{"passport":{"unfragile":{"@version":"1.0","version":"2026-05","artifact":{"id":"vscode-tencent-cloud-coding-copilot","slug":"tencent-cloud-codebuddy","name":"Tencent Cloud CodeBuddy","type":"extension","url":"https://marketplace.visualstudio.com/items?itemName=Tencent-Cloud.coding-copilot","page_url":"https://unfragile.ai/tencent-cloud-codebuddy","categories":["code-editors"],"tags":["Code Assistant","CodeBuddy","Codebuddy Code Assistant","keybindings","tencent","Tencent AI Code Assistant","tencent cloud","Tencent Cloud  AI Code Assistant","Tencent Cloud  Code Assistant","Tencent Cloud AI Code Assistant","Tencent Cloud Codebuddy","Tencent Cloud CodeBuddy代码助手","Tencent Code Assistant","Tencent Codebuddy","Tencent CodeBuddy 代码助手","代码助手","代码助手CodeBuddy","腾讯CodeBuddy","腾讯云AI代码助手","腾讯云AI代码助手Codebuddy","腾讯云CodeBuddy","腾讯云代码助手 CodeBuddy","腾讯代码助手CodeBuddy"],"pricing":{"model":"freemium","free":true,"starting_price":null},"status":"active","verified":false},"capabilities":[{"id":"vscode-tencent-cloud-coding-copilot__cap_0","uri":"capability://code.generation.editing.multi.file.autonomous.code.generation.with.instruction.comprehension","name":"multi-file autonomous code generation with instruction comprehension","description":"The Craft Agent capability enables autonomous generation and rewriting of code across multiple files based on natural language instructions. It uses Tencent Hunyuan or configurable third-party models (DeepSeek, GLM) to deeply comprehend instruction semantics and generate executable applications spanning multiple source files. The agent maintains cross-file consistency by understanding project structure context and generates code that is immediately compilable without manual intervention.","intents":["I need to scaffold a new feature across multiple files without writing boilerplate","I want to refactor code across an entire module based on architectural guidelines","I need to generate a complete, runnable application from a high-level specification","I want to apply consistent code transformations across multiple files simultaneously"],"best_for":["teams building microservices or modular architectures","developers prototyping multi-file features quickly","engineering teams standardizing code patterns across codebases"],"limitations":["Multi-file context understanding depends on project structure visibility — scope of accessible files not documented","No documented token limit per generation request, may fail on very large multi-file operations","Consistency across generated files relies on model capability, not explicit constraint enforcement","Cannot guarantee generated code passes compilation without human review"],"requires":["VS Code extension installed (version requirement unknown)","Active internet connection for cloud-based inference","Tencent Cloud account or free tier access via copilot.tencent.com","Project files accessible within VS Code workspace"],"input_types":["natural language instructions","code context from current workspace","selected code snippets for reference"],"output_types":["multi-file source code","executable application code","structured code with consistent formatting"],"categories":["code-generation-editing","planning-reasoning"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"vscode-tencent-cloud-coding-copilot__cap_1","uri":"capability://code.generation.editing.intelligent.inline.code.completion.with.language.specific.context","name":"intelligent inline code completion with language-specific context","description":"Provides real-time code completion suggestions as developers type, leveraging Tencent Hunyuan or configurable models to predict next tokens based on language syntax and project context. The completion engine supports 14+ programming languages (Java, Python, Go, C/C++, JavaScript, TypeScript, HTML, PHP, Ruby, Rust, Swift, Scala, Lua, Dart) with language-specific AST awareness. Suggestions are inserted directly into the editor via one-click acceptance or keyboard shortcuts.","intents":["I want faster code writing with context-aware suggestions as I type","I need completion that understands my project's coding patterns and conventions","I want to reduce boilerplate typing for common code structures","I need multi-language support across my polyglot codebase"],"best_for":["individual developers writing code across multiple languages","teams with polyglot codebases requiring consistent completion behavior","developers working in less-common languages (Scala, Lua, Dart, Swift)"],"limitations":["Completion trigger mechanism not documented — unclear if on-demand or continuous","No documented latency characteristics or token budget per completion","Language support limited to 14 documented languages; others unknown","Potential conflicts with other AI completion extensions (GitHub Copilot, Codeium) not addressed","Context window for completion suggestions not specified"],"requires":["VS Code extension installed","Active internet connection for inference","Tencent Cloud account or free tier access","File in one of 14+ supported languages"],"input_types":["partial code in editor","surrounding code context","language syntax rules"],"output_types":["code completion suggestions","single or multiple completion options"],"categories":["code-generation-editing"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"vscode-tencent-cloud-coding-copilot__cap_10","uri":"capability://text.generation.language.sidebar.integration.with.conversation.history.and.code.context","name":"sidebar