{"passport":{"unfragile":{"@version":"1.0","version":"2026-05","artifact":{"id":"vscode-hybridtalentcomputing-roo-cline-chinese","slug":"roo-code-chineseroo-cline","name":"Roo Code Chinese（原Roo Cline）","type":"extension","url":"https://marketplace.visualstudio.com/items?itemName=HybridTalentComputing.roo-cline-chinese","page_url":"https://unfragile.ai/roo-code-chineseroo-cline","categories":["code-editors"],"tags":["agent","ai","autonomous","chatgpt","claude","cline","coding","dev","llama","mcp","openrouter","roo code","roocode","sonnet"],"pricing":{"model":"freemium","free":true,"starting_price":null},"status":"active","verified":false},"capabilities":[{"id":"vscode-hybridtalentcomputing-roo-cline-chinese__cap_0","uri":"capability://code.generation.editing.context.aware.code.generation.with.chinese.optimized.prompts","name":"context-aware code generation with chinese-optimized prompts","description":"Generates code completions and implementations by analyzing the current file and project context, then routing requests to configured LLM endpoints (DeepSeek, Claude, or custom APIs) with system prompts translated and optimized for Chinese language models. The extension maintains conversation history within the VS Code editor to enable multi-turn code generation workflows without losing context between requests.","intents":["I want to generate code snippets based on my current file context without leaving VS Code","I need an AI assistant that understands Chinese prompts and generates code optimized for Chinese development workflows","I want to use lightweight Chinese LLMs (like DeepSeek-R1-Distill-Qwen) for faster local or API-based inference","I need to iterate on code generation with multi-turn conversations while keeping project context"],"best_for":["Chinese-speaking developers using VS Code","teams deploying lightweight LLMs (7B-14B parameters) for cost-effective code generation","developers wanting to avoid cloud-only solutions by using local or regional API endpoints"],"limitations":["Context window size depends on configured LLM — no automatic context truncation or summarization documented","API key and endpoint configuration method not documented in marketplace listing, requiring external setup","No built-in support for multi-file context analysis — limited to current file scope unless manually specified","Chinese prompt optimization is claimed but not benchmarked against English prompts or other Chinese-localized tools"],"requires":["Visual Studio Code (minimum version unknown, not specified in documentation)","API key for SiliconFlow, OpenRouter, or compatible LLM provider","Network connectivity to configured LLM endpoint","Supported LLM: DeepSeek-R1-Distill-Qwen-14B (recommended), DeepSeek-R1-Distill-Qwen-7B, Claude-3.5-Sonnet, or compatible API-compatible models"],"input_types":["natural language prompts in Chinese or English","current file content (automatically captured)","project context (scope unknown)"],"output_types":["code snippets","complete function implementations","code explanations in Chinese"],"categories":["code-generation-editing","text-generation-language"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"vscode-hybridtalentcomputing-roo-cline-chinese__cap_1","uri":"capability://text.generation.language.vs.code.sidebar.chat.interface.with.persistent.conversation.history","name":"vs code sidebar chat interface with persistent conversation history","description":"Provides an integrated chat panel in the VS Code sidebar that maintains multi-turn conversation history with the configured LLM. Messages are sent to the LLM endpoint with current file context automatically injected, and responses are rendered in the chat UI with syntax highlighting for code blocks. The conversation state persists within the current VS Code session.","intents":["I want to chat with an AI assistant without switching windows or opening a browser","I need to ask follow-up questions about code without losing the conversation context","I want to see code suggestions inline in my editor with full conversation history visible"],"best_for":["developers who prefer chat-based interaction over inline code completion","teams using VS Code as their primary development environment","developers working with Chinese-language prompts who want native UI support"],"limitations":["Conversation history is session-based only — no persistence to disk or cloud storage documented","Chat UI integration point and layout (sidebar width, resizing, etc.) not documented","No built-in conversation export, save, or sharing functionality mentioned","Unclear whether conversation history is sent to LLM on each request, potentially increasing token usage"],"requires":["Visual Studio Code (minimum version unknown)","Active LLM endpoint connection with valid API key","Network connectivity"],"input_types":["natural language text in Chinese or English"],"output_types":["natural language responses","code blocks with syntax highlighting","formatted text with markdown support"],"categories":["text-generation-language","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"vscode-hybridtalentcomputing-roo-cline-chinese__cap_10","uri":"capability://automation.workflow.upstream.roo.code.project.synchronization.and.maintenance","name":"upstream roo code project synchronization and maintenance","description":"Maintains synchronization with the upstream Roo Code project by merging updates and bug fixes from the original repository. The extension is a localized fork that inherits core