{"passport":{"unfragile":{"@version":"1.0","version":"2026-05","artifact":{"id":"tool_sourceai","slug":"sourceai","name":"SourceAI","type":"product","url":"https://sourceai.dev","page_url":"https://unfragile.ai/sourceai","categories":["code-editors"],"tags":[],"pricing":{"model":"paid","free":false,"starting_price":null},"status":"active","verified":false},"capabilities":[{"id":"tool_sourceai__cap_0","uri":"capability://code.generation.editing.natural.language.to.code.generation","name":"natural-language-to-code-generation","description":"Converts plain English descriptions into executable code by processing natural language prompts through a language model fine-tuned on code-generation tasks, then formatting output for the target language. The system maintains context awareness of language-specific conventions, syntax rules, and framework idioms to produce syntactically valid code that follows community best practices. Implementation likely uses prompt engineering with language-specific templates and post-processing to ensure proper formatting and indentation.","intents":["I want to write a function to sort an array but don't remember the exact syntax in this language","I need to scaffold a REST API endpoint quickly without writing boilerplate from scratch","I want to generate a data validation function from a description of the validation rules","I need to create a utility function for a common task but want to avoid manual typing"],"best_for":["Junior developers learning new languages or frameworks","Intermediate developers prototyping features rapidly","Technical teams accelerating repetitive scaffolding tasks","Non-programmers exploring code generation as a learning tool"],"limitations":["Generated code frequently requires manual debugging and optimization; output quality is inconsistent and sometimes produces inefficient or insecure patterns","No context awareness of existing codebase architecture or project-specific conventions — generates isolated snippets rather than integrated solutions","Struggles with complex multi-file refactoring or architectural decisions requiring domain knowledge","No built-in security scanning of generated code; may produce SQL injection vulnerabilities, hardcoded credentials, or unsafe patterns"],"requires":["Active internet connection for API calls to backend model","Valid SourceAI account with active subscription","Supported target programming language (50+ languages claimed)"],"input_types":["text (natural language prompt)","optional: existing code snippet for context"],"output_types":["code (formatted for target language)","text (explanation of generated code)"],"categories":["code-generation-editing","text-generation-language"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_sourceai__cap_1","uri":"capability://code.generation.editing.multi.language.code.completion","name":"multi-language-code-completion","description":"Provides context-aware code completion suggestions across 50+ programming languages by analyzing partial code input and predicting the most likely next tokens or statements. The system uses language-specific grammar rules and syntax validation to ensure suggestions are syntactically valid and follow language conventions. Completion likely operates through a combination of token-level prediction and pattern matching against common idioms in each language.","intents":["I'm writing code in a language I'm less familiar with and want syntax suggestions","I want to complete a function signature or method call without looking up the exact API","I need to quickly fill in boilerplate code like imports, class definitions, or loop structures","I want suggestions for the next logical statement in my code flow"],"best_for":["Developers working across multiple programming languages","Teams with polyglot codebases (Python, JavaScript, Go, Rust, etc.)","Developers learning new languages and needing syntax guidance"],"limitations":["No codebase indexing or project-wide context awareness — suggestions are based on isolated snippets, not your actual project structure","Completion quality degrades for domain-specific or custom frameworks not well-represented in training data","No IDE integration mentioned; requires manual copy-paste workflow rather than seamless in-editor suggestions","Cannot learn from your project's coding style or conventions over time"],"requires":["Active SourceAI subscription","Internet connectivity for backend inference","Supported programming language"],"input_types":["text (partial code snippet)"],"output_types":["text (completion suggestions)","code (formatted completion)"],"categories":["code-generation-editing"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_sourceai__cap_10","uri":"capability://code.generation.editing.api.endpoint.code.generation","name":"api-endpoint-code-generation","description":"Generates REST API endpoint code (controllers, route handlers, request/response models) from natural language descriptions or API specifications, producing framework-specific code that handles routing, validation, and error handling. The system uses API specification patterns (OpenAPI/Swagger) and framework conventions to generate complete endpoint implementations. Implementation likely involves parsing API specifications or natural language descriptions into an intermediate representation, then generating framework-specific code with proper error handling and validation.","intents":["I need to quickly scaffold REST API endpoints for a new service","I want to generate request/response models and validation from an API spec","I need to implement CRUD operations for a resource without writing boilerplate","I want to generate API documentation and implementation code together"],"best_for":["Backend developers building REST APIs","Teams using API-first development approaches","Rapid API prototyping and MVP development","Developers new to API