{"passport":{"unfragile":{"@version":"1.0","version":"2026-05","artifact":{"id":"openrouter-x-ai-grok-3","slug":"x-ai-grok-3","name":"xAI: Grok 3","type":"model","url":"https://openrouter.ai/models/x-ai~grok-3","page_url":"https://unfragile.ai/x-ai-grok-3","categories":["chatbots-assistants"],"tags":["x-ai","api-access","text"],"pricing":{"model":"paid","free":false,"starting_price":"$3.00e-6 per prompt token"},"status":"active","verified":false},"capabilities":[{"id":"openrouter-x-ai-grok-3__cap_0","uri":"capability://code.generation.editing.enterprise.grade.code.generation.and.completion","name":"enterprise-grade code generation and completion","description":"Generates production-ready code across multiple programming languages using transformer-based sequence-to-sequence architecture trained on large-scale code corpora. Supports context-aware completion by analyzing surrounding code structure, imports, and function signatures to produce syntactically and semantically correct implementations. Integrates via REST API endpoints supporting streaming responses for real-time IDE integration.","intents":["Generate boilerplate code and scaffolding for new projects or modules","Complete partial function implementations with domain-specific logic","Refactor existing code snippets to follow best practices","Generate unit tests and test fixtures for existing functions"],"best_for":["Enterprise development teams building production systems","Solo developers accelerating feature implementation","Teams migrating legacy codebases to modern frameworks"],"limitations":["Context window limitations may truncate large files; requires strategic code selection for multi-file refactoring","Generated code quality varies by language; less reliable for niche or domain-specific languages","No built-in IDE plugin; requires custom integration via OpenRouter API","Streaming responses add latency overhead compared to batch processing"],"requires":["OpenRouter API key with xAI Grok 3 access","HTTP/2 capable client for streaming support","Minimum context window of 8K tokens for typical code files"],"input_types":["code snippets","natural language descriptions","partial function signatures","code comments with intent"],"output_types":["complete code implementations","code suggestions with multiple variants","refactored code with explanations","test code and fixtures"],"categories":["code-generation-editing","developer-tools"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"openrouter-x-ai-grok-3__cap_1","uri":"capability://data.processing.analysis.structured.data.extraction.from.unstructured.text","name":"structured data extraction from unstructured text","description":"Extracts and transforms unstructured text into structured formats (JSON, CSV, XML) using instruction-following capabilities and in-context learning. Leverages attention mechanisms to identify relevant entities, relationships, and hierarchies within documents, then formats output according to user-specified schemas. Supports schema validation and error correction through multi-turn conversation patterns.","intents":["Extract invoice line items, amounts, and dates from PDF text","Parse customer feedback into structured sentiment and category tags","Convert natural language requirements into structured API specifications","Extract entities and relationships from legal documents or contracts"],"best_for":["Data engineering teams building ETL pipelines","Business analysts automating document processing","Compliance teams extracting structured data from regulatory documents","Product teams converting unstructured feedback into analytics"],"limitations":["Accuracy degrades with highly ambiguous or malformed source text; no built-in confidence scoring","Schema complexity is limited by context window; deeply nested structures may require decomposition","No native support for image-based documents; requires OCR preprocessing","Extraction quality varies significantly by domain; requires validation layer for production use"],"requires":["OpenRouter API key with xAI Grok 3 access","JSON schema definition or format specification","Text input preprocessed to remove binary/encoding artifacts","Validation framework for output quality assurance"],"input_types":["unstructured text","semi-structured documents","natural language descriptions","JSON schema specifications"],"output_types":["JSON objects","CSV rows","XML documents","structured key-value pairs"],"categories":["data-processing-analysis","text-generation-language"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"openrouter-x-ai-grok-3__cap_10","uri":"capability://code.generation.editing.code.review.and.quality.analysis","name":"code review and quality analysis","description":"Analyzes code for quality issues, security vulnerabilities, performance problems, and style violations using static analysis patterns combined with semantic understanding. Identifies issues across multiple dimensions (security, performance, maintainability, style) and provides specific, actionable recommendations with code examples. Supports multiple programming languages and frameworks with language-specific analysis rules.","intents":["Identify security vulnerabilities and potential exploits in code","Detect performance bottlenecks and optimization opportunities","Enforce coding standards and style consistency","Suggest architectural improvements and refactoring opportunities"],"best_for":["Development teams implementing code review automation","Security teams scanning codebases for vulnerabilities","Technical