{"passport":{"unfragile":{"@version":"1.0","version":"2026-05","artifact":{"id":"tool_open-voice-os","slug":"open-voice-os","name":"Open Voice OS","type":"repo","url":"https://openvoiceos.com","page_url":"https://unfragile.ai/open-voice-os","categories":["voice-audio"],"tags":[],"pricing":{"model":"free","free":true,"starting_price":null},"status":"active","verified":false},"capabilities":[{"id":"tool_open-voice-os__cap_0","uri":"capability://tool.use.integration.modular.skill.based.voice.command.execution","name":"modular skill-based voice command execution","description":"Executes user voice commands through a pluggable skill framework inherited from Mycroft-core, where each skill is an independent Python module that registers command patterns and handlers. Skills are loaded at runtime and can be enabled/disabled without restarting the core engine, allowing developers to extend functionality by creating new skills that follow Mycroft skill conventions. The skill system maintains backward compatibility with the Mycroft ecosystem while supporting OVOS-specific enhancements.","intents":["I want to add custom voice commands without modifying the core voice assistant","I need to create domain-specific voice interfaces for my application or device","I want to reuse existing Mycroft skills in my privacy-focused voice deployment"],"best_for":["developers building custom voice-controlled IoT devices","teams creating embedded voice assistants for specific workflows","open-source contributors extending the Mycroft ecosystem"],"limitations":["Skill ecosystem is significantly smaller than Alexa or Google Assistant, limiting pre-built integrations","Skill development documentation is incomplete; developers must reference Mycroft-core patterns","No built-in skill marketplace or centralized discovery mechanism","Skill isolation is process-level only; no sandboxing prevents malicious skills from accessing system resources"],"requires":["Python 3.7+","ovos-core installed and running","Understanding of Mycroft skill development conventions","Linux-based operating system"],"input_types":["voice audio (processed to text via STT)","text commands via CLI","structured intent data from NLP pipeline"],"output_types":["voice response (via TTS)","text output to CLI","device control signals","structured data to other skills"],"categories":["tool-use-integration","voice-assistant-framework"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_open-voice-os__cap_1","uri":"capability://tool.use.integration.pluggable.speech.to.text.engine.abstraction","name":"pluggable speech-to-text engine abstraction","description":"Provides a configurable STT backend abstraction layer that allows swapping between different speech recognition engines without modifying core voice processing logic. Supports both cloud-based STT (default, requires internet) and self-hosted offline alternatives, with configuration managed through a central settings file. The abstraction handles audio stream routing, engine initialization, and result normalization across heterogeneous STT implementations.","intents":["I want to use offline speech recognition to keep voice data private","I need to switch STT providers without rebuilding the voice assistant","I want to use a specific STT engine optimized for my language or domain"],"best_for":["privacy-conscious developers requiring on-device speech recognition","teams deploying voice assistants in air-gapped or low-connectivity environments","builders optimizing for specific languages or acoustic domains"],"limitations":["Default STT configuration requires internet connectivity; offline setup requires manual configuration of self-hosted engines","Offline STT engine performance and accuracy metrics are not documented","No built-in fallback mechanism if primary STT engine fails","Audio codec support and quality constraints are undocumented","Latency overhead of STT abstraction layer is not quantified"],"requires":["Linux-based OS","Python 3.7+","Internet connection (for default cloud STT) OR self-hosted STT engine (e.g., Vosk, Coqui STT)","Audio input device (microphone)"],"input_types":["raw audio stream (WAV, PCM formats assumed)","configuration file (YAML or JSON format)"],"output_types":["recognized text string","confidence score","structured intent data"],"categories":["tool-use-integration","audio-processing"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_open-voice-os__cap_10","uri":"capability://tool.use.integration.open.source.codebase.with.community.driven.development","name":"open-source codebase with community-driven development","description":"Entire OVOS codebase is open-source under Apache License 2.0, allowing independent security audits, community contributions, and local modifications without vendor restrictions. Developers can inspect implementation details, identify security issues, and contribute improvements directly. The project is maintained by a distributed community of developers rather than a single corporation, enabling transparent development and community governance.","intents":["I