functionality from Roo Code while adding Chinese language support and optimizations. Maintenance is performed by individual developer (Leo) with explicit disclaimers about update frequency and project continuity.","intents":["I want to use Roo Code with Chinese language support without waiting for official localization","I need a maintained fork that keeps up with upstream Roo Code improvements","I want to benefit from community improvements to Roo Code while having Chinese UI"],"best_for":["Chinese developers who want Roo Code with native language support","teams unable or unwilling to wait for official Roo Code localization","users comfortable with community-maintained forks and accepting maintenance risks"],"limitations":["Maintenance is not guaranteed — developer explicitly disclaims timely updates or fixes","Project may terminate at any time — no long-term support commitment","Synchronization with upstream Roo Code is manual and may lag behind latest releases","No formal governance or community contribution process documented","Unrelated to official Roo Code team — no official support or endorsement","Single maintainer creates bus factor risk — project continuity depends on one person"],"requires":["Acceptance of maintenance risks and lack of guaranteed support","Understanding that project may change or terminate without notice"],"input_types":["upstream Roo Code updates"],"output_types":["localized Roo Code with Chinese support"],"categories":["automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"vscode-hybridtalentcomputing-roo-cline-chinese__cap_11","uri":"capability://tool.use.integration.extensible.llm.provider.integration.via.api.abstraction","name":"extensible llm provider integration via api abstraction","description":"Abstracts LLM provider differences behind a unified API interface, allowing support for multiple providers (SiliconFlow, OpenRouter, OpenAI-compatible APIs) without duplicating code. The extension implements a provider adapter pattern that translates between the unified internal API and provider-specific request/response formats, enabling easy addition of new providers.","intents":["I want to switch between different LLM providers without changing my workflow","I need to support multiple LLM providers for redundancy or cost optimization","I want to add support for a new LLM provider without modifying core extension code"],"best_for":["developers using multiple LLM providers for cost or performance optimization","teams with provider-specific requirements (regional providers, custom endpoints)","extension maintainers wanting to add new provider support without major refactoring"],"limitations":["Provider abstraction details not documented — unclear what interface providers must implement","No built-in provider auto-detection or fallback logic documented","Adding new providers requires code changes — no plugin system for third-party providers","Provider-specific features (streaming, function calling, etc.) may not be uniformly supported","No provider health checking or automatic failover documented"],"requires":["Understanding of provider API formats (OpenAI-compatible, SiliconFlow, OpenRouter)","Code changes to extension source to add new providers"],"input_types":["provider configuration (endpoint, API key, model name)"],"output_types":["unified LLM inference results"],"categories":["tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"vscode-hybridtalentcomputing-roo-cline-chinese__cap_2","uri":"capability://tool.use.integration.configurable.llm.endpoint.routing.with.multi.provider.support","name":"configurable llm endpoint routing with multi-provider support","description":"Allows users to configure custom LLM API endpoints and select between multiple providers (SiliconFlow, OpenRouter, OpenAI-compatible APIs, or local endpoints). The extension routes all inference requests to the configured endpoint using the selected model, with API key management handled through VS Code settings. Supports both cloud-hosted and self-hosted LLM services via standard API protocols.","intents":["I want to use my own LLM endpoint instead of relying on a single cloud provider","I need to switch between different models (DeepSeek, Claude, Llama) without changing the extension","I want to use a local LLM server or regional API provider for data residency or cost reasons","I need to configure API keys securely without hardcoding them in my project"],"best_for":["enterprises with custom LLM infrastructure or on-premise deployments","developers using regional API providers (SiliconFlow for China, etc.)","teams running local LLM servers (Ollama, vLLM, etc.) for privacy or cost optimization","developers wanting to avoid vendor lock-in by supporting multiple LLM providers"],"limitations":["Configuration method not documented in marketplace listing — unclear if via VS Code settings UI, JSON config, or command palette","API key storage mechanism not specified — unclear if stored in VS Code secrets, plaintext settings, or system keychain","No built-in support for authentication methods beyond API keys (OAuth, mTLS, etc.) documented","Model switching mechanism not documented — unclear if automatic, manual selection, or environment-based","No fallback or retry logic documented for endpoint failures"],"requires":["Visual Studio Code (minimum version unknown)","Valid API endpoint URL for configured LLM provider","API key or authentication credential for the endpoint","Network connectivity to the endpoint","LLM endpoint must support