leads enforcing code quality standards","CI/CD pipelines integrating automated code analysis"],"limitations":["Analysis is heuristic-based; may produce false positives or miss subtle issues","Security analysis is not a substitute for professional security audits","Performance recommendations are generic; require profiling validation","Language-specific analysis quality varies; less reliable for niche languages"],"requires":["OpenRouter API key with xAI Grok 3 access","Source code files or snippets","Optional: language specification and framework context","Optional: custom linting rules or style guides"],"input_types":["source code files","code snippets","pull request diffs","entire codebases"],"output_types":["issue lists with severity levels","code suggestions and fixes","refactoring recommendations","security vulnerability reports","performance analysis"],"categories":["code-generation-editing","safety-moderation"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"openrouter-x-ai-grok-3__cap_11","uri":"capability://planning.reasoning.logical.reasoning.and.problem.decomposition","name":"logical reasoning and problem decomposition","description":"Breaks down complex problems into logical steps and performs multi-step reasoning using chain-of-thought patterns and tree-of-thought exploration. Implements explicit reasoning traces that show intermediate steps, allowing users to follow and validate reasoning logic. Supports both linear reasoning chains and branching exploration of alternative solution paths.","intents":["Solve complex math problems with step-by-step reasoning","Debug code issues through systematic problem decomposition","Analyze business problems and develop solution strategies","Validate reasoning logic and identify logical fallacies"],"best_for":["Educators using AI for tutoring and explanation","Developers debugging complex system issues","Analysts solving business problems systematically","Researchers validating logical arguments"],"limitations":["Reasoning traces may contain logical errors; not suitable for formal proof verification","Complex reasoning chains may exceed context window limits","Reasoning quality varies by problem domain; less reliable for novel or ambiguous problems","No built-in validation of reasoning correctness; requires expert review"],"requires":["OpenRouter API key with xAI Grok 3 access","Clear problem statement or question","Optional: domain context or constraints","Optional: reasoning style preferences (linear vs. exploratory)"],"input_types":["complex problems or questions","code debugging scenarios","business analysis requests","logical reasoning challenges"],"output_types":["step-by-step reasoning traces","solution paths with alternatives","logical argument structures","problem decompositions","validation of reasoning"],"categories":["planning-reasoning","text-generation-language"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"openrouter-x-ai-grok-3__cap_2","uri":"capability://text.generation.language.multi.turn.conversational.reasoning.with.context.retention","name":"multi-turn conversational reasoning with context retention","description":"Maintains conversation state across multiple turns using transformer-based attention mechanisms that track user intent, previous responses, and contextual constraints. Implements sliding-window context management to balance memory retention with token efficiency, allowing users to reference earlier statements and build on previous reasoning without explicit context reinjection. Supports both stateless API calls and stateful session management patterns.","intents":["Debug code issues through iterative back-and-forth dialogue","Refine requirements through multi-turn clarification conversations","Build complex reasoning chains where each response builds on prior analysis","Maintain context across long customer support conversations"],"best_for":["Developers building conversational AI agents","Customer support teams deploying chatbots","Product teams prototyping interactive experiences","Researchers exploring multi-turn reasoning capabilities"],"limitations":["Context window limitations require explicit conversation pruning for sessions exceeding ~50K tokens","No built-in persistence; conversation state must be managed externally via database or session store","Attention mechanisms may lose fine-grained details from early conversation turns in very long sessions","Stateless API design requires client-side responsibility for context management"],"requires":["OpenRouter API key with xAI Grok 3 access","Client-side conversation history management (array of message objects)","Session storage mechanism for multi-session persistence","Message format compliance with OpenAI-compatible chat API schema"],"input_types":["natural language text","code snippets in conversation context","structured data references","follow-up questions and clarifications"],"output_types":["natural language responses","code suggestions with explanations","structured analysis and recommendations","clarifying questions"],"categories":["text-generation-language","planning-reasoning"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"openrouter-x-ai-grok-3__cap_3","uri":"capability://code.generation.editing.technical.documentation.and.api.specification.generation","name":"technical documentation and api specification generation","description":"Generates comprehensive technical documentation, API specifications, and architectural diagrams from code, requirements, or natural language descriptions. Uses