want to audit the security of my voice assistant","I need to modify the voice assistant for my specific use case","I want to contribute improvements to the voice assistant project"],"best_for":["security-conscious organizations requiring code audits","developers building custom voice assistants with specific requirements","open-source contributors and community members"],"limitations":["Smaller development team and community than commercial alternatives means slower bug fixes","No guaranteed SLA or support contract","Code quality and documentation vary across modules","Community contributions may introduce security or stability issues","No formal security audit or certification","Maintenance burden falls on community; critical bugs may not be fixed quickly"],"requires":["Git and GitHub account for contributions","Understanding of Python and voice assistant architecture","Familiarity with Apache License 2.0 terms"],"input_types":["source code repository","issue reports and feature requests","pull requests with code changes"],"output_types":["auditable source code","community-driven improvements","local modifications and customizations"],"categories":["tool-use-integration","safety-moderation"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_open-voice-os__cap_11","uri":"capability://tool.use.integration.configurable.voice.recognition.and.command.structure.customization","name":"configurable voice recognition and command structure customization","description":"Allows developers to customize voice recognition patterns, command structures, and skill behavior through configuration files and skill development. Skills can define custom utterance patterns, entity extraction rules, and response templates, enabling power users to tailor the assistant to specific workflows and vocabularies. Configuration is typically YAML or JSON-based, allowing non-programmers to modify behavior without code changes.","intents":["I want to add custom voice commands specific to my domain or workflow","I need to recognize domain-specific terminology or jargon","I want to customize the assistant's behavior without modifying core code"],"best_for":["power users and developers building domain-specific voice interfaces","teams with specialized vocabularies or command structures","organizations customizing voice assistants for specific workflows"],"limitations":["Customization scope and capabilities are undocumented","Configuration file format and schema are undocumented","No GUI for configuration; requires manual file editing","Complex customizations require skill development (Python coding)","No validation or testing tools for custom configurations","Limited documentation on customization best practices"],"requires":["Text editor for configuration files","Understanding of YAML or JSON (assumed)","Knowledge of skill development for complex customizations","Python 3.7+ for skill development"],"input_types":["configuration files (YAML or JSON format assumed)","skill code with custom utterance patterns","entity extraction rules"],"output_types":["customized voice command recognition","domain-specific skill behavior","tailored assistant responses"],"categories":["tool-use-integration","planning-reasoning"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_open-voice-os__cap_2","uri":"capability://tool.use.integration.pluggable.text.to.speech.engine.abstraction","name":"pluggable text-to-speech engine abstraction","description":"Provides a configurable TTS backend abstraction that allows swapping between different text-to-speech engines (cloud-based or local) without modifying core voice synthesis logic. Handles voice selection, speech rate/pitch configuration, and audio output routing across heterogeneous TTS implementations. Configuration is centralized, enabling runtime switching between TTS providers.","intents":["I want to use offline text-to-speech to avoid sending data to cloud services","I need to select specific voices or languages for my voice assistant","I want to switch TTS providers based on quality, latency, or cost requirements"],"best_for":["developers building privacy-first voice assistants","teams requiring specific voice characteristics or language support","builders optimizing for latency in real-time voice interactions"],"limitations":["Offline TTS voice quality is significantly lower than cloud alternatives","Limited voice selection and language coverage in offline TTS engines","No documented latency profiles for different TTS backends","No built-in voice caching or pre-synthesis optimization","Audio output format constraints are undocumented"],"requires":["Linux-based OS","Python 3.7+","Audio output device (speaker or headphones)","TTS engine (cloud API key OR local TTS engine like eSpeak, Piper)"],"input_types":["text string to synthesize","configuration file (YAML or JSON)","voice/language selection parameters"],"output_types":["audio stream (WAV, PCM formats assumed)","audio file saved to