{"passport":{"unfragile":{"@version":"1.0","version":"2026-05","artifact":{"id":"vscode-alvaai-alva","slug":"alva-ai-assistant-chat-code-lab","name":"Alva - AI Assistant, Chat & Code Lab","type":"extension","url":"https://marketplace.visualstudio.com/items?itemName=AlvaAI.Alva","page_url":"https://unfragile.ai/alva-ai-assistant-chat-code-lab","categories":["code-editors","testing-quality"],"tags":["ai","ai-tools","algorithms","analysis","anomaly","artificial intelligence","assessment","audit","autocorrect","automated review","c#","c++","chatgpt","clean code","code analysis","code generator","code integrity","code quality","code review","complexity","compliance","correctness","coverage","css","cybersecurity","data science","debugging","deep learning","deployment","detection","devops","documentation","efficiency","engineering","error detection","ethics","golang","gpt","gpt3","gpt4","integration","integrity","java","javascript","kotlin","languages","lua","machine learning","maintenance","management","modelling","monitoring","neural networks","nlp","optimization","perl","php","practices","prediction","python","r","refactoring","reliability","ruby","rust","scala","scalability","sdlc","security","semantics","shell","software quality","sql","standardization","static analysis","swift","syntax","testing","typescript","vulnerabilities","vulnerability scanner"],"pricing":{"model":"freemium","free":true,"starting_price":null},"status":"active","verified":false},"capabilities":[{"id":"vscode-alvaai-alva__cap_0","uri":"capability://code.generation.editing.inline.bug.detection.and.auto.fix","name":"inline-bug-detection-and-auto-fix","description":"Analyzes the current file's code by sending it to OpenAI's GPT-3.5-turbo API to identify logical errors, runtime issues, and common bugs, then generates corrected code that can be clicked and pasted directly into the editor. The extension maintains the original code context and provides inline suggestions without requiring manual code submission or context switching.","intents":["I want to find bugs in my code without running a linter or debugger","I need AI to suggest fixes for errors I'm seeing in my code","I want to quickly patch code issues without leaving my editor"],"best_for":["solo developers debugging code interactively","teams doing rapid prototyping where formal testing isn't yet in place","developers learning new languages who need immediate error feedback"],"limitations":["No static analysis — relies entirely on LLM pattern recognition, which may miss subtle logic errors or type mismatches","Context limited to single file; cannot detect bugs arising from cross-file dependencies or module interactions","Requires OpenAI API calls for every analysis, incurring per-token costs and network latency (~1-3 seconds per request)","No guarantee of correctness — LLM-generated fixes may introduce new bugs or be semantically incorrect"],"requires":["VS Code (version unspecified, likely 1.60+)","Active OpenAI API key with available credits","Internet connectivity for API calls","Supported programming language (specific list unknown)"],"input_types":["source code (current file in editor)"],"output_types":["corrected code snippet","explanation of detected bugs","suggested fixes as clickable code blocks"],"categories":["code-generation-editing","debugging"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"vscode-alvaai-alva__cap_1","uri":"capability://code.generation.editing.code.efficiency.optimization","name":"code-efficiency-optimization","description":"Sends the current file's code to GPT-3.5-turbo to identify performance bottlenecks, algorithmic inefficiencies, and resource-heavy patterns, then generates optimized versions with explanations of improvements. The extension suggests refactored code that reduces time complexity, memory usage, or redundant operations while preserving functionality.","intents":["I want to optimize slow or inefficient code without manually profiling it","I need suggestions for reducing algorithmic complexity in my implementation","I want to improve code performance for resource-constrained environments"],"best_for":["performance-conscious developers optimizing existing codebases","teams building resource-constrained applications (embedded systems, mobile)","developers learning optimization patterns and best practices"],"limitations":["No profiling data — optimization suggestions are based on code patterns, not actual runtime metrics or bottleneck identification","Cannot optimize across multiple files or understand system-level performance constraints","LLM may suggest micro-optimizations with negligible real-world impact while missing architectural inefficiencies","No validation that optimized code maintains original behavior or passes existing tests"],"requires":["VS Code (version unspecified)","OpenAI API key with available credits","Internet connectivity","Source code in a supported language"],"input_types":["source code (current file)"],"output_types":["optimized code snippet","explanation of efficiency