OpenAI-compatible API format or provider-specific format (SiliconFlow, OpenRouter)"],"input_types":["API endpoint URL (string)","API key (string)","model identifier (string)","optional: custom headers or authentication parameters"],"output_types":["LLM inference results routed from configured endpoint"],"categories":["tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"vscode-hybridtalentcomputing-roo-cline-chinese__cap_3","uri":"capability://code.generation.editing.automatic.file.context.injection.for.code.generation","name":"automatic file context injection for code generation","description":"Automatically captures and injects the current file's content, file path, and language information into LLM requests without requiring manual context specification. The extension detects the active editor tab and includes this context in the system prompt or request payload, enabling the LLM to generate code that aligns with the current file's syntax, style, and imports.","intents":["I want code suggestions that match the syntax and style of my current file","I need the AI to understand what language I'm coding in without me telling it","I want to generate code that integrates seamlessly with my existing file without manual context copying"],"best_for":["developers working in multiple languages who want automatic language detection","teams with strict code style guidelines that should be reflected in AI-generated code","developers wanting to minimize manual context specification overhead"],"limitations":["Context scope limited to current file — no cross-file context analysis or project-wide code understanding documented","No automatic detection of project structure, dependencies, or imports — context is file-local only","Large files may exceed LLM context windows, causing truncation or errors (no automatic summarization documented)","No mechanism to exclude sensitive code sections or credentials from context injection"],"requires":["Visual Studio Code with an active editor tab","File must be saved or at least have a language identifier (unsaved files may have limited context)"],"input_types":["current file content (automatic)","file path (automatic)","language identifier (automatic)"],"output_types":["context-aware code suggestions","code completions matching current file syntax"],"categories":["code-generation-editing","memory-knowledge"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"vscode-hybridtalentcomputing-roo-cline-chinese__cap_4","uri":"capability://code.generation.editing.lightweight.llm.optimization.for.chinese.models","name":"lightweight llm optimization for chinese models","description":"Implements prompt engineering and system message optimization specifically for lightweight Chinese LLMs (7B-14B parameters), particularly DeepSeek-R1-Distill series. The extension translates system prompts to Chinese and adjusts instruction formatting to match the training patterns of Chinese-optimized models, enabling better code generation quality from smaller models compared to using English prompts.","intents":["I want to use a small, fast LLM (7B-14B) without sacrificing code generation quality","I need code generation that understands Chinese comments and variable names","I want to reduce inference latency and API costs by using lightweight models instead of large ones"],"best_for":["Chinese-speaking development teams optimizing for inference cost and latency","developers deploying LLMs on resource-constrained hardware (edge devices, laptops)","teams using regional API providers (SiliconFlow) with lightweight model offerings","projects requiring fast iteration cycles where latency is critical"],"limitations":["Optimization is specific to DeepSeek models — effectiveness with other Chinese LLMs (Qwen, Baichuan) not documented","No benchmarks or performance comparisons provided — claimed 'extremely fast' but no latency metrics disclosed","Prompt optimization details not disclosed — unclear what specific Chinese prompt engineering techniques are used","No fallback to English prompts if Chinese model performance is poor","Lightweight models may have reduced code understanding for complex multi-file refactoring tasks"],"requires":["Lightweight LLM endpoint: DeepSeek-R1-Distill-Qwen-14B (recommended) or DeepSeek-R1-Distill-Qwen-7B","API key for provider hosting the model (SiliconFlow recommended)","Network connectivity to LLM endpoint"],"input_types":["code generation prompts in Chinese or English","current file context"],"output_types":["code suggestions optimized for lightweight model inference"],"categories":["code-generation-editing","text-generation-language"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"vscode-hybridtalentcomputing-roo-cline-chinese__cap_5","uri":"capability://tool.use.integration.vs.code.command.palette.integration.for.ai.actions","name":"vs code command palette integration for ai actions","description":"Exposes AI capabilities through VS Code command palette, allowing users to trigger code generation, refactoring, and chat actions via keyboard shortcuts or command search. Commands are registered in the extension's activation context and can be invoked without using the sidebar chat interface, enabling power users to work entirely through keyboard-driven workflows.","intents":["I want to trigger AI code generation with a keyboard shortcut without using the mouse","I need to access AI features through the command palette for faster workflow","I want to bind custom keybindings to specific AI actions"],"best_for":["keyboard-driven