disk"],"categories":["tool-use-integration","audio-processing"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_open-voice-os__cap_3","uri":"capability://planning.reasoning.natural.language.intent.recognition.and.parsing","name":"natural language intent recognition and parsing","description":"Processes recognized speech text through an NLP pipeline to extract user intent and entities, converting natural language utterances into structured intent objects that skills can handle. The NLP component is mentioned in architecture but implementation details are undocumented; it likely uses pattern matching or lightweight NLU models to classify utterances against registered skill intents. Intent results are passed to the skill execution layer for command dispatch.","intents":["I want to understand what the user is asking for from their voice input","I need to extract parameters (entities) from natural language commands","I want to handle variations of the same command (e.g., 'turn on the light' vs 'lights on')"],"best_for":["developers building voice interfaces with natural language understanding","teams requiring intent classification without external NLU services","builders optimizing for low-latency intent recognition on embedded devices"],"limitations":["NLP implementation details are undocumented; accuracy and approach are unknown","No documented support for complex multi-turn conversations or context tracking","Entity extraction capabilities and supported entity types are unknown","No quantified accuracy metrics or benchmark data","Likely limited to English or small set of languages","No built-in confidence scoring or fallback handling for ambiguous intents"],"requires":["Python 3.7+","ovos-core installed","Registered skills with intent patterns","Recognized text output from STT engine"],"input_types":["text string (from STT)","skill intent pattern definitions"],"output_types":["structured intent object (name, confidence, entities)","matched skill identifier","extracted parameters/entities"],"categories":["planning-reasoning","data-processing-analysis"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_open-voice-os__cap_4","uri":"capability://automation.workflow.headless.voice.assistant.deployment.with.optional.ui.layer","name":"headless voice assistant deployment with optional ui layer","description":"Supports deployment as a headless voice-only system (no display required) with optional graphical UI layer for touch-screen devices. The core voice engine runs independently of any UI, allowing deployment on Raspberry Pi, embedded systems, or server environments without display hardware. Optional UI components can be added for devices with screens, providing visual feedback and touch-based control alongside voice interaction.","intents":["I want to deploy a voice assistant on a Raspberry Pi or headless device","I need a voice assistant that works with or without a display","I want to add a touch screen interface to my voice assistant without rebuilding the core"],"best_for":["developers building IoT voice devices with minimal hardware requirements","teams deploying voice assistants in headless server environments","makers creating smart speakers or voice-controlled devices"],"limitations":["UI customization scope and capabilities are undocumented","No documented UI framework or technology stack","UI layer is optional and may lag behind core voice engine in features","Touch screen driver support is undocumented","No built-in multi-display or distributed UI support"],"requires":["Linux-based OS","Python 3.7+","Audio input/output devices","Optional: touch screen hardware and drivers"],"input_types":["voice audio","touch input (if UI enabled)","configuration files"],"output_types":["voice response","visual feedback on screen (if UI enabled)","device control signals"],"categories":["automation-workflow","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_open-voice-os__cap_5","uri":"capability://automation.workflow.containerized.deployment.via.docker","name":"containerized deployment via docker","description":"Provides Docker containerization for isolated, reproducible OVOS deployments without modifying host system dependencies. Developers can run OVOS in a Docker container with all dependencies pre-configured, enabling consistent behavior across development, testing, and production environments. The container approach abstracts away Linux distribution differences and simplifies multi-instance deployments.","intents":["I want to deploy OVOS in a containerized environment for consistency","I need to run multiple OVOS instances on the same host without dependency conflicts","I want to simplify OVOS deployment across different Linux distributions"],"best_for":["DevOps teams deploying OVOS at scale","developers testing OVOS without modifying host system","teams using Kubernetes or container orchestration platforms"],"limitations":["Audio input/output routing through Docker requires host device passthrough configuration","Container overhead adds latency to voice processing (quantified impact unknown)","Docker image size and build time are undocumented","No documented Kubernetes manifests or Helm charts","GPU acceleration