improvements","complexity analysis (e.g., 'reduced from O(n²) to O(n log n)')"],"categories":["code-generation-editing","optimization"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"vscode-alvaai-alva__cap_10","uri":"capability://tool.use.integration.click.to.paste.code.insertion","name":"click-to-paste-code-insertion","description":"Provides a direct integration between AI-generated code suggestions and the VS Code editor through clickable code blocks. When the assistant generates code (from bug fixes, refactoring, tests, etc.), developers can click a 'paste' button to insert the code directly at the cursor position, eliminating manual copy-paste workflows and reducing friction in the code generation loop.","intents":["I want to quickly apply AI-generated code suggestions without manual copying","I need to iterate rapidly on code generation without context-switching","I want to accept or reject generated code with a single click"],"best_for":["developers using AI code generation extensively","rapid prototyping and iterative development workflows","developers seeking minimal friction in AI-assisted coding"],"limitations":["No preview or diff view before insertion — code is inserted directly without review opportunity","No undo integration; pasting code creates an undo point but doesn't provide semantic rollback","Insertion position determined by cursor location; may insert code in unintended locations if cursor is not positioned correctly","No validation that inserted code is syntactically correct or compatible with surrounding code","Single-click insertion may lead to accidental code insertion without review"],"requires":["VS Code","Alva extension installed and active","Code generation from Alva chat or inline suggestions"],"input_types":["AI-generated code blocks from chat or inline suggestions"],"output_types":["code inserted at cursor position in editor","undo history entry for inserted code"],"categories":["tool-use-integration","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"vscode-alvaai-alva__cap_11","uri":"capability://tool.use.integration.openai.api.key.integration.and.authentication","name":"openai-api-key-integration-and-authentication","description":"Manages OpenAI API authentication by accepting user-provided API keys and routing all AI requests through OpenAI's GPT-3.5-turbo API. The extension requires no signup or login; developers simply provide their OpenAI API key once, and all subsequent requests are authenticated and billed to their OpenAI account. Key storage and management is handled by VS Code's secure credential storage (unknown if encrypted locally or stored in plaintext).","intents":["I want to use Alva with my existing OpenAI API account without creating new credentials","I need to control costs by using my own API key and monitoring usage","I want to ensure my code is sent only to OpenAI, not to a third-party service"],"best_for":["developers with existing OpenAI API accounts","organizations with OpenAI API contracts or enterprise agreements","developers concerned about data privacy and third-party service usage"],"limitations":["Requires active OpenAI API account with available credits; no free tier or trial provided by Alva","API key storage mechanism not documented; unknown if keys are encrypted or stored in plaintext","No built-in cost monitoring or usage tracking; developers must monitor OpenAI dashboard separately","OpenAI API dependency creates single point of failure; service outages or API changes affect all Alva functionality","No support for alternative LLM providers (Anthropic, local models, etc.); locked to OpenAI"],"requires":["VS Code","OpenAI API key (obtainable from https://platform.openai.com/account/api-keys)","Active OpenAI account with available API credits","Internet connectivity to OpenAI API endpoints"],"input_types":["OpenAI API key (string)"],"output_types":["authenticated API requests to OpenAI","API responses (code, suggestions, feedback)"],"categories":["tool-use-integration","safety-moderation"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"vscode-alvaai-alva__cap_12","uri":"capability://text.generation.language.sidebar.chat.interface","name":"sidebar-chat-interface","description":"Provides a persistent chat panel in VS Code's sidebar where developers can ask questions, request code generation, and receive conversational responses from GPT-3.5-turbo. The chat interface maintains context of the current file and allows multi-turn conversations without requiring manual code submission or context specification, enabling iterative refinement of suggestions.","intents":["I want to ask an AI assistant questions about my code without leaving the editor","I need to have a conversation with AI to refine code suggestions iteratively","I want to maintain context across multiple related questions about my codebase"],"best_for":["developers seeking interactive AI assistance during coding","teams using AI as a supplementary developer","developers learning through interactive dialogue with AI"],"limitations":["Chat