integration with conversation history and code context","description":"Provides a dedicated sidebar panel within VS Code for accessing CodeBuddy features, maintaining conversation history, and managing code context. The sidebar displays ongoing conversations, allows code selection and insertion from chat, and provides quick access to custom agents and commands. Conversation history is persisted across sessions, enabling users to reference previous interactions. Code context can be selected from the editor and automatically included in conversations for context-aware responses.","intents":["I want to maintain conversation history with CodeBuddy across sessions","I need quick access to CodeBuddy features without command palette","I want to reference previous conversations and code discussions","I need to insert code from conversations directly into my editor"],"best_for":["developers using CodeBuddy frequently throughout the day","teams collaborating on code discussions","developers needing persistent context across coding sessions"],"limitations":["Conversation history storage location and retention not documented","Sidebar UI layout and customization options not specified","Code context selection mechanism not detailed","Conversation export or sharing capabilities not documented","Privacy implications of persistent history not addressed"],"requires":["VS Code extension installed","VS Code sidebar visible and accessible","Tencent Cloud account"],"input_types":["code selections from editor","conversation messages","custom agent invocations"],"output_types":["conversation display","code insertion into editor","conversation history"],"categories":["text-generation-language","memory-knowledge"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"vscode-tencent-cloud-coding-copilot__cap_11","uri":"capability://tool.use.integration.cross.ide.support.with.platform.specific.optimizations","name":"cross-ide support with platform-specific optimizations","description":"Extends CodeBuddy functionality beyond VS Code to JetBrains IDEs (IntelliJ IDEA, Rider, PyCharm, Android Studio), Visual Studio, HarmonyOS DevEco Studio, CloudStudio, and WeChat Mini Program Developer Tools. Each IDE integration is optimized for platform-specific UI patterns, keybindings, and workflows. The extension uses IDE-native APIs for code insertion, diagnostics integration, and sidebar rendering. Platform support is continuously updated, though some IDEs may experience delays due to release schedules.","intents":["I want to use CodeBuddy in my preferred IDE beyond VS Code","I need consistent CodeBuddy experience across multiple IDEs","I want CodeBuddy support for HarmonyOS or WeChat Mini Program development","I need CodeBuddy in JetBrains IDEs for Java, Python, or Kotlin development"],"best_for":["teams using multiple IDEs across different projects","developers working on HarmonyOS or WeChat Mini Programs","organizations standardizing on JetBrains or Visual Studio","polyglot teams requiring consistent AI assistance across tools"],"limitations":["IDE version requirements not documented per platform","Feature parity across IDEs not guaranteed — some features may be IDE-specific","Release delays for some IDEs due to platform update cycles","IDE-specific keybindings and UI patterns may differ from VS Code","Support for older IDE versions not documented"],"requires":["CodeBuddy extension installed for target IDE","Supported IDE version (requirements unknown)","Tencent Cloud account","Active internet connection"],"input_types":["code in IDE editor","IDE diagnostics","IDE-specific context"],"output_types":["code suggestions and completions","IDE-native annotations","code insertions"],"categories":["tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"vscode-tencent-cloud-coding-copilot__cap_2","uri":"capability://code.generation.editing.smart.code.review.with.normalization.and.best.practice.checking","name":"smart code review with normalization and best-practice checking","description":"Analyzes selected code or entire files to identify violations of coding standards, best practices, and normalization rules. The code review engine uses Tencent Hunyuan models to understand code semantics and compare against configurable rule sets. Reviews can be triggered on-demand via command palette or sidebar, with results presented as inline annotations or conversation-style feedback. Custom rules can be managed at the team level for enterprise deployments.","intents":["I want automated code review feedback before submitting pull requests","I need to enforce team coding standards and conventions automatically","I want to identify potential bugs or anti-patterns in my code","I need to ensure code normalization across my team's codebase"],"best_for":["engineering teams enforcing coding standards","code review processes seeking to reduce manual review burden","enterprises with custom coding conventions requiring automated enforcement"],"limitations":["Review scope not documented — unclear if operates on selection, file, or project level","Output format and presentation style not specified","Custom rules engine specification not provided","No documented accuracy metrics or false-positive rates","Rules management interface and API not documented"],"requires":["VS Code extension installed","Code selection or file open in editor","Active internet