code analysis patterns to extract function signatures, parameters, and return types, then synthesizes documentation in multiple formats (Markdown, OpenAPI/Swagger, Docstring conventions). Supports both forward documentation (code-to-docs) and reverse documentation (requirements-to-code-spec) workflows.","intents":["Generate OpenAPI/Swagger specifications from existing REST API code","Create comprehensive README and API documentation from codebase","Generate docstrings and inline comments for undocumented legacy code","Create architecture decision records and design documentation from requirements"],"best_for":["Development teams improving documentation practices","API teams automating specification generation","Technical writers accelerating documentation workflows","Open-source maintainers scaling documentation efforts"],"limitations":["Generated documentation requires human review for accuracy; no built-in validation against actual code behavior","Complex architectural patterns may be oversimplified in generated diagrams","Docstring generation varies in quality by language; less reliable for dynamically-typed languages","No support for generating interactive documentation or live examples"],"requires":["OpenRouter API key with xAI Grok 3 access","Source code or requirements document as input","Target documentation format specification (Markdown, OpenAPI, etc.)","Optional: existing documentation fragments for style consistency"],"input_types":["source code files","function signatures","requirements documents","natural language descriptions","existing documentation samples"],"output_types":["Markdown documentation","OpenAPI/Swagger specifications","Docstrings and inline comments","Architecture diagrams (text-based)","API reference tables"],"categories":["code-generation-editing","text-generation-language"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"openrouter-x-ai-grok-3__cap_4","uri":"capability://text.generation.language.text.summarization.with.configurable.abstraction.levels","name":"text summarization with configurable abstraction levels","description":"Condenses long-form text into summaries of variable length and abstraction using extractive and abstractive summarization techniques. Implements hierarchical attention mechanisms to identify key concepts and relationships, then generates summaries at user-specified levels (executive summary, detailed summary, bullet points). Supports domain-specific summarization for technical documents, legal contracts, and business reports.","intents":["Summarize lengthy research papers or technical documentation into key takeaways","Create executive summaries of business reports and meeting notes","Generate bullet-point summaries of customer feedback or support tickets","Condense legal documents or contracts into plain-language summaries"],"best_for":["Knowledge workers processing large volumes of documents","Legal and compliance teams reviewing contracts","Research teams synthesizing literature reviews","Product teams analyzing customer feedback at scale"],"limitations":["Summarization quality degrades with highly technical or domain-specific jargon without context","May lose nuance or important caveats in aggressive compression ratios","No built-in fact-checking; summaries may contain hallucinations or misinterpretations","Context window limits summarization of documents exceeding ~100K tokens"],"requires":["OpenRouter API key with xAI Grok 3 access","Text input with clear structure (paragraphs, sections)","Target summary length or compression ratio specification","Optional: domain context or terminology glossary for specialized documents"],"input_types":["long-form text documents","research papers","meeting transcripts","legal documents","customer feedback collections"],"output_types":["executive summaries","bullet-point summaries","detailed summaries","key takeaways lists","structured summary objects"],"categories":["text-generation-language","data-processing-analysis"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"openrouter-x-ai-grok-3__cap_5","uri":"capability://text.generation.language.domain.specific.knowledge.application.and.reasoning","name":"domain-specific knowledge application and reasoning","description":"Applies deep domain knowledge across finance, healthcare, legal, and technology sectors to provide specialized reasoning and recommendations. Leverages training data enriched with domain-specific patterns, terminology, and best practices to deliver contextually-appropriate responses. Implements domain-aware instruction following that adjusts reasoning style and terminology based on detected domain context.","intents":["Analyze financial statements and provide investment recommendations","Review medical case summaries and suggest diagnostic considerations","Analyze legal documents and identify compliance risks","Architect technical solutions with industry best practices"],"best_for":["Financial analysts and investment professionals","Healthcare organizations and medical professionals","Legal teams and compliance departments","Enterprise architects and technical leaders"],"limitations":["Domain knowledge is not real-time; may lack latest regulatory changes or market data","Recommendations should not replace professional expertise; requires human validation","Domain accuracy varies by specialization; less reliable for emerging or niche domains","No built-in access to proprietary databases or real-time market data"],"requires":["OpenRouter API key with xAI Grok 3 access","Domain context