context limited to current file; cannot maintain conversation history across files or projects","Unknown if conversation history is persisted across sessions or cleared on extension reload","No integration with version control or code review workflows","Chat responses are advisory only; no enforcement or integration with CI/CD","No support for multi-user collaboration or shared chat history"],"requires":["VS Code","OpenAI API key","Internet connectivity"],"input_types":["natural language questions or requests","current file context (automatically provided)"],"output_types":["conversational responses from GPT-3.5-turbo","code snippets or examples","clickable code blocks for insertion"],"categories":["text-generation-language","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"vscode-alvaai-alva__cap_13","uri":"capability://tool.use.integration.freemium.pricing.with.optional.future.subscriptions","name":"freemium-pricing-with-optional-future-subscriptions","description":"Offers the extension itself at no cost, with all AI functionality powered by user-provided OpenAI API keys. Developers pay only for OpenAI API usage (per-token pricing), with no subscription required to Alva itself. The extension documentation indicates that future versions may introduce optional premium features or subscriptions, but current version is entirely free with API-based cost model.","intents":["I want to use AI-assisted coding without paying for a subscription service","I want to control my costs by using my own API key and monitoring usage","I want to try AI coding assistance without committing to a paid plan"],"best_for":["cost-conscious developers with existing OpenAI API accounts","teams with OpenAI API contracts or enterprise agreements","developers seeking transparent, usage-based pricing"],"limitations":["OpenAI API costs can accumulate quickly with heavy usage; no built-in cost controls or rate limiting","No free tier or trial provided by Alva; requires active OpenAI account with credits","Future versions may introduce paid features or subscriptions, changing the cost model","No cost monitoring or usage tracking built into extension; requires manual monitoring via OpenAI dashboard","Pricing is subject to OpenAI's API rate changes and billing model updates"],"requires":["VS Code","OpenAI API key with available credits","Willingness to pay OpenAI's per-token API pricing"],"input_types":["none (pricing model is transparent and usage-based)"],"output_types":["access to all Alva features","API usage tracked by OpenAI (not by Alva)"],"categories":["tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"vscode-alvaai-alva__cap_2","uri":"capability://code.generation.editing.code.language.translation","name":"code-language-translation","description":"Accepts source code in one programming language and uses GPT-3.5-turbo to generate semantically equivalent code in a target language. The extension maintains logic and functionality while adapting to the idioms, syntax, and standard libraries of the destination language, with generated code available for direct insertion into the editor.","intents":["I need to convert code from one language to another (e.g., Python to JavaScript)","I want to port a legacy codebase to a modern language","I need to generate equivalent code in a language I'm less familiar with"],"best_for":["developers migrating codebases between languages","polyglot teams needing code in multiple languages","developers learning new languages by comparing implementations"],"limitations":["No guarantee of idiomatic output — generated code may be literal translations rather than leveraging target language best practices","Cannot handle language-specific features that don't have direct equivalents (e.g., Python decorators → JavaScript)","May miss subtle semantic differences between languages (e.g., integer division, type coercion)","Requires manual testing and validation; generated code may have bugs or performance issues","Single-file scope — cannot translate multi-file projects or resolve cross-language dependencies"],"requires":["VS Code","OpenAI API key","Internet connectivity","Source code in a supported language"],"input_types":["source code (current file)","target language specification (via chat or command)"],"output_types":["translated source code","explanation of translation choices","notes on language-specific differences"],"categories":["code-generation-editing","transformation"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"vscode-alvaai-alva__cap_3","uri":"capability://code.generation.editing.unit.test.generation","name":"unit-test-generation","description":"Analyzes the current file's functions and methods by sending them to GPT-3.5-turbo, then generates unit test code covering happy paths, edge cases, and error conditions. The generated tests follow the conventions and frameworks of the detected language (Jest for JavaScript, pytest for Python, etc.) and are provided as clickable code blocks for insertion.","intents":["I want to generate unit