developers and power users","teams with custom keybinding configurations","developers using VS Code command palette as primary navigation method"],"limitations":["Specific commands and keybindings not documented in marketplace listing","No documentation of command names, parameters, or return values","Unclear whether commands support arguments (e.g., 'generate function' vs 'generate function with specific signature')","No built-in command discovery or help system mentioned"],"requires":["Visual Studio Code (minimum version unknown)","Knowledge of command names (not documented publicly)"],"input_types":["command name (string)","optional command arguments"],"output_types":["AI action execution (code generation, chat, etc.)"],"categories":["tool-use-integration","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"vscode-hybridtalentcomputing-roo-cline-chinese__cap_6","uri":"capability://memory.knowledge.multi.turn.conversation.state.management.within.editor.session","name":"multi-turn conversation state management within editor session","description":"Maintains conversation history and context across multiple LLM interactions within a single VS Code session, allowing users to ask follow-up questions and reference previous responses without losing context. The extension manages message history, token counting (if applicable), and context window management to ensure coherent multi-turn conversations.","intents":["I want to ask follow-up questions about code without re-explaining the context","I need to iterate on code generation with multiple refinement requests","I want to maintain conversation context across multiple file edits"],"best_for":["developers using iterative code generation workflows","teams requiring multi-step code refactoring or feature implementation","users preferring conversational interaction over single-shot code generation"],"limitations":["Conversation history is session-based only — lost when VS Code closes","No persistence mechanism documented — no export, save, or backup of conversations","Unclear whether full conversation history is sent to LLM on each request (potential token waste) or if summarization is used","No context window management or automatic truncation documented — may fail on very long conversations","No conversation branching or version control for exploring multiple code generation paths"],"requires":["Visual Studio Code session","Active LLM endpoint connection"],"input_types":["natural language prompts","code snippets for refinement"],"output_types":["conversational responses","refined code suggestions"],"categories":["memory-knowledge","text-generation-language"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"vscode-hybridtalentcomputing-roo-cline-chinese__cap_7","uri":"capability://text.generation.language.syntax.aware.code.block.rendering.in.chat.interface","name":"syntax-aware code block rendering in chat interface","description":"Renders code blocks in the chat interface with syntax highlighting based on detected language, making code suggestions readable and visually distinct from natural language responses. The extension parses markdown code blocks from LLM responses and applies VS Code's built-in syntax highlighting engine to provide language-specific formatting.","intents":["I want to see code suggestions with proper syntax highlighting in the chat interface","I need to distinguish code from explanatory text in AI responses","I want to copy code snippets from chat responses without manual formatting"],"best_for":["developers who read code in the chat interface before copying to editor","teams using chat-based code generation workflows","developers working with multiple programming languages"],"limitations":["Syntax highlighting depends on VS Code's language support — unsupported languages may render without highlighting","No built-in code copy button or clipboard integration documented","Unclear whether code blocks are clickable or interactive (e.g., insert into editor with one click)","No code diff visualization for comparing suggested code with existing code"],"requires":["VS Code with syntax highlighting support for target language"],"input_types":["markdown code blocks from LLM responses"],"output_types":["syntax-highlighted code blocks in chat UI"],"categories":["text-generation-language","code-generation-editing"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"vscode-hybridtalentcomputing-roo-cline-chinese__cap_8","uri":"capability://safety.moderation.no.user.data.collection.with.explicit.privacy.disclaimer","name":"no user data collection with explicit privacy disclaimer","description":"Implements a privacy-first architecture that does not collect, store, or transmit user code or conversation data to the extension developer's servers. All LLM requests are routed directly to the configured endpoint (SiliconFlow, OpenRouter, etc.), and the extension itself does not log or persist user interactions. Privacy policy explicitly disclaims data collection and advises users to protect sensitive information.","intents":["I want to use an AI code assistant without my code being sent to the extension developer","I need to ensure my proprietary code stays within my organization's infrastructure","I want transparency about what data is collected and where it goes"],"best_for":["enterprises with strict data residency and privacy requirements","teams handling proprietary or sensitive code","developers concerned about data collection by AI tool vendors","organizations in