frameworks"],"limitations":["Generated endpoints lack business logic and require significant customization","No understanding of authentication, authorization, or security requirements","Cannot generate code for complex workflows or multi-step operations","Generated validation may be too strict or too lenient for actual requirements","No awareness of performance implications or caching strategies","Error handling is generic and may not match application-specific error codes"],"requires":["Active SourceAI subscription","Internet connectivity","Target framework specified (Express, Django, FastAPI, etc.)","Optional: OpenAPI/Swagger specification or API description"],"input_types":["text (natural language API description)","code (OpenAPI/Swagger specification)"],"output_types":["code (framework-specific endpoint code)","code (request/response models)","text (API documentation)"],"categories":["code-generation-editing"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_sourceai__cap_11","uri":"capability://code.generation.editing.regex.pattern.generation.and.explanation","name":"regex-pattern-generation-and-explanation","description":"Generates regular expressions from natural language descriptions of pattern matching requirements and explains existing regex patterns in plain English. The system uses pattern templates and regex construction rules to build expressions that match specified patterns, and reverse-engineers regex to explain what they match. Implementation likely uses regex syntax rules and pattern libraries to generate valid expressions, with explanation through pattern decomposition.","intents":["I need a regex to validate email addresses but don't remember the syntax","I found a regex online and want to understand what it does","I need to extract specific data from text using pattern matching","I want to validate user input against specific format requirements"],"best_for":["Developers working with text processing and validation","Teams implementing input validation","Developers learning regex syntax","Data extraction and ETL tasks"],"limitations":["Generated regex may not handle all edge cases or variations","Regex complexity grows quickly; generated patterns may be inefficient for complex requirements","No understanding of regex engine differences (PCRE, JavaScript, Python, etc.)","Explanations may be overly verbose or miss subtle pattern behaviors","Cannot generate regex for complex parsing tasks better suited to proper parsers","Performance implications not considered — generated regex may be slow on large inputs"],"requires":["Active SourceAI subscription","Internet connectivity","Target regex flavor specified (JavaScript, Python, PCRE, etc.)"],"input_types":["text (natural language pattern description)","code (existing regex for explanation)"],"output_types":["code (regex pattern)","text (explanation of pattern)"],"categories":["code-generation-editing"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_sourceai__cap_12","uri":"capability://code.generation.editing.code.style.and.formatting.standardization","name":"code-style-and-formatting-standardization","description":"Reformats code to match specified style guides and coding standards (PEP 8, Google Style Guide, Airbnb, etc.) by parsing code and applying language-specific formatting rules. The system uses style configuration templates for popular standards and applies consistent indentation, naming conventions, and code organization. Implementation likely involves parsing code into an AST, then regenerating code with standardized formatting and style rules applied.","intents":["I want to reformat my code to match my team's style guide","I need to convert code to follow PEP 8 or another standard","I want to ensure consistent naming conventions across my codebase","I need to apply consistent indentation and formatting to legacy code"],"best_for":["Teams establishing coding standards","Projects with inconsistent code style","Code review processes enforcing style standards","Legacy code modernization efforts"],"limitations":["Formatting may not match all aspects of complex style guides","No understanding of context-specific formatting preferences","May break code that relies on specific formatting (e.g., string alignment)","Cannot apply style rules that require semantic understanding","Reformatting may introduce subtle behavior changes in some languages"],"requires":["Active SourceAI subscription","Internet connectivity","Code in a supported language","Target style guide specified (optional; defaults to language standard)"],"input_types":["code (unformatted or inconsistently formatted)"],"output_types":["code (reformatted code)"],"categories":["code-generation-editing"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_sourceai__cap_2","uri":"capability://code.generation.editing.code.explanation.and.documentation","name":"code-explanation-and-documentation","description":"Analyzes provided code snippets and generates human-readable explanations of what the code does, how it works, and why specific patterns were chosen. The system uses natural language generation to produce documentation that explains logic flow, variable purposes, and potential edge cases. Implementation likely involves parsing code into an AST or semantic representation, then generating explanatory text with language-specific terminology.","intents":["I inherited legacy code and need to understand what it does before modifying it","I want to generate docstrings or comments for my code automatically","I need to explain a complex algorithm to a junior developer on my team","I want to understand how a code snippet from Stack Overflow works before using it"],"best_for":["Teams maintaining legacy codebases with poor documentation","Junior developers learning to read and understand existing code","Technical writers generating API documentation","Code reviewers needing to understand