{"passport":{"unfragile":{"@version":"1.0","version":"2026-05","artifact":{"id":"github-leon-ai--leon","slug":"leon-ai--leon","name":"leon","type":"agent","url":"https://getleon.ai","page_url":"https://unfragile.ai/leon-ai--leon","categories":["chatbots-assistants"],"tags":["ai","ai-agent","ai-assistant","artificial-intelligence","assistant","automation","bot","chatbot","leon","nodejs","offline","personal-assistant","privacy","python","speech-recognition","speech-synthesis","speech-to-text","text-to-speech","virtual-assistant","voice-assistant"],"pricing":{"model":"open_source","free":true,"starting_price":null},"status":"active","verified":false},"capabilities":[{"id":"github-leon-ai--leon__cap_0","uri":"capability://automation.workflow.offline.first.voice.to.intent.recognition.and.execution","name":"offline-first voice-to-intent recognition and execution","description":"Leon processes speech input through local speech-to-text engines (supporting multiple STT backends like Sphinx, Google Cloud Speech, or Azure), converts recognized text to structured intents via a modular skill-matching system, and executes corresponding actions without requiring cloud connectivity. The architecture uses a plugin-based skill loader that maps utterances to Python/Node.js modules, enabling offline operation while maintaining privacy by keeping audio processing local.","intents":["I want to build a voice assistant that works without sending audio to cloud services","I need to add custom voice commands that execute local scripts or integrations","I want to deploy a privacy-first personal assistant that doesn't depend on external APIs"],"best_for":["privacy-conscious developers building local-first assistants","teams deploying voice automation in restricted network environments","solo developers wanting to avoid cloud STT/TTS costs at scale"],"limitations":["Offline STT accuracy is lower than cloud-based alternatives (Sphinx ~70-80% vs Google Cloud ~95%+)","Skill matching relies on exact phrase or fuzzy string matching, not semantic understanding — requires explicit intent definition","No built-in multi-language support for offline mode; cloud backends add latency and dependency","Audio processing pipeline adds ~500-1500ms latency depending on STT backend choice"],"requires":["Node.js 14+ for core agent runtime","Python 3.7+ for skill execution (many skills written in Python)","PocketSphinx or compatible offline STT engine, OR API credentials for cloud STT (Google Cloud Speech, Azure, etc.)","System audio input/output capabilities (microphone + speakers or headset)"],"input_types":["audio (WAV, MP3, raw PCM)","text (fallback text input for testing)","structured intent objects (for programmatic skill invocation)"],"output_types":["audio (synthesized speech via TTS)","text (transcribed intent and response)","side effects (file operations, API calls, system commands executed by skills)"],"categories":["automation-workflow","voice-interface"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github-leon-ai--leon__cap_1","uri":"capability://tool.use.integration.modular.skill.plugin.system.with.intent.routing","name":"modular skill plugin system with intent routing","description":"Leon implements a skill-based architecture where each capability is a self-contained module (Python or Node.js) that registers itself with a central intent router. Skills declare their trigger phrases, required parameters, and execution logic; the router uses fuzzy string matching or regex patterns to map user utterances to the appropriate skill, then invokes it with extracted parameters. This design enables non-developers to add new capabilities by dropping a skill file into a directory without modifying core agent code.","intents":["I want to extend Leon with custom commands without forking the codebase","I need to create a skill that integrates with my internal APIs or services","I want to share reusable skills with other Leon users in a community marketplace"],"best_for":["developers building extensible automation platforms","teams creating domain-specific assistants (e.g., DevOps, customer service bots)","open-source communities wanting to crowdsource assistant capabilities"],"limitations":["Intent matching is deterministic and phrase-based, not semantic — ambiguous utterances may route to wrong skill or fail silently","No built-in skill versioning or dependency management — breaking changes in core API can orphan community skills","Skill isolation is filesystem-based, not sandboxed — malicious or buggy skills can crash the entire agent or access sensitive data","Parameter extraction relies on regex/positional parsing, not structured NLU — complex multi-parameter intents require manual parsing in skill code"],"requires":["Node.js 14+ for skill loader and router","Python 3.7+ for Python-based skills (or Node.js for JavaScript skills)","Skill template/boilerplate (provided in docs) to define intent metadata","File system write access to skills directory for dynamic skill loading"],"input_types":["skill manifest (JSON or YAML