support (if any) is undocumented"],"requires":["Docker runtime (version undocumented)","Linux host OS","Audio device access (requires --device flag or volume mount)","Sufficient disk space for Docker image"],"input_types":["Dockerfile or pre-built Docker image","environment variables for configuration","mounted volumes for persistent data"],"output_types":["running Docker container","voice assistant accessible via network or local audio"],"categories":["automation-workflow","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_open-voice-os__cap_6","uri":"capability://automation.workflow.prebuilt.linux.image.for.single.board.computers","name":"prebuilt linux image for single-board computers","description":"Provides stripped-down, pre-configured Linux images (e.g., for Raspberry Pi, Mycroft devices) with OVOS pre-installed and optimized for embedded hardware. Developers can flash the image to storage media and boot immediately without manual installation or configuration. The image includes minimal OS components to reduce resource consumption on low-spec hardware.","intents":["I want to quickly deploy OVOS on a Raspberry Pi without Linux administration","I need a minimal OS image optimized for voice assistant hardware","I want to avoid manual dependency installation and configuration"],"best_for":["makers and hobbyists building voice-controlled devices","developers prototyping voice assistants on Raspberry Pi","non-technical users deploying OVOS on embedded hardware"],"limitations":["Prebuilt image is 'stripped-down' by design, limiting additional software installation","Image customization requires rebuilding from source (process undocumented)","Supported hardware is limited (Raspberry Pi, Mycroft devices; others unknown)","Image update/upgrade path is undocumented","No documented image size or storage requirements","Minimal OS may lack tools for troubleshooting or advanced configuration"],"requires":["Compatible single-board computer (Raspberry Pi 3/4/5 or Mycroft device)","SD card or storage media (capacity undocumented)","Card flashing tool (Balena Etcher, dd, etc.)","Power supply and audio hardware"],"input_types":["prebuilt image file (.img or .zip)","storage media"],"output_types":["bootable device with OVOS running","voice assistant ready for use"],"categories":["automation-workflow","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_open-voice-os__cap_7","uri":"capability://tool.use.integration.command.line.interface.for.skill.invocation.and.testing","name":"command-line interface for skill invocation and testing","description":"Exposes voice assistant functionality via command-line interface, allowing developers and users to invoke skills and test voice commands without audio input. The CLI provides direct access to skill execution, enabling scripted testing, automation, and integration with other command-line tools. Developers can test skills and voice logic without requiring microphone input or TTS output.","intents":["I want to test voice skills without audio hardware","I need to invoke voice commands programmatically from scripts or automation","I want to debug skill behavior without running the full voice pipeline"],"best_for":["developers testing and debugging voice skills","CI/CD pipelines automating skill testing","teams integrating OVOS with command-line automation tools"],"limitations":["CLI syntax and available commands are undocumented","No documented support for complex multi-turn interactions via CLI","CLI output format is undocumented (JSON, text, structured data unknown)","No built-in logging or debugging output control","Limited to text-based interaction; no audio feedback via CLI"],"requires":["Linux shell environment","ovos-core installed and running","Skill to invoke registered in the system"],"input_types":["command-line arguments","text input (simulating voice utterance)"],"output_types":["text response from skill","exit code indicating success/failure","structured data (format unknown)"],"categories":["tool-use-integration","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_open-voice-os__cap_8","uri":"capability://tool.use.integration.mycroft.skill.ecosystem.compatibility.and.reuse","name":"mycroft skill ecosystem compatibility and reuse","description":"Maintains backward compatibility with Mycroft-core skill protocol, allowing developers to use existing Mycroft skills in OVOS deployments without modification. OVOS is positioned as 'Mycroft Community Edition' with fork compatibility, enabling the skill ecosystem to be shared between projects. Developers can leverage thousands of existing Mycroft skills while benefiting from OVOS-specific enhancements.","intents":["I want to use existing Mycroft skills in my OVOS deployment","I need to leverage the Mycroft skill ecosystem without vendor lock-in","I want to contribute skills that work in both Mycroft and OVOS"],"best_for":["developers migrating from Mycroft to OVOS","teams leveraging existing Mycroft skill investments","open-source contributors maintaining compatibility across projects"],"limitations":["Skill