regulated industries (finance, healthcare, government)"],"limitations":["Privacy guarantee is only for the extension itself — data sent to configured LLM endpoints (SiliconFlow, OpenRouter, etc.) is subject to those providers' privacy policies","No technical isolation or sandboxing documented — relies on user trust and configuration","Users are responsible for protecting sensitive information — no built-in redaction or filtering of credentials, API keys, etc.","No audit trail or verification mechanism to confirm data is not collected","Disclaimer explicitly states 'does not guarantee' protection — liability is disclaimed"],"requires":["Trust in extension developer's privacy claims (no third-party audit documented)","Careful configuration of LLM endpoint to ensure data goes to trusted provider"],"input_types":["user code and prompts (not collected by extension)"],"output_types":["no data collection output"],"categories":["safety-moderation"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"vscode-hybridtalentcomputing-roo-cline-chinese__cap_9","uri":"capability://text.generation.language.chinese.ui.localization.with.translated.system.prompts","name":"chinese ui localization with translated system prompts","description":"Provides complete Chinese-language user interface for the extension, including sidebar labels, chat messages, command names, and settings. System prompts sent to LLMs are translated from English to Chinese, optimized for Chinese language models' training patterns. This enables native Chinese-language interaction without requiring English proficiency from users.","intents":["I want to use an AI code assistant entirely in Chinese without switching to English","I need system prompts optimized for Chinese LLMs rather than translated English prompts","I want a development tool that respects my native language and cultural context"],"best_for":["Chinese-speaking developers and teams","organizations in China, Taiwan, Singapore, and other Chinese-speaking regions","teams using Chinese variable names, comments, and documentation","developers preferring native language interfaces for better usability"],"limitations":["Localization is Chinese-only — no support for other languages (Japanese, Korean, etc.)","Prompt translation quality not benchmarked — unclear if translations are hand-crafted or machine-generated","No option to switch back to English UI if user prefers","Documentation and error messages may still contain English terms or technical jargon","Localization maintenance depends on single maintainer — no guarantee of timely updates for new features"],"requires":["VS Code with Chinese language support","Preference for Chinese-language interface"],"input_types":["user interactions in Chinese"],"output_types":["Chinese-language UI and responses"],"categories":["text-generation-language"],"confidence":0.5,"matches":0,"success_rate":0}],"trust":{"score":41,"verified":false,"data_access_risk":"high","permissions":["Visual Studio Code (minimum version unknown, not specified in documentation)","API key for SiliconFlow, OpenRouter, or compatible LLM provider","Network connectivity to configured LLM endpoint","Supported LLM: DeepSeek-R1-Distill-Qwen-14B (recommended), DeepSeek-R1-Distill-Qwen-7B, Claude-3.5-Sonnet, or compatible API-compatible models","Visual Studio Code (minimum version unknown)","Active LLM endpoint connection with valid API key","Network connectivity","Acceptance of maintenance risks and lack of guaranteed support","Understanding that project may change or terminate without notice","Understanding of provider API formats (OpenAI-compatible, SiliconFlow, OpenRouter)"],"failure_modes":["Context window size depends on configured LLM — no automatic context truncation or summarization documented","API key and endpoint configuration method not documented in marketplace listing, requiring external setup","No built-in support for multi-file context analysis — limited to current file scope unless manually specified","Chinese prompt optimization is claimed but not benchmarked against English prompts or other Chinese-localized tools","Conversation history is session-based only — no persistence to disk or cloud storage documented","Chat UI integration point and layout (sidebar width, resizing, etc.) not documented","No built-in conversation export, save, or sharing functionality mentioned","Unclear whether conversation history is sent to LLM on each request, potentially increasing token usage","Maintenance is not guaranteed — developer explicitly disclaims timely updates or fixes","Project may terminate at any time — no long-term support commitment","builder identity is not verified yet","no observed match outcomes yet"],"rank_breakdown":{"adoption":0.51,"quality":0.34,"ecosystem":0.35000000000000003,"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":"2026-05-24T12:16:34.803Z","last_scraped_at":"2026-05-03T15:20:35.026Z","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-chineseroo-cline","compare_url":"https://unfragile.ai/compare?artifact=roo-code-chineseroo-cline"}},"signature":"p4vL5n4PcQQF+MXGCwPUhox89Kim0c6F3QUn6xg6q4SF1R7pqAebC7Ak3HDtMl7EokMxJXx4WqmIsdhC92EzDw==","signedAt":"2026-06-22T13:09:48.129Z","signedBy":"unfragile.ai","version":1},"_links":{"self":"https://unfragile.ai/api/v1/passport/roo-code-chineseroo-cline","artifact":"https://unfragile.ai/roo-code-chineseroo-cline","verify":"https://unfragile.ai/api/v1/verify?slug=roo-code-chineseroo-cline","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"}}