declaring trigger phrases, parameters, description)","user utterance (text or transcribed speech)","structured parameter objects (extracted from utterance or provided programmatically)"],"output_types":["skill execution result (JSON, text, or side effects)","routing decision (which skill matched, confidence score if applicable)","error or fallback response if no skill matches"],"categories":["tool-use-integration","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github-leon-ai--leon__cap_10","uri":"capability://automation.workflow.system.command.execution.and.shell.integration","name":"system command execution and shell integration","description":"Leon skills can execute system commands (shell scripts, executables) through a sandboxed execution layer, enabling automation of OS-level tasks like file operations, process management, or system configuration. Skills invoke commands via a wrapper that captures output and errors, returning results to the user. This enables voice control of system administration tasks, file management, and integration with command-line tools.","intents":["I want to control my computer's files and processes via voice commands","I need to automate system administration tasks through voice","I want to integrate Leon with command-line tools and scripts"],"best_for":["developers building system administration assistants","power users automating personal workflows","teams integrating Leon with DevOps tooling"],"limitations":["Command execution is not sandboxed — malicious or buggy skills can damage the system or access sensitive data","No built-in command whitelisting or permission control — any skill can execute any command","Output capture is synchronous and blocking — long-running commands freeze the agent","Cross-platform compatibility is limited — shell syntax differs between Windows (PowerShell), macOS (bash), and Linux (bash/sh)"],"requires":["Node.js 14+ with child_process module","System shell (bash, PowerShell, cmd.exe) available","Appropriate file system and process permissions for the commands being executed","Skill code that invokes commands safely (input validation, error handling)"],"input_types":["command string (shell command to execute)","arguments and parameters (passed to command)","working directory (optional, for command execution context)"],"output_types":["command stdout (standard output)","command stderr (error output)","exit code (0 for success, non-zero for failure)","execution time and resource usage (if tracked)"],"categories":["automation-workflow","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github-leon-ai--leon__cap_11","uri":"capability://memory.knowledge.context.aware.skill.execution.with.user.preferences.and.state","name":"context-aware skill execution with user preferences and state","description":"Leon maintains optional user profiles and skill state (stored in JSON files or external databases) that skills can access during execution. Skills can read user preferences (language, timezone, favorite contacts) and maintain state (reminders, task lists, conversation history) to provide personalized responses. This enables skills to adapt behavior based on user context without requiring explicit parameters in every utterance.","intents":["I want my assistant to remember my preferences and adapt responses accordingly","I need skills to maintain state across multiple invocations (e.g., task lists, reminders)","I want personalized responses based on user profile information"],"best_for":["developers building personalized assistants","teams creating stateful automation workflows","solo developers wanting to add memory to their voice assistant"],"limitations":["No built-in persistence layer — state is stored in JSON files by default, not suitable for concurrent access or large datasets","No encryption for stored state — sensitive data (passwords, API keys) should not be stored in user profiles","No automatic state synchronization across devices — each Leon instance maintains separate state","Skill authors must manually implement state management — no framework-level abstraction"],"requires":["User profile file (JSON) with preferences and metadata","Skill code that reads/writes user state","Optional: external database (SQLite, PostgreSQL) for persistent state","File system or database write permissions for state storage"],"input_types":["user ID or profile identifier","user preferences (language, timezone, etc.)","skill state (task lists, reminders, conversation history)"],"output_types":["personalized skill response","updated user state (if modified by skill)","error if state is corrupted or inaccessible"],"categories":["memory-knowledge","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github-leon-ai--leon__cap_2","uri":"capability://text.generation.language.text.to.speech.synthesis.with.multiple.backend.support","name":"text-to-speech synthesis with multiple backend support","description":"Leon generates spoken responses by routing text through configurable TTS backends (local engines like eSpeak, or cloud APIs like Google