connection","Tencent Cloud account"],"input_types":["selected code snippet","entire file content","custom rule definitions"],"output_types":["review feedback text","inline code annotations","rule violation list","best-practice recommendations"],"categories":["code-generation-editing","safety-moderation"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"vscode-tencent-cloud-coding-copilot__cap_3","uri":"capability://code.generation.editing.unit.test.generation.with.language.specific.test.framework.support","name":"unit test generation with language-specific test framework support","description":"Automatically generates unit tests for selected code or functions using language-specific test frameworks (Jest for JavaScript, pytest for Python, JUnit for Java, etc.). The generation engine analyzes function signatures, logic flow, and edge cases to create comprehensive test cases. Generated tests can be inserted directly into test files or created as new test files within the project structure. Supports both synchronous and asynchronous code patterns.","intents":["I want to generate unit tests quickly without writing boilerplate test structure","I need test coverage for legacy code that lacks tests","I want to ensure edge cases are covered in my test suite","I need tests for async/await or promise-based code"],"best_for":["developers improving test coverage on existing codebases","teams adopting test-driven development practices","developers working with multiple languages requiring different test frameworks"],"limitations":["Test framework selection mechanism not documented","No documented support for mocking, fixtures, or test data generation","Generated test quality depends on model capability — no accuracy metrics provided","Cannot guarantee generated tests are executable without human review","Async/await support mentioned but implementation details unknown"],"requires":["VS Code extension installed","Code selection or function in editor","Active internet connection","Tencent Cloud account"],"input_types":["function or code selection","language context","test framework preference (implicit)"],"output_types":["test code in language-specific framework","test file content","test case specifications"],"categories":["code-generation-editing","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"vscode-tencent-cloud-coding-copilot__cap_4","uri":"capability://code.generation.editing.code.repair.and.error.fixing.with.diagnostic.integration","name":"code repair and error fixing with diagnostic integration","description":"Detects code errors, compilation failures, and runtime issues, then generates fixes or repair suggestions. The repair engine integrates with VS Code's diagnostic system to identify errors from linters and compilers, then uses Tencent Hunyuan models to understand error context and propose corrections. Repairs can be applied automatically or presented as suggestions for manual review. Supports syntax errors, type mismatches, logic errors, and common anti-patterns.","intents":["I want automatic fixes for compilation errors without manual debugging","I need suggestions for fixing runtime errors or exceptions","I want to repair code that violates type constraints","I need help fixing logic errors or anti-patterns"],"best_for":["developers debugging code quickly during development","teams reducing time spent on trivial error fixes","developers learning new languages and making common mistakes"],"limitations":["Automatic vs. suggestion-based repair mode not documented","Error detection scope limited to VS Code diagnostics — may miss runtime errors","No documented accuracy metrics for repair suggestions","Complex logic errors may require human intervention","Cannot guarantee repaired code is semantically correct"],"requires":["VS Code extension installed","File with errors open in editor","Active internet connection","Tencent Cloud account"],"input_types":["code with errors","error diagnostics from VS Code","error messages and stack traces"],"output_types":["corrected code","repair suggestions","explanation of fix"],"categories":["code-generation-editing","planning-reasoning"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"vscode-tencent-cloud-coding-copilot__cap_5","uri":"capability://text.generation.language.conversational.ai.technical.q.a.with.context.insertion","name":"conversational ai technical q&a with context insertion","description":"Provides a chat interface within VS Code for asking technical questions and receiving answers grounded in Tencent Cloud documentation, WeChat development guides, and general programming knowledge. The Q&A engine uses multi-turn conversation to maintain context across questions, allowing follow-up queries and clarifications. Code from the current editor can be selected and inserted into conversations for context-specific advice. Answers can reference Tencent Cloud APIs and services, with links to documentation. Custom team knowledge bases can be integrated for enterprise deployments.","intents":["I want to ask technical questions without leaving my editor","I need documentation or API reference for Tencent Cloud services","I want to get code-specific advice by sharing my code in conversation","I need to understand how to use WeChat or Tencent Cloud APIs"],"best_for":["developers building on Tencent Cloud platform","teams using WeChat Mini Programs or Tencent services","developers seeking quick technical