specification in prompts","Subject matter expert review for critical decisions","Optional: domain-specific terminology or regulatory framework references"],"input_types":["domain-specific documents","case descriptions","technical requirements","regulatory or compliance questions","data analysis requests"],"output_types":["domain-specific recommendations","risk assessments","technical architectures","compliance analyses","structured domain insights"],"categories":["text-generation-language","planning-reasoning"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"openrouter-x-ai-grok-3__cap_6","uri":"capability://text.generation.language.instruction.following.with.complex.constraint.satisfaction","name":"instruction-following with complex constraint satisfaction","description":"Executes multi-step instructions with complex constraints, conditional logic, and format requirements using transformer-based instruction decoding. Implements constraint tracking across response generation to ensure adherence to specified formats, length limits, tone requirements, and logical conditions. Supports both explicit constraints (JSON schema, character limits) and implicit constraints (professional tone, technical accuracy).","intents":["Generate responses that strictly adhere to output format specifications","Create content with multiple simultaneous constraints (length, tone, technical accuracy)","Execute conditional logic workflows based on input characteristics","Enforce style guides and brand voice in generated content"],"best_for":["Content teams automating brand-consistent content generation","API developers requiring strict output format compliance","Workflow automation teams building constraint-based pipelines","Quality assurance teams validating model behavior"],"limitations":["Constraint satisfaction is probabilistic; complex constraints may occasionally be violated","Performance degrades with highly conflicting constraints (e.g., maximum length vs. comprehensive coverage)","No built-in constraint validation; requires post-processing verification","Implicit constraints (tone, style) are less reliable than explicit format constraints"],"requires":["OpenRouter API key with xAI Grok 3 access","Clear, unambiguous constraint specifications","Output validation framework for constraint verification","Optional: constraint examples or reference outputs"],"input_types":["natural language instructions","constraint specifications","format schemas","conditional logic rules","style guides or examples"],"output_types":["constrained text responses","formatted structured data","conditional outputs","style-compliant content"],"categories":["text-generation-language","planning-reasoning"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"openrouter-x-ai-grok-3__cap_7","uri":"capability://text.generation.language.multilingual.text.generation.and.translation","name":"multilingual text generation and translation","description":"Generates and translates text across 50+ languages using multilingual transformer architecture trained on parallel corpora. Supports both direct translation and cross-lingual generation (e.g., write marketing copy in Spanish given English requirements). Implements language-aware tokenization and decoding to maintain semantic coherence and cultural appropriateness across language boundaries.","intents":["Translate technical documentation into multiple languages for global distribution","Generate marketing content in target languages from English briefs","Create multilingual customer support responses","Localize software UI strings and help documentation"],"best_for":["Global companies localizing products and content","International teams collaborating across languages","Content teams scaling to multiple markets","Software teams implementing multilingual UIs"],"limitations":["Translation quality varies significantly by language pair; less reliable for low-resource languages","Cultural nuance and idioms may not translate accurately; requires native speaker review","Domain-specific terminology may be mistranslated without glossary support","No built-in support for dialect-specific variations within languages"],"requires":["OpenRouter API key with xAI Grok 3 access","Source language specification","Target language specification","Optional: terminology glossary or style guide for domain-specific translation"],"input_types":["text in any supported language","marketing briefs","technical documentation","UI strings","customer communications"],"output_types":["translated text","cross-lingual generated content","multilingual response sets","localized content variants"],"categories":["text-generation-language"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"openrouter-x-ai-grok-3__cap_8","uri":"capability://text.generation.language.creative.content.generation.with.style.control","name":"creative content generation with style control","description":"Generates creative content (marketing copy, storytelling, creative writing) with fine-grained style control using instruction-conditioned generation. Implements style embeddings that capture tone, voice, and narrative perspective, allowing users to specify creative parameters (formal vs. casual, technical vs. accessible, humorous vs. serious). Supports iterative refinement through multi-turn dialogue.","intents":["Generate marketing copy variants with different tones and messaging angles","Create product descriptions that balance technical accuracy with marketing appeal","Write creative narratives or storytelling content