tests for my code without writing them manually","I need test coverage for edge cases I might have missed","I want to add tests to legacy code that has none"],"best_for":["developers building test coverage quickly in greenfield projects","teams adding tests to untested legacy codebases","developers learning testing patterns and best practices"],"limitations":["Generated tests may not cover all edge cases or integration scenarios — LLM-based generation is heuristic, not exhaustive","Cannot understand business logic or domain-specific requirements; tests may be technically valid but semantically meaningless","No integration with actual test runners — generated code must be manually validated and executed","May generate tests that pass trivially without actually validating behavior","Single-file scope — cannot generate tests for multi-file interactions or external dependencies"],"requires":["VS Code","OpenAI API key","Internet connectivity","Source code in a supported language with a recognized test framework"],"input_types":["source code (current file with functions/methods)"],"output_types":["unit test code (framework-specific: Jest, pytest, JUnit, etc.)","test cases covering happy paths and edge cases","mock/stub suggestions for external dependencies"],"categories":["code-generation-editing","testing"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"vscode-alvaai-alva__cap_4","uri":"capability://code.generation.editing.code.refactoring.and.restructuring","name":"code-refactoring-and-restructuring","description":"Accepts code and refactoring intent (via chat or inline request) and uses GPT-3.5-turbo to generate restructured code that improves readability, maintainability, or adherence to design patterns. The extension suggests changes like extracting methods, renaming variables, applying SOLID principles, or reorganizing class hierarchies while preserving functionality.","intents":["I want to refactor messy code to be more readable and maintainable","I need to apply design patterns to my code structure","I want to extract duplicated logic into reusable functions"],"best_for":["developers improving code quality in existing projects","teams standardizing code style and structure","developers learning refactoring techniques and design patterns"],"limitations":["No static analysis — refactoring suggestions are based on pattern recognition, not comprehensive code flow analysis","Cannot guarantee behavior preservation; refactored code may have subtle bugs or behavioral changes","Single-file scope — cannot refactor across module boundaries or resolve cross-file dependencies","May suggest refactorings that conflict with existing project conventions or architecture","Requires manual testing and code review before integration"],"requires":["VS Code","OpenAI API key","Internet connectivity","Source code in a supported language"],"input_types":["source code (current file)","refactoring intent (e.g., 'extract method', 'apply factory pattern')"],"output_types":["refactored code","explanation of changes and design patterns applied","suggestions for further improvements"],"categories":["code-generation-editing","refactoring"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"vscode-alvaai-alva__cap_5","uri":"capability://code.generation.editing.automated.code.documentation.generation","name":"automated-code-documentation-generation","description":"Analyzes functions, classes, and modules in the current file and uses GPT-3.5-turbo to generate inline comments, docstrings, and documentation in the style appropriate to the language (JSDoc for JavaScript, docstrings for Python, etc.). The extension infers intent from code structure and generates documentation that explains purpose, parameters, return values, and usage examples.","intents":["I want to add documentation to undocumented code quickly","I need to generate docstrings for functions I've written","I want to improve code readability with inline comments"],"best_for":["developers documenting existing codebases rapidly","teams enforcing documentation standards","developers learning documentation best practices"],"limitations":["Generated documentation may be inaccurate or misleading if code intent is unclear from structure alone","Cannot infer business logic or domain-specific context; documentation may be technically correct but semantically wrong","Single-file scope — cannot generate cross-file or architectural documentation","May generate verbose or redundant documentation that requires manual cleanup","No validation that generated documentation matches actual code behavior"],"requires":["VS Code","OpenAI API key","Internet connectivity","Source code in a supported language"],"input_types":["source code (current file with functions/classes/modules)"],"output_types":["inline comments","docstrings (language-specific: JSDoc, Python docstrings, etc.)","usage examples","parameter and return value