manual file management. When the user requests a refactoring that requires file changes (e.g., extracting a module into a separate file, reorganizing directory structure), the AI can generate file operations that are applied through VS Code's file system API. The extension handles file creation, deletion, and movement while updating imports and references across the codebase to maintain consistency. File operations are grouped into checkpoints, allowing users to review and undo changes if needed.","intents":["I want to extract a module into a separate file and have the AI update all imports","I need to reorganize my project structure and want the AI to move files and fix references","I want the AI to create boilerplate files (e.g., tests, components) as part of code generation","I need to delete unused files and have the AI verify no references remain"],"best_for":["developers performing large refactorings that span multiple files","teams reorganizing project structure","developers generating boilerplate code and project scaffolding","teams automating repetitive file operations"],"limitations":["File operation safety not documented—no dry-run or preview before applying changes","Import resolution may fail for complex module systems (e.g., dynamic imports, monorepos)","No support for version control integration—file operations are not automatically committed","Circular dependency detection not documented—AI may create invalid import structures","File operation rollback limited to checkpoint undo—no git integration for recovery","Performance impact of large file operations not measured"],"requires":["VS Code 1.80+ (estimated minimum)","Writable workspace with file system access","Active AI provider connection"],"input_types":["refactoring requests","file operation specifications","code snippets"],"output_types":["file create/delete/move operations","updated imports and references","refactored code"],"categories":["code-generation-editing","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"roo-code__cap_11","uri":"capability://automation.workflow.terminal.command.execution.with.ai.driven.shell.scripting","name":"terminal command execution with ai-driven shell scripting","description":"Roo Code enables the AI to generate and execute shell commands in the VS Code integrated terminal, allowing automation of build processes, testing, deployment, and other command-line workflows. When the user requests an operation that requires running commands (e.g., 'run the test suite', 'build the Docker image'), the AI can generate appropriate shell commands and execute them through the terminal. The extension captures terminal output and includes it in the conversation, allowing the AI to interpret results and suggest next steps based on command success or failure. Command execution is logged in the checkpoint history, enabling users to review and replay commands.","intents":["I want the AI to run tests and analyze failures","I need the AI to execute build commands and report results","I want the AI to generate and run deployment scripts","I need the AI to execute git commands as part of a workflow"],"best_for":["developers automating build and test workflows","teams deploying code through AI-assisted CI/CD","developers who want AI to interpret command output and suggest fixes","teams standardizing on command-line workflows"],"limitations":["Command execution safety not documented—no confirmation or dry-run before execution","Terminal output parsing may fail for complex or colored output","No support for interactive commands (e.g., password prompts, user input)","Command timeout behavior not specified—long-running commands may hang","No built-in protection against destructive commands (e.g., rm -rf)","Cross-platform compatibility not documented—commands may fail on different OS"],"requires":["VS Code 1.80+ (estimated minimum)","VS Code integrated terminal access","Appropriate shell environment (bash, zsh, PowerShell, etc.)","Necessary tools installed (e.g., npm, docker, git)"],"input_types":["natural language requests","command specifications","workflow descriptions"],"output_types":["shell commands","terminal output","command results and analysis"],"categories":["automation-workflow","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"roo-code__cap_12","uri":"capability://automation.workflow.community.fork.maintenance.with.feature.parity.to.original.cline","name":"community fork maintenance with feature parity to original cline","description":"Roo Code is a community-maintained fork of the original Cline extension, created after the original team transitioned to a commercial product (Roomote). The fork maintains feature parity with Cline while adding enhancements (custom modes, improved context management, multi-provider support). The extension is open-source and hosted on GitHub, with community contributions and issue tracking. The fork is actively maintained with regular updates and bug fixes, ensuring compatibility with current VS Code versions and AI provider APIs. The community fork provides an alternative to the original Cline for users who prefer open-source development and community governance.","intents":["I want to use Cline-like functionality but prefer open-source and community-maintained software","I need an AI coding assistant that isn't tied to a commercial product","I want to contribute to the development of an AI coding assistant","I need to fork or modify the extension for my team's specific needs"],"best_for":["developers who prefer open-source software","teams with custom requirements who want to fork and modify the extension","communities building on top of Cline's architecture","organizations avoiding vendor lock-in with commercial AI