unfamiliar code quickly"],"limitations":["Explanations may be inaccurate or overly verbose for complex algorithms or domain-specific code","No understanding of business logic or domain context — explanations are purely technical","Cannot explain code intent or architectural decisions, only what the code literally does","Generated documentation may not match actual code behavior if code has bugs"],"requires":["Active SourceAI subscription","Code snippet in a supported programming language","Internet connectivity"],"input_types":["code (snippet or file)"],"output_types":["text (explanation)","text (documentation/docstring)"],"categories":["code-generation-editing","text-generation-language"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_sourceai__cap_3","uri":"capability://code.generation.editing.code.refactoring.suggestions","name":"code-refactoring-suggestions","description":"Analyzes code snippets to identify refactoring opportunities and suggests improvements for readability, performance, or maintainability. The system applies common refactoring patterns (extract method, simplify conditionals, reduce duplication) and generates modified code with explanations of why the refactoring improves the code. Implementation likely uses pattern matching against known anti-patterns and refactoring rules, then generates improved code through templated transformations.","intents":["I have working code but it's messy and hard to maintain — I want suggestions to clean it up","I want to reduce code duplication across multiple functions","I need to improve performance of a slow function without rewriting it from scratch","I want to make my code more readable and follow language idioms better"],"best_for":["Intermediate developers improving code quality","Teams conducting code reviews and looking for improvement suggestions","Developers refactoring legacy code incrementally","Technical leads establishing coding standards"],"limitations":["Refactoring suggestions may not account for project-specific constraints or architectural decisions","No understanding of performance implications — suggestions may be theoretically cleaner but practically slower","Cannot refactor across multiple files or understand dependencies between modules","Inconsistent quality; some suggestions may introduce subtle bugs or change code behavior","No ability to test refactored code or verify correctness"],"requires":["Active SourceAI subscription","Code snippet in a supported language","Internet connectivity"],"input_types":["code (snippet or function)"],"output_types":["code (refactored version)","text (explanation of changes and rationale)"],"categories":["code-generation-editing"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_sourceai__cap_4","uri":"capability://code.generation.editing.bug.detection.and.fix.suggestions","name":"bug-detection-and-fix-suggestions","description":"Scans code snippets for common bugs, security vulnerabilities, and logic errors, then suggests fixes with explanations. The system uses pattern matching against known bug categories (null pointer dereferences, off-by-one errors, SQL injection, hardcoded credentials) and generates corrected code. Implementation likely combines static analysis patterns with language-specific vulnerability rules and generates fixed code through templated transformations.","intents":["I have code that's not working correctly and need help identifying the bug","I want to check my code for security vulnerabilities before deploying","I need to find performance bottlenecks or inefficient patterns in my code","I want to ensure my code handles edge cases properly"],"best_for":["Junior developers learning to identify common bugs","Teams conducting security code reviews","Developers debugging code without access to a debugger","Technical leads establishing code quality standards"],"limitations":["Bug detection is pattern-based and misses complex logic errors or domain-specific bugs","No runtime context — cannot detect bugs that only manifest under specific conditions","Security scanning is superficial; misses sophisticated vulnerabilities or business logic flaws","Suggested fixes may not be correct or may introduce new bugs","No ability to test fixes or verify they resolve the original issue","Cannot understand code intent, so may flag correct code as buggy"],"requires":["Active SourceAI subscription","Code snippet in a supported language","Internet connectivity"],"input_types":["code (snippet or function)"],"output_types":["text (bug description and severity)","code (fixed version)","text (explanation of fix)"],"categories":["code-generation-editing","safety-moderation"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_sourceai__cap_5","uri":"capability://code.generation.editing.code.to.test.generation","name":"code-to-test-generation","description":"Generates unit tests or test cases from provided code snippets by analyzing function signatures, logic flow, and edge cases, then producing test code in the appropriate testing framework for the target language. The system uses pattern matching to identify test scenarios (happy path, error cases, boundary conditions) and generates test code with assertions. Implementation likely involves parsing function signatures, identifying parameters and return types, then generating test templates with common assertion patterns.","intents":["I wrote a function but don't know how to test it comprehensively","I want to generate test cases for edge cases I might have missed","I need to write unit tests quickly without manually creating test boilerplate","I want to ensure my code has good test coverage before shipping"],"best_for":["Developers new to testing or unfamiliar with testing frameworks","Teams trying to improve test coverage quickly","Rapid prototyping scenarios where comprehensive testing is needed fast","Junior developers learning test-driven