Cloud Text-to-Speech, Azure, or Amazon Polly). The TTS layer abstracts backend selection, allowing users to choose between offline synthesis (lower quality, no latency) and cloud synthesis (higher quality, requires API key). Audio output is streamed or buffered to system speakers, with support for multiple voices and languages depending on backend capabilities.","intents":["I want my assistant to speak responses in a natural voice without cloud dependency","I need to support multiple languages and voices in my voice assistant","I want to choose between fast local TTS and high-quality cloud TTS based on deployment context"],"best_for":["developers building voice-first interfaces with offline requirements","teams needing multi-language voice support across regions","privacy-focused deployments where audio output must not leave the device"],"limitations":["Offline TTS (eSpeak) produces robotic, low-quality speech unsuitable for consumer applications","Cloud TTS backends introduce 1-3 second latency and require internet connectivity plus API credentials","No built-in voice cloning or custom voice training — limited to pre-built voices from TTS providers","Audio streaming/buffering can cause delays in real-time conversation if not tuned properly"],"requires":["eSpeak or compatible offline TTS engine (for offline mode), OR API credentials for cloud TTS (Google Cloud, Azure, AWS)","System audio output device (speakers, headset, or audio interface)","Node.js 14+ for TTS abstraction layer","Network connectivity if using cloud TTS backends"],"input_types":["text (response to synthesize)","language code (e.g., 'en-US', 'fr-FR')","voice identifier (backend-specific voice name or ID)","speech rate and pitch parameters (if supported by backend)"],"output_types":["audio stream (WAV, MP3, or raw PCM)","audio file (saved to disk for caching or replay)","direct speaker output (streamed to system audio device)"],"categories":["text-generation-language","audio-synthesis"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github-leon-ai--leon__cap_3","uri":"capability://text.generation.language.speech.to.text.transcription.with.offline.and.cloud.backends","name":"speech-to-text transcription with offline and cloud backends","description":"Leon converts audio input to text using pluggable STT backends: offline engines (PocketSphinx, CMU Sphinx) for privacy and zero-latency operation, or cloud APIs (Google Cloud Speech-to-Text, Azure Speech Services, Deepgram) for higher accuracy. The STT layer handles audio format conversion, noise filtering, and streaming transcription, returning recognized text with optional confidence scores. Users configure their preferred backend via environment variables or config files.","intents":["I want to transcribe voice commands locally without sending audio to cloud services","I need high-accuracy speech recognition for my voice assistant","I want to support multiple languages and accents in voice input"],"best_for":["privacy-first voice assistant deployments","offline-capable systems in restricted network environments","developers optimizing for latency-sensitive voice interactions"],"limitations":["Offline STT (PocketSphinx) has ~70-80% accuracy on clean audio, degrades significantly with background noise or accents","Cloud STT requires internet connectivity and API credentials; adds 500ms-2s latency depending on audio length and provider","No built-in speaker diarization or multi-speaker support — assumes single speaker per utterance","Audio preprocessing (noise reduction, format conversion) can introduce artifacts or latency if not tuned carefully"],"requires":["PocketSphinx or CMU Sphinx (for offline mode), OR API credentials for cloud STT (Google Cloud, Azure, Deepgram, etc.)","System audio input device (microphone or audio interface)","Node.js 14+ for STT abstraction and audio handling","Python 3.7+ if using Sphinx-based backends"],"input_types":["audio stream (WAV, MP3, raw PCM, or live microphone input)","language code (e.g., 'en-US', 'fr-FR')","audio format and sample rate metadata"],"output_types":["transcribed text","confidence score (if provided by backend)","alternative transcriptions (if backend supports N-best results)","timing information (word-level timestamps if available)"],"categories":["text-generation-language","audio-processing"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github-leon-ai--leon__cap_4","uri":"capability://planning.reasoning.intent.based.task.automation.with.parameter.extraction","name":"intent-based task automation with parameter extraction","description":"Leon maps recognized user utterances to executable tasks by extracting parameters from text using regex patterns or simple NLU heuristics, then invoking the corresponding skill with structured parameters. For example, 'remind me to call John at 3 PM' extracts the action (remind), target (John), and time (3 PM), passing them to a reminder skill. This enables users to trigger complex workflows through natural language without explicit API calls or structured input.","intents":["I