documentation"],"categories":["code-generation-editing","documentation"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"vscode-alvaai-alva__cap_6","uri":"capability://code.generation.editing.security.and.integrity.analysis","name":"security-and-integrity-analysis","description":"Sends the current file's code to GPT-3.5-turbo to identify security vulnerabilities, unsafe patterns, and integrity risks such as SQL injection, XSS, hardcoded credentials, insecure cryptography, and unsafe deserialization. The extension provides explanations of detected issues and suggests secure alternatives or mitigations.","intents":["I want to identify security vulnerabilities in my code before deployment","I need to find hardcoded secrets or unsafe patterns in my codebase","I want to understand security best practices for my language"],"best_for":["developers building security-conscious applications","teams conducting code security reviews","developers learning secure coding practices"],"limitations":["No formal security audit — LLM-based detection may miss sophisticated vulnerabilities or false-positive on safe patterns","Cannot detect runtime vulnerabilities or behavioral security issues; analysis is static and pattern-based","Single-file scope — cannot detect vulnerabilities arising from cross-file interactions or external dependencies","No integration with vulnerability databases (CVE, NVD); cannot identify known library vulnerabilities","Requires manual validation and security expertise to assess severity and implement fixes"],"requires":["VS Code","OpenAI API key","Internet connectivity","Source code in a supported language"],"input_types":["source code (current file)"],"output_types":["list of identified security issues","severity assessment (high/medium/low)","explanation of vulnerability and attack vector","suggested secure alternatives or mitigations"],"categories":["code-generation-editing","safety-moderation"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"vscode-alvaai-alva__cap_7","uri":"capability://text.generation.language.interactive.code.review.and.feedback","name":"interactive-code-review-and-feedback","description":"Provides a chat interface within VS Code's sidebar where developers can ask questions about code, request reviews, and receive real-time feedback from GPT-3.5-turbo. The assistant analyzes the current file context and provides suggestions on code quality, design, performance, and best practices without requiring manual code submission or context specification.","intents":["I want to ask an AI assistant about my code without leaving the editor","I need real-time feedback on code quality and design decisions","I want to discuss architectural choices or implementation approaches"],"best_for":["solo developers seeking code review feedback","teams using AI as a supplementary code reviewer","developers learning code quality principles through interactive feedback"],"limitations":["Chat context limited to current file; cannot review multi-file architectures or cross-module interactions","No persistent conversation history across sessions (unknown if history is maintained)","Feedback is advisory only — no enforcement or integration with CI/CD pipelines","LLM-based feedback may be inconsistent or contradict project-specific conventions","No integration with version control or code review workflows (GitHub, GitLab, etc.)"],"requires":["VS Code","OpenAI API key","Internet connectivity","Source code in a supported language"],"input_types":["natural language questions or requests","current file context (automatically provided)"],"output_types":["conversational feedback and suggestions","code snippets or examples","explanations of best practices","clickable code blocks for direct insertion"],"categories":["text-generation-language","code-generation-editing"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"vscode-alvaai-alva__cap_8","uri":"capability://text.generation.language.intelligent.terminal.command.assistance","name":"intelligent-terminal-command-assistance","description":"Provides a voice-enabled or text-based interface to a terminal assistant that uses GPT-3.5-turbo to suggest, explain, and generate shell commands based on natural language intent. Developers can describe what they want to accomplish (e.g., 'find all Python files modified in the last week') and receive suggested commands with explanations, which can be executed directly or copied to the terminal.","intents":["I want to generate shell commands from natural language descriptions","I need help remembering complex command syntax without leaving the editor","I want to automate repetitive terminal tasks with AI suggestions"],"best_for":["developers unfamiliar with shell scripting or command-line tools","teams automating DevOps and build tasks","developers working across multiple operating systems with different command syntax"],"limitations":["No execution safety checks — generated commands are not validated before execution; dangerous commands (rm -rf, etc.) may be suggested","Context limited to current workspace; cannot understand system-wide state or environment variables","Platform-specific — commands generated for