development"],"limitations":["Generated tests may not cover all meaningful edge cases or business logic scenarios","Tests are based on code structure, not requirements — may miss cases where code doesn't match intended behavior","No understanding of mocking or dependency injection — tests may not work for code with external dependencies","Generated assertions may be trivial or not test the most important behavior","Cannot generate integration tests or end-to-end test scenarios","Tests require manual review and often need adjustment to actually pass"],"requires":["Active SourceAI subscription","Code snippet in a supported language","Internet connectivity","Target testing framework specified (Jest, pytest, JUnit, etc.)"],"input_types":["code (function or class)"],"output_types":["code (test file in target framework)","text (explanation of test cases)"],"categories":["code-generation-editing"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_sourceai__cap_6","uri":"capability://search.retrieval.code.snippet.search.and.retrieval","name":"code-snippet-search-and-retrieval","description":"Searches a knowledge base or training data for code snippets matching natural language queries or code patterns, then returns relevant examples with explanations. The system uses semantic matching or pattern-based retrieval to find similar code from its training corpus and presents examples that solve similar problems. Implementation likely uses embedding-based similarity search or keyword matching against indexed code examples.","intents":["I want to see examples of how to solve a specific problem in this language","I need to find code patterns for a common task like file I/O or API calls","I want to learn how experienced developers solve a particular problem","I'm looking for best-practice examples for a specific library or framework"],"best_for":["Junior developers learning by example","Developers new to a language or framework","Teams establishing coding standards and best practices","Developers looking for idiomatic solutions"],"limitations":["Retrieved examples may be outdated or use deprecated APIs","No guarantee that examples follow current best practices or security standards","Limited to examples in training data — may not cover niche use cases or new libraries","No context about when to use each pattern or trade-offs between approaches","Examples may be incomplete or require significant modification to work in your context"],"requires":["Active SourceAI subscription","Internet connectivity","Natural language query or code pattern"],"input_types":["text (natural language query)","code (pattern to match)"],"output_types":["code (example snippets)","text (explanation and context)"],"categories":["search-retrieval","code-generation-editing"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_sourceai__cap_7","uri":"capability://code.generation.editing.framework.and.library.code.generation","name":"framework-and-library-code-generation","description":"Generates boilerplate code and scaffolding for popular frameworks and libraries (React, Django, Express, etc.) based on natural language descriptions of desired functionality. The system uses framework-specific templates and patterns to generate code that follows framework conventions and best practices. Implementation likely uses a library of framework-specific code templates that are populated with user-specified parameters and logic.","intents":["I want to scaffold a new React component with hooks and state management","I need to generate a Django model with specific fields and relationships","I want to create an Express API endpoint with proper error handling","I need to set up a database migration or schema definition quickly"],"best_for":["Full-stack developers accelerating repetitive scaffolding","Teams building applications with popular frameworks","Developers new to a framework learning its conventions","Rapid prototyping and MVP development"],"limitations":["Generated code may not integrate properly with existing project structure or dependencies","No understanding of project-specific conventions or architectural patterns","Framework versions matter — generated code may use outdated APIs or patterns","Cannot generate code for custom or niche frameworks","Scaffolding is basic and often requires significant customization","No awareness of performance implications or optimization opportunities"],"requires":["Active SourceAI subscription","Internet connectivity","Target framework and version specified","Supported framework (React, Vue, Angular, Django, Flask, Express, etc.)"],"input_types":["text (natural language description of desired functionality)"],"output_types":["code (framework-specific boilerplate)","text (explanation of generated code and setup instructions)"],"categories":["code-generation-editing"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_sourceai__cap_8","uri":"capability://code.generation.editing.code.language.translation","name":"code-language-translation","description":"Converts code written in one programming language to functionally equivalent code in another language by analyzing the source code's logic and semantics, then generating equivalent code following the target language's idioms and conventions. The system uses pattern matching and semantic analysis to map language-specific constructs to their equivalents in the target language. Implementation likely involves parsing source code into an intermediate representation, then generating target language code from that representation.","intents":["I have a Python script and need to convert it to JavaScript for a web application","I want to port a Java library to Go for better performance","I need to migrate code from one language to another due to team skill changes","I want to understand how a concept works in a different language"],"best_for":["Teams migrating between programming