want to automate repetitive tasks by speaking natural commands","I need to extract structured data (names, times, quantities) from voice input to pass to backend systems","I want to chain multiple skills together based on a single user utterance"],"best_for":["developers building voice-driven automation for productivity apps","teams creating smart home or IoT control interfaces","solo developers wanting to add voice control to existing applications"],"limitations":["Parameter extraction is regex/pattern-based, not semantic — fails on paraphrasing or complex sentence structures","No built-in entity recognition or named entity linking — requires manual regex patterns per parameter type","No multi-turn dialogue or context carryover — each utterance is processed independently","Skill chaining is not supported natively — requires explicit skill-to-skill invocation in code"],"requires":["Skill definitions with parameter schemas and extraction patterns","STT output (transcribed text from speech input)","Python 3.7+ or Node.js 14+ for skill execution","Optional: external APIs or databases for skill actions (e.g., calendar API for reminders)"],"input_types":["user utterance (text or transcribed speech)","skill manifest with parameter extraction patterns","optional context (previous utterances, user profile, system state)"],"output_types":["extracted parameters (structured object)","skill execution result (success/failure, response text)","side effects (API calls, file operations, system commands)"],"categories":["planning-reasoning","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github-leon-ai--leon__cap_5","uri":"capability://automation.workflow.cross.platform.local.agent.deployment.with.node.js.and.python","name":"cross-platform local agent deployment with node.js and python","description":"Leon runs as a standalone agent on Windows, macOS, and Linux using Node.js as the core runtime, with Python support for skill execution. The agent loads skills dynamically from a skills directory, manages audio I/O through system APIs, and exposes a local HTTP API for programmatic control. Users can deploy Leon on personal computers, Raspberry Pi, or lightweight servers without cloud infrastructure, maintaining full control over data and execution.","intents":["I want to run a personal assistant on my local machine without cloud dependencies","I need to deploy an AI agent on resource-constrained hardware like Raspberry Pi","I want to integrate a voice assistant into my existing local application stack"],"best_for":["privacy-conscious users building personal automation","developers deploying edge AI agents in IoT or smart home contexts","teams with strict data residency requirements or offline-first architectures"],"limitations":["No built-in clustering or horizontal scaling — single-instance deployment only","Skill execution is single-threaded; long-running skills block other requests","No persistent state management — requires external database for skill state (reminders, user preferences, etc.)","Audio I/O is system-dependent; cross-platform compatibility requires testing on each OS"],"requires":["Node.js 14+ (core runtime)","Python 3.7+ (for Python-based skills)","System audio input/output (microphone and speakers)","Disk space for skill modules and TTS/STT models (~500MB-2GB depending on backend choices)"],"input_types":["voice input (microphone audio)","text input (via CLI or HTTP API)","HTTP requests (for programmatic skill invocation)"],"output_types":["voice output (synthesized speech to speakers)","text responses (via CLI or HTTP API)","skill side effects (file operations, API calls, system commands)"],"categories":["automation-workflow","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github-leon-ai--leon__cap_6","uri":"capability://tool.use.integration.http.api.for.programmatic.agent.control.and.skill.invocation","name":"http api for programmatic agent control and skill invocation","description":"Leon exposes a local HTTP API that allows external applications to trigger skills, query agent status, and manage configuration without using voice. Developers can POST requests with intent names and parameters to invoke skills, GET agent state, or configure TTS/STT backends. This enables integration with web frontends, mobile apps, or other services that need to control the assistant programmatically.","intents":["I want to control Leon from a web UI or mobile app without voice input","I need to integrate Leon's skills into my existing application via HTTP","I want to build a custom frontend for my voice assistant"],"best_for":["developers building multi-interface assistants (voice + web + mobile)","teams integrating Leon into larger application ecosystems","solo developers prototyping voice assistant UIs"],"limitations":["No built-in authentication or authorization — requires external reverse proxy or firewall for security","API is synchronous; long-running skills block HTTP responses","No API versioning or backwards compatibility guarantees — breaking changes possible between