answers without web search","enterprises with custom knowledge bases"],"limitations":["Knowledge base limited to Tencent Cloud, WeChat, and general programming docs — not comprehensive for all technologies","Custom knowledge base management interface not documented","Multi-turn conversation context window not specified","No documented source attribution for answers","Cannot access real-time information or external web resources"],"requires":["VS Code extension installed","Active internet connection","Tencent Cloud account","Optional: custom knowledge base for enterprise tier"],"input_types":["natural language questions","code snippets from editor","follow-up queries"],"output_types":["conversational text answers","code examples","documentation links","API references"],"categories":["text-generation-language","memory-knowledge","search-retrieval"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"vscode-tencent-cloud-coding-copilot__cap_6","uri":"capability://tool.use.integration.configurable.multi.model.inference.with.provider.switching","name":"configurable multi-model inference with provider switching","description":"Allows switching between multiple AI models (Tencent Hunyuan, DeepSeek, GLM) for code generation and analysis tasks. The model configuration system enables users to select preferred models at the extension level, with support for third-party model integration via API configuration. Model switching is persistent across VS Code sessions. Enterprise deployments can enforce model policies and restrict available models. The architecture supports flexible model selection without requiring extension restart.","intents":["I want to use different AI models for different coding tasks","I need to switch to a specific model for cost optimization","I want to test code generation quality across multiple models","I need to enforce specific models for compliance or security reasons"],"best_for":["developers experimenting with different model capabilities","teams optimizing inference costs across different models","enterprises with model selection policies","organizations integrating third-party models"],"limitations":["Model switching mechanism not documented — unclear if requires restart or is hot-swappable","API key configuration process for third-party models not specified","No documented performance characteristics per model","Model availability and pricing not documented","Enterprise policy enforcement mechanism not detailed"],"requires":["VS Code extension installed","Active internet connection","Tencent Cloud account or API keys for third-party models","Model selection in extension settings"],"input_types":["model selection preference","API credentials for third-party models"],"output_types":["model configuration state","code generation from selected model"],"categories":["tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"vscode-tencent-cloud-coding-copilot__cap_7","uri":"capability://automation.workflow.custom.agent.and.command.creation.with.team.management","name":"custom agent and command creation with team management","description":"Enables creation of custom agents and commands tailored to team workflows, with centralized management for enterprise deployments. Custom agents can be defined to perform specific coding tasks (e.g., 'generate API endpoint', 'refactor for performance') and invoked via command palette or sidebar. Commands are stored and versioned at the team level, allowing sharing across developers. The agent creation interface supports natural language instruction definition and parameter configuration. Enterprise accounts can enforce agent policies and audit usage.","intents":["I want to create reusable coding tasks for my team","I need to standardize code generation workflows across developers","I want to automate repetitive coding patterns specific to our architecture","I need to track and audit custom agent usage across the team"],"best_for":["engineering teams with standardized coding workflows","enterprises enforcing architectural patterns","organizations with custom code generation requirements","teams seeking to reduce cognitive load through workflow automation"],"limitations":["Custom agent creation API not documented","Agent parameter configuration interface not specified","Team management and sharing mechanism not detailed","Audit and usage tracking capabilities not documented","No documented limits on number of custom agents"],"requires":["VS Code extension installed","Tencent Cloud account with team/enterprise tier","Team management access for creating shared agents"],"input_types":["natural language agent instructions","parameter definitions","code templates"],"output_types":["custom agent definition","command palette entries","agent execution results"],"categories":["automation-workflow","planning-reasoning"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"vscode-tencent-cloud-coding-copilot__cap_8","uri":"capability://tool.use.integration.mcp.ecosystem.compatibility.with.open.source.integration","name":"mcp ecosystem compatibility with open-source integration","description":"Integrates with the Model Context Protocol (MCP) open ecosystem, enabling CodeBuddy to work alongside other MCP-compatible tools and services. The MCP integration allows CodeBuddy to leverage external tools, knowledge bases, and services through standardized MCP server interfaces. This enables extensibility without modifying the