tools"],"limitations":["Community maintenance may be slower than commercial support","Feature parity with original Cline not guaranteed—fork may lag behind","No official support or SLA—issues resolved on best-effort basis","Potential for community fragmentation if fork diverges significantly from Cline","Dependency on community contributors—may face maintenance gaps if contributors leave"],"requires":["VS Code 1.80+ (estimated minimum)","GitHub account for contributing (optional)","Willingness to use community-maintained software"],"input_types":["GitHub issues and pull requests","community contributions","feature requests"],"output_types":["bug fixes and patches","new features and enhancements","documentation and guides"],"categories":["automation-workflow","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"roo-code__cap_2","uri":"capability://tool.use.integration.multi.provider.ai.model.abstraction.with.provider.specific.function.calling","name":"multi-provider ai model abstraction with provider-specific function calling","description":"Roo Code abstracts away provider-specific API differences through a unified interface that supports OpenAI (GPT-4, GPT-4.5), Anthropic (Claude Opus 4.7), and Vertex AI (Google Cloud). The extension handles provider-specific details like function calling schemas, token counting, and API authentication, allowing users to switch providers or use multiple providers in parallel without changing their workflow. Each provider has native bindings for tool use and function calling, enabling the AI to invoke VS Code operations (file edits, terminal commands, etc.) through provider-native APIs rather than custom wrappers. The extension manages API key storage, provider selection UI, and fallback logic if a provider is unavailable.","intents":["I want to use Claude for architecture planning and GPT-4 for code generation in the same session","I need to switch AI providers without reconfiguring my workflow","I want the AI to call VS Code functions (edit files, run commands) using the provider's native function-calling API","I need to use Vertex AI because my organization has a Google Cloud contract"],"best_for":["teams evaluating multiple AI providers for cost or capability reasons","developers who want provider flexibility without vendor lock-in","organizations with existing cloud contracts (e.g., Google Cloud, OpenAI)","developers building custom modes that require specific model capabilities"],"limitations":["Provider selection UI and API key management not documented—unclear how users switch providers","Model parameter tuning (temperature, max tokens) not documented—may use provider defaults","Fallback behavior if a provider is unavailable not specified","Token counting and rate limiting per provider not documented","No built-in cost tracking or usage analytics across providers","Function calling schemas may differ between providers—compatibility not guaranteed"],"requires":["API key for at least one supported provider (OpenAI, Anthropic, or Vertex AI)","Network access to provider APIs","VS Code 1.80+ (estimated minimum)"],"input_types":["provider API keys","model selection preferences","function calling schemas"],"output_types":["unified AI responses","provider-native function calls","code edits and file operations"],"categories":["tool-use-integration","code-generation-editing"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"roo-code__cap_3","uri":"capability://code.generation.editing.in.place.code.editing.with.checkpoint.based.undo.and.multi.file.transactions","name":"in-place code editing with checkpoint-based undo and multi-file transactions","description":"Roo Code enables the AI to edit code directly in the editor through a transaction-based system where multiple file edits are grouped into atomic checkpoints. When the user requests a refactoring or code generation, the AI generates edits that are applied to the workspace, and the user can review changes before committing. The extension maintains a checkpoint history, allowing users to revert to previous states if an edit introduces bugs or doesn't match expectations. Edits are applied using VS Code's TextEdit API, ensuring compatibility with the editor's undo/redo system and enabling users to manually adjust AI-generated code before saving.","intents":["I want the AI to refactor my code and see the changes in the editor before committing","I need to undo an AI-generated edit and try a different approach","I want the AI to make coordinated changes across multiple files as a single transaction","I need to manually tweak AI-generated code before saving"],"best_for":["developers who want AI-assisted refactoring with human review","teams with strict code review processes requiring checkpoint visibility","developers working on large refactorings that span multiple files"],"limitations":["Checkpoint history not persisted across sessions—checkpoints are lost on extension reload","Maximum number of checkpoints not specified—may cause memory issues on long editing sessions","Conflict resolution for simultaneous edits not documented—unclear behavior if user edits while AI is generating","No explicit conflict detection with other extensions or manual edits","Transaction atomicity not guaranteed if VS Code crashes during multi-file edit"],"requires":["VS Code 1.80+ (estimated minimum)","Writable workspace with file system access","Active AI provider connection"],"input_types":["natural language refactoring requests","code snippets","file paths"],"output_types":["in-place code edits","checkpoint markers","diff previews"],"categories":["code-generation-editing","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"roo-code__cap_4","uri":"capability://tool.use.integration.mcp.server.integration.for.extended.tool.capabilities","name":"mcp