releases","Limited to local network by default; exposing to internet requires manual TLS/reverse proxy setup"],"requires":["Node.js 14+ (for HTTP server)","Network access to Leon's host machine (localhost or LAN)","HTTP client library (curl, fetch, axios, etc.)","Knowledge of skill names and parameter schemas"],"input_types":["HTTP POST with JSON body (intent name, parameters)","HTTP GET for status queries","HTTP PUT/PATCH for configuration changes"],"output_types":["JSON response (skill result, status, error)","HTTP status codes (200, 400, 500, etc.)","side effects (skill execution, TTS output)"],"categories":["tool-use-integration","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github-leon-ai--leon__cap_7","uri":"capability://automation.workflow.configuration.driven.backend.selection.for.tts.and.stt","name":"configuration-driven backend selection for tts and stt","description":"Leon uses environment variables and config files (JSON or YAML) to specify which TTS and STT backends to use, API credentials, language preferences, and voice selections. Users can switch from offline (eSpeak, PocketSphinx) to cloud (Google, Azure, Deepgram) backends by editing config without code changes. This enables different deployment profiles: offline-first for privacy, cloud-based for accuracy, or hybrid for flexibility.","intents":["I want to choose between offline and cloud TTS/STT without modifying code","I need to deploy Leon in different environments with different backend preferences","I want to manage API credentials and language settings centrally"],"best_for":["DevOps teams managing multiple Leon deployments","developers testing different TTS/STT backends for performance/quality tradeoffs","teams with environment-specific requirements (offline in production, cloud in dev)"],"limitations":["No runtime backend switching — requires restart to apply config changes","Credentials stored in plaintext config files or environment variables — requires external secret management for production","No validation of config values — invalid backend names or credentials fail silently at runtime","Limited to predefined backends; adding new TTS/STT providers requires code changes"],"requires":["Node.js 14+ (for config loading)","Config file (JSON/YAML) or environment variables","API credentials for cloud backends (if using cloud TTS/STT)","Offline TTS/STT engines installed (if using offline mode)"],"input_types":["config file (JSON or YAML)","environment variables (LEON_TTS_BACKEND, LEON_STT_BACKEND, etc.)","API credentials (API keys, service account files)"],"output_types":["loaded configuration object","backend initialization status","error messages if config is invalid"],"categories":["automation-workflow","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github-leon-ai--leon__cap_8","uri":"capability://automation.workflow.skill.lifecycle.management.with.hot.reload.capability","name":"skill lifecycle management with hot-reload capability","description":"Leon monitors the skills directory for new, updated, or deleted skill files and dynamically loads/unloads them without restarting the agent. Each skill is loaded as an isolated module with its own execution context, allowing developers to iterate on skills rapidly. The skill loader validates skill manifests (trigger phrases, parameters, description) and registers them with the intent router, enabling new capabilities to be added at runtime.","intents":["I want to add new skills to Leon without restarting the agent","I need to update a skill's logic and test it immediately","I want to disable or remove skills without downtime"],"best_for":["developers iterating on skill implementations","teams managing large skill libraries with frequent updates","open-source communities contributing skills without coordination"],"limitations":["Hot-reload can cause race conditions if skills are invoked during reload — no transactional skill updates","Skill isolation is filesystem-based, not sandboxed — malicious skills can access other skills' data or crash the agent","No skill versioning or rollback — old versions are overwritten immediately","Manifest validation is basic — invalid skills may load partially and fail at runtime"],"requires":["Node.js 14+ with file system watch capability","Skill files in the designated skills directory","Skill manifest (JSON or YAML) with required metadata","Write permissions to skills directory for dynamic loading"],"input_types":["skill file (Python or JavaScript module)","skill manifest (JSON or YAML with trigger phrases, parameters)","file system events (create, update, delete)"],"output_types":["skill registration confirmation","error messages if manifest is invalid","list of loaded skills and their trigger phrases"],"categories":["automation-workflow","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github-leon-ai--leon__cap_9","uri":"capability://text.generation.language.multi.language.support.with.language.specific.skill.variants","name":"multi-language support with language-specific skill variants","description":"Leon supports