one OS may not work on another (e.g., bash vs. PowerShell)","No integration with actual shell execution; commands must be manually copied or executed","May generate commands with incorrect syntax or flags for the user's shell version"],"requires":["VS Code","OpenAI API key","Internet connectivity","Terminal/shell integration (bash, zsh, PowerShell, etc.)"],"input_types":["natural language description of desired action","optional: current working directory or file context"],"output_types":["suggested shell commands","explanation of what each command does","alternative command options","warnings about potentially dangerous operations"],"categories":["text-generation-language","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"vscode-alvaai-alva__cap_9","uri":"capability://code.generation.editing.multi.language.code.analysis.and.suggestions","name":"multi-language-code-analysis-and-suggestions","description":"Automatically detects the programming language of the current file and applies language-specific analysis using GPT-3.5-turbo. The extension understands language idioms, standard libraries, and best practices for 20+ languages (JavaScript, Python, Java, C#, Go, Rust, etc.) and provides tailored suggestions that respect language conventions and ecosystem standards.","intents":["I want AI assistance that understands my language's idioms and best practices","I need suggestions that follow my language's community standards and conventions","I want to work with multiple languages and get appropriate feedback for each"],"best_for":["polyglot developers working across multiple languages","teams with diverse tech stacks","developers learning new languages and their conventions"],"limitations":["Language detection may fail for ambiguous or mixed-language files","Specific list of supported languages not documented; some niche languages may not be recognized","Suggestions may not reflect latest language versions or ecosystem changes","No integration with language-specific linters, formatters, or type checkers","Cannot understand project-specific conventions or style guides"],"requires":["VS Code","OpenAI API key","Internet connectivity","Source code in a supported programming language"],"input_types":["source code (current file in any supported language)"],"output_types":["language-specific suggestions and best practices","idiomatic code examples","explanations of language-specific patterns","refactored code following language conventions"],"categories":["code-generation-editing","data-processing-analysis"],"confidence":0.5,"matches":0,"success_rate":0}],"trust":{"score":43,"verified":false,"data_access_risk":"high","permissions":["VS Code (version unspecified, likely 1.60+)","Active OpenAI API key with available credits","Internet connectivity for API calls","Supported programming language (specific list unknown)","VS Code (version unspecified)","OpenAI API key with available credits","Internet connectivity","Source code in a supported language","VS Code","Alva extension installed and active"],"failure_modes":["No static analysis — relies entirely on LLM pattern recognition, which may miss subtle logic errors or type mismatches","Context limited to single file; cannot detect bugs arising from cross-file dependencies or module interactions","Requires OpenAI API calls for every analysis, incurring per-token costs and network latency (~1-3 seconds per request)","No guarantee of correctness — LLM-generated fixes may introduce new bugs or be semantically incorrect","No profiling data — optimization suggestions are based on code patterns, not actual runtime metrics or bottleneck identification","Cannot optimize across multiple files or understand system-level performance constraints","LLM may suggest micro-optimizations with negligible real-world impact while missing architectural inefficiencies","No validation that optimized code maintains original behavior or passes existing tests","No preview or diff view before insertion — code is inserted directly without review opportunity","No undo integration; pasting code creates an undo point but doesn't provide semantic rollback","builder identity is not verified yet","no observed match outcomes yet"],"rank_breakdown":{"adoption":0.52,"quality":0.35,"ecosystem":0.45,"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":"2026-05-24T12:16:34.118Z","last_scraped_at":"2026-05-03T15:20:31.090Z","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=alva-ai-assistant-chat-code-lab","compare_url":"https://unfragile.ai/compare?artifact=alva-ai-assistant-chat-code-lab"}},"signature":"6RgPXhxRIXGI7ZfCFIfht70oTFRQE/o1TPD4wzQzVVAWgmUFx79DbgkTAhJEKbZfIMsbC9GcwXT0gKLDBadBCg==","signedAt":"2026-06-21T11:47:23.566Z","signedBy":"unfragile.ai","version":1},"_links":{"self":"https://unfragile.ai/api/v1/passport/alva-ai-assistant-chat-code-lab","artifact":"https://unfragile.ai/alva-ai-assistant-chat-code-lab","verify":"https://unfragile.ai/api/v1/verify?slug=alva-ai-assistant-chat-code-lab","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"}}