server integration for extended tool capabilities","description":"Roo Code supports Model Context Protocol (MCP) servers, enabling integration with external tools and services beyond VS Code's built-in APIs. Users can configure MCP servers (e.g., for database access, API testing, or custom business logic) and the AI can invoke these tools through the MCP protocol. The extension handles MCP server lifecycle management (startup, shutdown, error handling) and translates MCP tool definitions into function calls that the underlying AI provider can invoke. This allows teams to extend Roo Code's capabilities with custom tools without modifying the extension itself.","intents":["I want the AI to query my database to understand schema before generating queries","I need the AI to call my internal APIs to fetch business logic or configuration","I want to extend Roo Code with custom tools specific to my team's workflow","I need the AI to interact with external services (e.g., GitHub, Jira) to gather context"],"best_for":["teams with custom internal tools or APIs","developers needing database schema awareness for code generation","organizations building domain-specific AI workflows","teams using MCP-compatible services (e.g., Anthropic's MCP ecosystem)"],"limitations":["MCP server configuration and lifecycle management not documented—unclear how to set up servers","Error handling and timeout behavior for MCP calls not specified","No built-in MCP server library—users must implement or find compatible servers","Security implications of exposing internal tools to AI not documented","MCP server performance impact on extension responsiveness not measured","Compatibility with all MCP server implementations not guaranteed"],"requires":["MCP server implementation (external, user-provided or third-party)","Network access to MCP server","MCP server configuration in Roo Code settings (format not documented)"],"input_types":["MCP server definitions","tool schemas","natural language requests"],"output_types":["MCP tool invocations","tool results integrated into AI responses","code generated with external context"],"categories":["tool-use-integration","memory-knowledge"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"roo-code__cap_5","uri":"capability://planning.reasoning.debug.mode.root.cause.analysis.with.logging.suggestion.engine","name":"debug-mode root cause analysis with logging suggestion engine","description":"Roo Code's Debug Mode specializes in helping developers trace and fix bugs by analyzing error messages, stack traces, and code context to identify root causes and suggest targeted logging or instrumentation. When activated, Debug Mode configures the AI to ask clarifying questions about the bug (reproduction steps, error messages, affected code), then generates logging statements or debugging code that can be inserted into the codebase to gather more information. The mode integrates with VS Code's debugging UI, allowing users to set breakpoints and inspect state while the AI suggests next steps based on the observed behavior.","intents":["I have an error and want the AI to help me trace the root cause","I need the AI to suggest logging statements to debug a flaky test","I want the AI to analyze a stack trace and identify the problematic code","I need help understanding why a specific code path is being executed"],"best_for":["developers debugging complex issues in unfamiliar codebases","teams with limited debugging expertise","developers working on production issues with limited reproduction steps","teams standardizing on logging practices via custom Debug Mode configurations"],"limitations":["Logging suggestion quality depends on error message clarity—vague errors may produce generic suggestions","No automatic breakpoint placement—users must manually set breakpoints","Integration with VS Code debugger not documented—unclear how debug state is shared with AI","No support for remote debugging or multi-process debugging scenarios","Suggested logging may not be optimal for performance-critical code"],"requires":["VS Code 1.80+ (estimated minimum)","Error message or stack trace","Access to relevant source code"],"input_types":["error messages","stack traces","code snippets","reproduction steps"],"output_types":["root cause analysis","logging code suggestions","debugging strategies","instrumentation recommendations"],"categories":["planning-reasoning","code-generation-editing"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"roo-code__cap_6","uri":"capability://planning.reasoning.architect.mode.system.design.and.migration.planning","name":"architect-mode system design and migration planning","description":"Roo Code's Architect Mode configures the AI to think at the system level, focusing on architectural decisions, design patterns, and large-scale refactoring strategies rather than individual code edits. When activated, Architect Mode prompts the AI to ask about project constraints (performance requirements, team size, deployment environment), existing architecture, and migration goals before suggesting changes. The mode generates architectural specifications, migration plans, and design documents in addition to code, enabling teams to plan large changes collaboratively before implementation. Architect Mode integrates with the codebase indexing to understand the current system structure and suggest changes that align with existing patterns.","intents":["I need to plan a migration from monolith to microservices and want architectural guidance","I want the AI to review my system design and suggest improvements","I need to document the architecture of my codebase for onboarding new team members","I want to plan a major