with specified voice and perspective","Generate social media content adapted to platform-specific styles"],"best_for":["Marketing teams accelerating copywriting workflows","Content creators scaling creative output","Product teams generating variant content for A/B testing","Creative agencies automating initial draft generation"],"limitations":["Generated creative content may lack originality or unique voice; requires human refinement","Style control is approximate; subtle stylistic nuances may not be captured accurately","No built-in brand voice learning; requires explicit style specification per request","Creative quality is subjective; generated content may not align with creative vision"],"requires":["OpenRouter API key with xAI Grok 3 access","Clear style and tone specifications","Brand guidelines or style examples for consistency","Human review and refinement workflow"],"input_types":["product or service descriptions","marketing briefs","creative direction","style specifications","reference examples"],"output_types":["marketing copy variants","product descriptions","creative narratives","social media content","styled content variants"],"categories":["text-generation-language"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"openrouter-x-ai-grok-3__cap_9","uri":"capability://text.generation.language.question.answering.with.source.attribution","name":"question-answering with source attribution","description":"Answers questions based on provided context or knowledge with explicit source attribution and confidence indicators. Implements retrieval-augmented generation patterns where answers are grounded in provided documents or context, with mechanisms to identify and cite specific source passages. Supports both closed-book QA (knowledge-based) and open-book QA (context-based) modes.","intents":["Answer customer questions based on product documentation","Extract answers from research papers with source citations","Build FAQ systems that cite supporting documentation","Create knowledge base systems with traceable answers"],"best_for":["Customer support teams building knowledge base systems","Research teams analyzing document collections","Product teams creating self-service help systems","Compliance teams documenting answer sources"],"limitations":["Answer quality depends on source document quality; garbage in, garbage out","Source attribution may be inaccurate for implicit or inferred answers","No built-in document retrieval; requires external search/retrieval system","Context window limits the amount of source material that can be provided per query"],"requires":["OpenRouter API key with xAI Grok 3 access","Relevant source documents or context","Question input in natural language","Optional: document indexing and retrieval system for large knowledge bases"],"input_types":["natural language questions","source documents or context","knowledge base references","document collections"],"output_types":["answers with source citations","confidence-scored responses","multi-source answers","follow-up question suggestions"],"categories":["text-generation-language","search-retrieval"],"confidence":0.5,"matches":0,"success_rate":0}],"trust":{"score":25,"verified":false,"data_access_risk":"high","permissions":["OpenRouter API key with xAI Grok 3 access","HTTP/2 capable client for streaming support","Minimum context window of 8K tokens for typical code files","JSON schema definition or format specification","Text input preprocessed to remove binary/encoding artifacts","Validation framework for output quality assurance","Source code files or snippets","Optional: language specification and framework context","Optional: custom linting rules or style guides","Clear problem statement or question"],"failure_modes":["Context window limitations may truncate large files; requires strategic code selection for multi-file refactoring","Generated code quality varies by language; less reliable for niche or domain-specific languages","No built-in IDE plugin; requires custom integration via OpenRouter API","Streaming responses add latency overhead compared to batch processing","Accuracy degrades with highly ambiguous or malformed source text; no built-in confidence scoring","Schema complexity is limited by context window; deeply nested structures may require decomposition","No native support for image-based documents; requires OCR preprocessing","Extraction quality varies significantly by domain; requires validation layer for production use","Analysis is heuristic-based; may produce false positives or miss subtle issues","Security analysis is not a substitute for professional security audits","builder identity is not verified yet","no observed match outcomes yet"],"rank_breakdown":{"adoption":0.05,"quality":0.49,"ecosystem":0.24,"match_graph":0.25,"freshness":0.75,"weights":{"adoption":0.35,"quality":0.2,"ecosystem":0.1,"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":"2026-05-24T12:16:25.059Z","last_scraped_at":"2026-05-03T15:20:45.776Z","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=x-ai-grok-3","compare_url":"https://unfragile.ai/compare?artifact=x-ai-grok-3"}},"signature":"uMyhKsIybbzlgwNFTMtngNnA9aszTX3EBy/Ub6SSkkSrcF10dbbrLLeLLbfA4CSEIMUydzcDR0br9u3Sx57iAA==","signedAt":"2026-06-21T01:36:00.622Z","signedBy":"unfragile.ai","version":1},"_links":{"self":"https://unfragile.ai/api/v1/passport/x-ai-grok-3","artifact":"https://unfragile.ai/x-ai-grok-3","verify":"https://unfragile.ai/api/v1/verify?slug=x-ai-grok-3","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"}}