core extension, supporting custom integrations for specialized domains or internal tools. MCP compatibility is explicitly stated but implementation details are not documented.","intents":["I want to integrate CodeBuddy with my custom internal tools via MCP","I need CodeBuddy to access specialized knowledge bases through MCP servers","I want to extend CodeBuddy capabilities without modifying the extension","I need to connect CodeBuddy to open-source tools in the MCP ecosystem"],"best_for":["enterprises with custom internal tools and knowledge bases","teams building specialized coding workflows","organizations adopting MCP-based tool ecosystems","developers integrating CodeBuddy with open-source MCP servers"],"limitations":["MCP server implementation details not documented","Integration mechanism and configuration process unknown","No documented list of tested or compatible MCP servers","Custom MCP server development guidance not provided","Performance impact of MCP integrations not specified"],"requires":["VS Code extension installed","MCP server(s) to integrate","MCP server configuration and credentials","Network connectivity to MCP servers"],"input_types":["MCP server configuration","MCP protocol messages"],"output_types":["integrated tool capabilities","knowledge base access","custom service responses"],"categories":["tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"vscode-tencent-cloud-coding-copilot__cap_9","uri":"capability://safety.moderation.enterprise.rules.management.and.policy.enforcement","name":"enterprise rules management and policy enforcement","description":"Provides centralized rules management system for enterprises to define, enforce, and audit coding standards, security policies, and architectural constraints across teams. Rules can be applied to code review, generation, and completion capabilities. The rules engine supports conditional logic, custom metrics, and integration with CI/CD pipelines. Rules are versioned and can be rolled out gradually across teams. Audit logs track rule violations and enforcement actions.","intents":["I need to enforce security policies across all code generation","I want to ensure architectural patterns are followed automatically","I need to audit compliance with coding standards","I want to prevent certain code patterns or dependencies from being generated"],"best_for":["enterprises with strict security and compliance requirements","organizations enforcing architectural governance","teams managing large codebases with consistency requirements","regulated industries requiring audit trails"],"limitations":["Rules engine specification not documented","Conditional logic and custom metrics not detailed","CI/CD pipeline integration mechanism unknown","Audit log format and retention not specified","Rule rollout and versioning process not documented"],"requires":["VS Code extension installed","Tencent Cloud enterprise account","Team/organization management access","Rules definition and configuration"],"input_types":["rule definitions","policy specifications","code for evaluation"],"output_types":["rule enforcement decisions","audit logs","compliance reports"],"categories":["safety-moderation","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0}],"trust":{"score":47,"verified":false,"data_access_risk":"high","permissions":["VS Code extension installed (version requirement unknown)","Active internet connection for cloud-based inference","Tencent Cloud account or free tier access via copilot.tencent.com","Project files accessible within VS Code workspace","VS Code extension installed","Active internet connection for inference","Tencent Cloud account or free tier access","File in one of 14+ supported languages","VS Code sidebar visible and accessible","Tencent Cloud account"],"failure_modes":["Multi-file context understanding depends on project structure visibility — scope of accessible files not documented","No documented token limit per generation request, may fail on very large multi-file operations","Consistency across generated files relies on model capability, not explicit constraint enforcement","Cannot guarantee generated code passes compilation without human review","Completion trigger mechanism not documented — unclear if on-demand or continuous","No documented latency characteristics or token budget per completion","Language support limited to 14 documented languages; others unknown","Potential conflicts with other AI completion extensions (GitHub Copilot, Codeium) not addressed","Context window for completion suggestions not specified","Conversation history storage location and retention not documented","builder identity is not verified yet","no observed match outcomes yet"],"rank_breakdown":{"adoption":0.73,"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":"2026-05-03T15:20:32.168Z","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=tencent-cloud-codebuddy","compare_url":"https://unfragile.ai/compare?artifact=tencent-cloud-codebuddy"}},"signature":"GRdGziRTviKGjqfL8tNHnx4qVhGhnh3h1UewZeo6jcP0wJDa5hEmOAP3HEBekIrf6egMvqSROMxMcvub1V14Bw==","signedAt":"2026-06-19T22:09:48.429Z","signedBy":"unfragile.ai","version":1},"_links":{"self":"https://unfragile.ai/api/v1/passport/tencent-cloud-codebuddy","artifact":"https://unfragile.ai/tencent-cloud-codebuddy","verify":"https://unfragile.ai/api/v1/verify?slug=tencent-cloud-codebuddy","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"}}