languages","Developers learning new languages by comparing translations","Projects requiring code in multiple languages","Rapid prototyping in different language ecosystems"],"limitations":["Translation quality varies significantly based on language similarity and code complexity","Language-specific idioms and best practices may not translate well","No understanding of language-specific performance characteristics or optimization opportunities","Cannot translate code that relies on language-specific libraries or frameworks","Translated code often requires significant refactoring to be idiomatic in the target language","May miss subtle semantic differences between languages (e.g., type systems, memory management)"],"requires":["Active SourceAI subscription","Internet connectivity","Source code in a supported language","Target language specified"],"input_types":["code (in source language)"],"output_types":["code (in target language)","text (explanation of translation choices)"],"categories":["code-generation-editing"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_sourceai__cap_9","uri":"capability://code.generation.editing.sql.query.generation.and.optimization","name":"sql-query-generation-and-optimization","description":"Generates SQL queries from natural language descriptions and optimizes existing queries for performance by analyzing query structure and suggesting indexing strategies or query rewrites. The system uses pattern matching against common SQL patterns and applies optimization rules (join reordering, index hints, query simplification). Implementation likely involves parsing SQL into an AST, analyzing execution patterns, and generating optimized query variants.","intents":["I need to write a complex SQL query but don't remember the exact syntax","I want to optimize a slow database query without rewriting it from scratch","I need to generate a query to extract specific data from my database schema","I want to understand why a query is slow and how to fix it"],"best_for":["Developers working with SQL databases","Database administrators optimizing query performance","Teams without dedicated DBAs","Rapid development scenarios requiring quick query generation"],"limitations":["Query generation assumes standard SQL; may not work with database-specific dialects (T-SQL, PL/pgSQL)","Optimization suggestions may not account for actual data distribution or index statistics","No understanding of application logic or business requirements — may suggest queries that don't match intent","Cannot analyze query performance without access to actual database and execution plans","Suggested optimizations may not work for all database systems or versions","No awareness of transaction isolation levels or concurrency implications"],"requires":["Active SourceAI subscription","Internet connectivity","Database schema information (optional, for context)","Target SQL dialect specified (MySQL, PostgreSQL, SQL Server, etc.)"],"input_types":["text (natural language query description)","code (existing SQL query for optimization)"],"output_types":["code (SQL query)","text (explanation and optimization suggestions)"],"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":["Active internet connection for API calls to backend model","Valid SourceAI account with active subscription","Supported target programming language (50+ languages claimed)","Active SourceAI subscription","Internet connectivity for backend inference","Supported programming language","Internet connectivity","Target framework specified (Express, Django, FastAPI, etc.)","Optional: OpenAPI/Swagger specification or API description","Target regex flavor specified (JavaScript, Python, PCRE, etc.)"],"failure_modes":["Generated code frequently requires manual debugging and optimization; output quality is inconsistent and sometimes produces inefficient or insecure patterns","No context awareness of existing codebase architecture or project-specific conventions — generates isolated snippets rather than integrated solutions","Struggles with complex multi-file refactoring or architectural decisions requiring domain knowledge","No built-in security scanning of generated code; may produce SQL injection vulnerabilities, hardcoded credentials, or unsafe patterns","No codebase indexing or project-wide context awareness — suggestions are based on isolated snippets, not your actual project structure","Completion quality degrades for domain-specific or custom frameworks not well-represented in training data","No IDE integration mentioned; requires manual copy-paste workflow rather than seamless in-editor suggestions","Cannot learn from your project's coding style or conventions over time","Generated endpoints lack business logic and require significant customization","No understanding of authentication, authorization, or security requirements","builder identity is not verified yet","no observed match outcomes yet"],"rank_breakdown":{"adoption":0.36666666666666664,"quality":0.78,"ecosystem":0.15000000000000002,"match_graph":0.25,"freshness":0.75,"weights":{"adoption":0.25,"quality":0.25,"ecosystem":0.1,"match_graph":0.35,"freshness":0.05}},"observed_outcomes":{"matches":0,"success_rate":0,"avg_confidence":0,"top_intents":[],"last_matched_at":null},"maintenance":{"status":"active","updated_at":"2026-05-24T12:16:33.096Z","last_scraped_at":"2026-04-05T13:23:42.551Z","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=sourceai","compare_url":"https://unfragile.ai/compare?artifact=sourceai"}},"signature":"C8yG0b/60uzzbRC/RjaXC1kqoLJyHTbZjGW4N8R2FRB3RelI/qTlLhAeeuEtwQdHTb6Et/0UXs/1vwDtSnC3BA==","signedAt":"2026-06-19T20:08:40.759Z","signedBy":"unfragile.ai","version":1},"_links":{"self":"https://unfragile.ai/api/v1/passport/sourceai","artifact":"https://unfragile.ai/sourceai","verify":"https://unfragile.ai/api/v1/verify?slug=sourceai","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"}}