refactoring and need a step-by-step migration strategy"],"best_for":["architects and senior developers planning large system changes","teams migrating between architectural patterns","organizations documenting system design for compliance or knowledge sharing","teams evaluating technology choices (e.g., database, framework, deployment platform)"],"limitations":["Architectural suggestions are based on AI training data—may not account for organization-specific constraints","No formal validation of suggested architectures—users must review for feasibility","Migration plans are high-level—implementation details require manual planning","No integration with architecture decision records (ADRs) or formal documentation tools","Suggestions may not account for legacy system constraints or technical debt"],"requires":["VS Code 1.80+ (estimated minimum)","Codebase context (via indexing)","Clear project goals and constraints"],"input_types":["project goals and constraints","current architecture description","performance and scalability requirements","team size and expertise"],"output_types":["architectural specifications","migration plans","design documents","pattern recommendations","technology evaluations"],"categories":["planning-reasoning","text-generation-language"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"roo-code__cap_7","uri":"capability://text.generation.language.ask.mode.fast.codebase.q.a.and.documentation.generation","name":"ask-mode fast codebase q&a and documentation generation","description":"Roo Code's Ask Mode optimizes for quick answers and explanations by configuring the AI to provide concise, focused responses without generating code. When activated, Ask Mode enables users to ask questions about their codebase (e.g., 'How does the authentication flow work?', 'What does this function do?'), and the AI retrieves relevant code context from the codebase index to provide accurate answers. Ask Mode also supports documentation generation, allowing users to request README updates, API documentation, or inline code comments that the AI generates based on the codebase structure and existing documentation patterns.","intents":["I want to understand how a specific feature works in my codebase","I need to generate documentation for a new API endpoint","I want the AI to explain a complex algorithm or design pattern in my code","I need to update README or API docs to reflect recent changes"],"best_for":["developers onboarding to new codebases","teams maintaining documentation alongside code","developers who want quick answers without code generation","teams with documentation requirements (e.g., API documentation, architecture guides)"],"limitations":["Documentation quality depends on existing code comments and structure—sparse code may produce incomplete docs","No integration with documentation tools (e.g., Swagger, Sphinx)—generated docs are plain text","No automatic documentation validation or consistency checking","Explanations may be verbose or miss important context if codebase is poorly structured","No support for multi-language documentation generation"],"requires":["VS Code 1.80+ (estimated minimum)","Codebase context (via indexing)","Clear questions or documentation requests"],"input_types":["natural language questions","code snippets","documentation requests"],"output_types":["explanations and summaries","documentation (README, API docs, comments)","code walkthroughs"],"categories":["text-generation-language","memory-knowledge"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"roo-code__cap_8","uri":"capability://planning.reasoning.custom.mode.creation.and.team.workflow.standardization","name":"custom mode creation and team workflow standardization","description":"Roo Code allows users to create custom modes that encode team-specific coding standards, architectural patterns, and workflow preferences as reusable AI personas. Custom modes are defined through configuration (format not documented) that specifies the AI's system prompt, context window strategy, output formatting, and tool availability. Once created, custom modes can be shared across the team, enabling consistent AI behavior across developers and projects. Custom modes enable teams to standardize on specific coding patterns (e.g., 'always use async/await instead of callbacks'), architectural decisions (e.g., 'prefer composition over inheritance'), or domain-specific practices (e.g., 'follow HIPAA compliance guidelines for healthcare code').","intents":["I want to create a custom mode that enforces my team's coding standards","I need the AI to follow our architectural patterns without manual prompting","I want to share a specialized mode with my team for consistent AI behavior","I need the AI to be aware of domain-specific requirements (e.g., compliance, performance)"],"best_for":["teams with strong coding standards or architectural patterns","organizations with domain-specific requirements (e.g., healthcare, finance)","teams standardizing on specific AI models or providers","teams building internal AI workflows for code generation"],"limitations":["Custom mode creation requires manual configuration—no visual mode builder UI","Mode configuration format not documented—unclear syntax and options","No mode versioning or rollback—custom modes may break with extension updates","No mode testing or validation framework—users must manually verify mode behavior","Mode sharing mechanism not documented—unclear how to distribute modes across team","No built-in mode templates or examples—users must create modes from scratch"],"requires":["VS Code 1.80+ (estimated minimum)","Understanding of Roo Code's mode configuration format (not documented)","Team agreement on coding standards or architectural