multiple languages by allowing skills to define language-specific trigger phrases and responses. When a user speaks in a particular language (detected via STT language setting), Leon routes to language-specific skill variants if available, falling back to default language if not. This enables building multilingual assistants where skills can respond in the user's language without requiring separate agent instances.","intents":["I want to build a multilingual voice assistant that responds in the user's language","I need to support regional variants (e.g., en-US vs. en-GB) with different trigger phrases","I want to gradually add language support to my assistant without rewriting skills"],"best_for":["developers building assistants for international audiences","teams supporting multiple languages in a single deployment","open-source projects wanting community translations"],"limitations":["Language detection relies on STT backend language setting — no automatic language detection from speech","Skill authors must manually define trigger phrases and responses for each language — no automatic translation","No built-in translation API integration — requires manual translation or external service","Fallback behavior is not configurable — defaults to primary language if variant not found"],"requires":["Skill manifests with language-specific trigger phrases (e.g., 'en', 'fr', 'es')","STT backend supporting multiple languages","TTS backend supporting multiple languages and voices","Skill authors providing translations for each supported language"],"input_types":["language code (e.g., 'en-US', 'fr-FR')","user utterance in target language","skill manifest with language variants"],"output_types":["skill response in user's language","synthesized speech in user's language","fallback response if language variant not available"],"categories":["text-generation-language","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0}],"trust":{"score":48,"verified":false,"data_access_risk":"high","permissions":["Node.js 14+ for core agent runtime","Python 3.7+ for skill execution (many skills written in Python)","PocketSphinx or compatible offline STT engine, OR API credentials for cloud STT (Google Cloud Speech, Azure, etc.)","System audio input/output capabilities (microphone + speakers or headset)","Node.js 14+ for skill loader and router","Python 3.7+ for Python-based skills (or Node.js for JavaScript skills)","Skill template/boilerplate (provided in docs) to define intent metadata","File system write access to skills directory for dynamic skill loading","Node.js 14+ with child_process module","System shell (bash, PowerShell, cmd.exe) available"],"failure_modes":["Offline STT accuracy is lower than cloud-based alternatives (Sphinx ~70-80% vs Google Cloud ~95%+)","Skill matching relies on exact phrase or fuzzy string matching, not semantic understanding — requires explicit intent definition","No built-in multi-language support for offline mode; cloud backends add latency and dependency","Audio processing pipeline adds ~500-1500ms latency depending on STT backend choice","Intent matching is deterministic and phrase-based, not semantic — ambiguous utterances may route to wrong skill or fail silently","No built-in skill versioning or dependency management — breaking changes in core API can orphan community skills","Skill isolation is filesystem-based, not sandboxed — malicious or buggy skills can crash the entire agent or access sensitive data","Parameter extraction relies on regex/positional parsing, not structured NLU — complex multi-parameter intents require manual parsing in skill code","Command execution is not sandboxed — malicious or buggy skills can damage the system or access sensitive data","No built-in command whitelisting or permission control — any skill can execute any command","builder identity is not verified yet","no observed match outcomes yet"],"rank_breakdown":{"adoption":0.7110668864552716,"quality":0.34,"ecosystem":0.6000000000000001,"match_graph":0.25,"freshness":0.75,"weights":{"adoption":0.25,"quality":0.25,"ecosystem":0.1,"match_graph":0.28,"freshness":0.12}},"observed_outcomes":{"matches":0,"success_rate":0,"avg_confidence":0,"top_intents":[],"last_matched_at":null},"maintenance":{"status":"active","updated_at":"2026-05-24T12:16:21.550Z","last_scraped_at":"2026-05-03T13:57:04.027Z","last_commit":"2026-05-03T13:05:21Z"},"community":{"stars":17206,"forks":1440,"weekly_downloads":null,"model_downloads":null,"model_likes":null}},"distribution":{"claim_url":"https://unfragile.ai/submit?claim=leon-ai--leon","compare_url":"https://unfragile.ai/compare?artifact=leon-ai--leon"}},"signature":"KGLvwMbS2GgBL+ix5JgW9y/owEQ5lM0pMmQzN3v/Lq/t3SNvpnbZEG9VAthgkdUCjuBQMuf83qscwkgkX3ctAA==","signedAt":"2026-06-22T00:15:46.052Z","signedBy":"unfragile.ai","version":1},"_links":{"self":"https://unfragile.ai/api/v1/passport/leon-ai--leon","artifact":"https://unfragile.ai/leon-ai--leon","verify":"https://unfragile.ai/api/v1/verify?slug=leon-ai--leon","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"}}