compatibility is maintained at fork level; divergence may break compatibility over time","OVOS-specific features may not be available in Mycroft skills","Skill quality and maintenance varies widely across the Mycroft ecosystem","No centralized skill marketplace or discovery mechanism","Skill documentation quality is inconsistent"],"requires":["Mycroft skill (compatible with Mycroft-core dev branch)","ovos-core installed","Python 3.7+"],"input_types":["Mycroft skill code","skill manifest/metadata"],"output_types":["skill functionality integrated into OVOS","voice commands handled by skill"],"categories":["tool-use-integration","memory-knowledge"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_open-voice-os__cap_9","uri":"capability://safety.moderation.privacy.preserving.local.voice.processing.without.cloud.dependency","name":"privacy-preserving local voice processing without cloud dependency","description":"Processes voice input entirely on local hardware without sending audio or transcripts to cloud services by default. Supports offline STT and TTS engines, enabling complete voice assistant functionality without internet connectivity or external API calls. This architecture ensures voice data never leaves the user's device, providing strong privacy guarantees compared to cloud-based assistants.","intents":["I want to ensure voice data never leaves my device","I need a voice assistant that works without internet connectivity","I want to avoid corporate surveillance and data collection from voice interactions"],"best_for":["privacy-conscious developers and users","organizations with strict data residency requirements","teams deploying voice assistants in air-gapped or low-connectivity environments"],"limitations":["Offline STT and TTS accuracy is significantly lower than cloud alternatives","Language and voice selection is limited in offline engines","Setup requires manual configuration of offline backends (not default)","Default STT configuration still requires internet; privacy requires explicit configuration","No documented security audit or privacy certification","Skills may still make external API calls if not carefully vetted"],"requires":["Linux-based OS","Python 3.7+","Self-hosted STT engine (Vosk, Coqui STT, etc.) for offline operation","Self-hosted TTS engine (eSpeak, Piper, etc.) for offline operation","Audio input/output devices"],"input_types":["voice audio","configuration for offline backends"],"output_types":["voice response","device control signals"],"categories":["safety-moderation","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0}],"trust":{"score":36,"verified":false,"data_access_risk":"high","permissions":["Python 3.7+","ovos-core installed and running","Understanding of Mycroft skill development conventions","Linux-based operating system","Linux-based OS","Internet connection (for default cloud STT) OR self-hosted STT engine (e.g., Vosk, Coqui STT)","Audio input device (microphone)","Git and GitHub account for contributions","Understanding of Python and voice assistant architecture","Familiarity with Apache License 2.0 terms"],"failure_modes":["Skill ecosystem is significantly smaller than Alexa or Google Assistant, limiting pre-built integrations","Skill development documentation is incomplete; developers must reference Mycroft-core patterns","No built-in skill marketplace or centralized discovery mechanism","Skill isolation is process-level only; no sandboxing prevents malicious skills from accessing system resources","Default STT configuration requires internet connectivity; offline setup requires manual configuration of self-hosted engines","Offline STT engine performance and accuracy metrics are not documented","No built-in fallback mechanism if primary STT engine fails","Audio codec support and quality constraints are undocumented","Latency overhead of STT abstraction layer is not quantified","Smaller development team and community than commercial alternatives means slower bug fixes","builder identity is not verified yet","no observed match outcomes yet"],"rank_breakdown":{"adoption":0.2833333333333333,"quality":0.6799999999999999,"ecosystem":0.15000000000000002,"match_graph":0.25,"freshness":0.75,"weights":{"adoption":0.3,"quality":0.2,"ecosystem":0.15,"match_graph":0.3,"freshness":0.05}},"observed_outcomes":{"matches":0,"success_rate":0,"avg_confidence":0,"top_intents":[],"last_matched_at":null},"maintenance":{"status":"active","updated_at":"2026-05-24T12:16:31.859Z","last_scraped_at":"2026-04-05T13:23:42.562Z","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=open-voice-os","compare_url":"https://unfragile.ai/compare?artifact=open-voice-os"}},"signature":"KgQF79UGpbacAKunMaECPeIs8zfM4dbyMFePCxoB9lGE5AkmOZ4STMwwQV5wvuFfTw81oRnMo3bC7i3c0jRxCA==","signedAt":"2026-06-22T13:26:49.971Z","signedBy":"unfragile.ai","version":1},"_links":{"self":"https://unfragile.ai/api/v1/passport/open-voice-os","artifact":"https://unfragile.ai/open-voice-os","verify":"https://unfragile.ai/api/v1/verify?slug=open-voice-os","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"}}