patterns"],"input_types":["mode configuration (format unknown)","system prompt specifications","tool definitions"],"output_types":["custom AI personas","standardized code generation","team-specific workflows"],"categories":["planning-reasoning","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"roo-code__cap_9","uri":"capability://text.generation.language.vs.code.sidebar.chat.interface.with.context.aware.conversation.history","name":"vs code sidebar chat interface with context-aware conversation history","description":"Roo Code integrates a chat interface into the VS Code sidebar that maintains conversation history and context awareness across multiple turns. The chat interface allows users to interact with the AI through natural language, with the extension automatically including relevant file context (current file, selected code, project structure) in each message. The conversation history is maintained within the session, enabling the AI to reference previous messages and maintain context across multiple requests. The chat interface includes UI controls for checkpoint navigation, mode selection, and provider configuration, providing a unified entry point for all Roo Code features.","intents":["I want to chat with the AI about my code without switching windows","I need the AI to remember previous messages in our conversation","I want to include my current file context in the AI request automatically","I need to switch modes or providers without leaving the chat interface"],"best_for":["developers who prefer chat-based interaction over command palette or context menus","teams using Roo Code as a primary development assistant","developers who want persistent conversation history within a session"],"limitations":["Conversation history not persisted across sessions—history is lost on extension reload","Context inclusion strategy not documented—unclear which files/code are automatically included","No explicit context management UI—users cannot manually adjust included context","Chat interface performance not documented—may lag on large conversations","No search or filtering of conversation history","No export or sharing of conversations"],"requires":["VS Code 1.80+ (estimated minimum)","Active AI provider connection"],"input_types":["natural language messages","code snippets (via selection)","file context (automatic)"],"output_types":["AI responses","code suggestions","explanations","file edits"],"categories":["text-generation-language","code-generation-editing"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"roo-code__headline","uri":"capability://code.generation.editing.ai.assisted.code.editor.extension","name":"ai-assisted code editor extension","description":"Roo Code is a community-driven extension for Visual Studio Code that enhances coding workflows with AI-assisted features like code generation, debugging, and context management, tailored for various coding tasks.","intents":["best AI code editor extension","AI code editor for debugging","AI-assisted coding tools for VS Code","top extensions for agentic coding","code generation tools for developers"],"best_for":[],"limitations":[],"requires":[],"input_types":[],"output_types":[],"categories":["code-generation-editing"],"confidence":0.5,"matches":0,"success_rate":0}],"trust":{"score":59,"verified":false,"data_access_risk":"high","permissions":["VS Code 1.80+ (minimum version not explicitly stated, inferred from modern extension APIs)","API key for at least one supported provider (OpenAI, Anthropic, or Vertex AI)","Active internet connection for cloud-based AI providers","VS Code workspace with accessible file system","Sufficient disk space for index storage (size not specified)","File system permissions to read project files","VS Code 1.80+ (estimated minimum)","Writable workspace with file system access","Active AI provider connection","VS Code integrated terminal access"],"failure_modes":["Custom mode creation requires manual configuration—no visual mode builder UI documented","Mode switching requires manual selection in UI; no automatic task detection","Context window limits per mode not documented—unclear if modes adjust context strategy","No mode versioning or rollback—custom modes may break with extension updates","Indexing scope and file type filtering not documented—unclear which files are indexed","Maximum project size for indexing not specified—may degrade on very large monorepos","Index refresh strategy unclear—may lag behind rapid file changes","No explicit control over what gets indexed—users cannot exclude directories or file types","Indexing performance impact on VS Code startup time not documented","File operation safety not documented—no dry-run or preview before applying changes","builder identity is not verified yet","no observed match outcomes yet"],"rank_breakdown":{"adoption":0.7,"quality":0.9,"ecosystem":0.3,"match_graph":0.25,"freshness":0.75,"weights":{"adoption":0.25,"quality":0.25,"ecosystem":0.15,"match_graph":0.23,"freshness":0.12}},"observed_outcomes":{"matches":0,"success_rate":0,"avg_confidence":0,"top_intents":[],"last_matched_at":null},"maintenance":{"status":"active","updated_at":"2026-05-24T12:16:25.061Z","last_scraped_at":null,"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=roo-code","compare_url":"https://unfragile.ai/compare?artifact=roo-code"}},"signature":"Etua2c8Lwar8dL+oAmIvC02U5PthSgqqABCHqtSJwppgtXOTajMQfDFrDEUqCpwb1tkwRINd5sdzeL+sArkcBQ==","signedAt":"2026-06-19T22:52:05.629Z","signedBy":"unfragile.ai","version":1},"_links":{"self":"https://unfragile.ai/api/v1/passport/roo-code","artifact":"https://unfragile.ai/roo-code","verify":"https://unfragile.ai/api/v1/verify?slug=roo-code","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"}}