{"passport":{"unfragile":{"@version":"1.0","version":"2026-05","artifact":{"id":"amazon-q-developer","slug":"amazon-q-developer","name":"Amazon Q Developer","type":"agent","url":"https://aws.amazon.com/q/developer","page_url":"https://unfragile.ai/amazon-q-developer","categories":["code-review-security"],"tags":[],"pricing":{"model":"freemium","free":true,"starting_price":null},"status":"active","verified":false},"capabilities":[{"id":"amazon-q-developer__cap_0","uri":"capability://code.generation.editing.multiline.code.completion.with.context.aware.suggestions","name":"multiline code completion with context-aware suggestions","description":"Generates multi-line code suggestions within IDE plugins (VS Code, JetBrains, Visual Studio, Eclipse) by analyzing the current file context and user intent. The system infers code patterns from surrounding code and produces suggestions that integrate seamlessly with existing code style. Claims highest reported acceptance rate among multiline suggestion assistants per BT Group benchmarks.","intents":["I want the IDE to suggest the next 3-5 lines of code as I type","I need boilerplate code generated quickly without manual typing","I want suggestions that match my existing code style and patterns"],"best_for":["developers using JetBrains IDEs, VS Code, Visual Studio, or Eclipse","teams working in Java, .NET, Python, or JavaScript (implied support)","developers seeking high code acceptance rates for AI suggestions"],"limitations":["Supported programming languages beyond Java and .NET are not explicitly documented","Context window size for analyzing surrounding code is unknown, may limit effectiveness in large files","No documented support for real-time pair programming or simultaneous multi-user editing","Accuracy on legacy code patterns or unfamiliar frameworks is undocumented"],"requires":["IDE plugin installation (JetBrains, VS Code, Visual Studio, or Eclipse)","AWS account (free tier available but specific quotas undocumented)","Active internet connection for cloud-based inference"],"input_types":["code context (surrounding lines in current file)","implicit user intent (cursor position, partial code)"],"output_types":["code suggestions (multi-line code blocks)","inline completions"],"categories":["code-generation-editing","developer-tools"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"amazon-q-developer__cap_1","uri":"capability://code.generation.editing.autonomous.java.version.upgrade.agent","name":"autonomous java version upgrade agent","description":"Agentic capability that automatically transforms Java 8 codebases to Java 17 by analyzing code structure, identifying deprecated APIs, and applying modern language features (records, sealed classes, pattern matching). The agent operates autonomously on production applications, handling multi-file refactoring and dependency updates. Specific upgrade metrics and success rates are claimed but not detailed in public documentation.","intents":["I need to upgrade a large Java 8 codebase to Java 17 without manual refactoring","I want to modernize legacy Java code to use current language features","I need to ensure compatibility with newer Java versions across a large application"],"best_for":["enterprise teams managing large Java codebases","organizations with Java 8 legacy systems requiring modernization","teams lacking in-house expertise for Java version migrations"],"limitations":["Only documented for Java 8 → Java 17 path; other version jumps not mentioned","Scope of transformation (what code patterns are handled) is undocumented","No information on handling of third-party library compatibility or breaking changes","Success rate and accuracy metrics are not publicly disclosed","Requires AWS account and integration with Amazon Q Developer platform"],"requires":["Java 8 codebase with standard Maven or Gradle build configuration","AWS account with Amazon Q Developer access","IDE plugin or CLI tool installed","Git repository for version control (implied)"],"input_types":["Java source code (full codebase)","build configuration (pom.xml, build.gradle)","project structure metadata"],"output_types":["refactored Java 17 source code","updated build configuration","migration report (undocumented)"],"categories":["code-generation-editing","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"amazon-q-developer__cap_10","uri":"capability://code.generation.editing.ml.model.design.and.data.pipeline.assistance","name":"ml model design and data pipeline assistance","description":"Provides guidance and code generation for machine learning model design, data pipeline construction, and feature engineering. The system suggests appropriate algorithms, generates boilerplate code for model training and evaluation, and helps structure data pipelines for ML workflows. Integrates with AWS ML services (SageMaker, etc.).","intents":["I want suggestions for which ML algorithm to use for my problem","I need to generate boilerplate code for model training and evaluation","I want to build a data pipeline for ML without writing everything from scratch"],"best_for":["data scientists building ML models","developers integrating ML into applications","teams new to machine learning"],"limitations":["Supported ML frameworks (TensorFlow, PyTorch, scikit-learn, etc.) are not listed","Algorithm selection logic and reasoning are undocumented","Handling of hyperparameter tuning and model optimization is unclear","Accuracy of model design suggestions for domain-specific problems is undocumented","Integration with AWS SageMaker is mentioned but not detailed"],"requires":["IDE plugin or CLI tool installed","AWS account with Amazon Q Developer access","Python or relevant ML framework knowledge (implied)"],"input_types":["problem description (natural language)","dataset schema or sample data","performance requirements"],"output_types":["algorithm recommendations","model training code","data pipeline code","evaluation metrics code"],"categories":["code-generation-editing","planning-reasoning"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"amazon-q-developer__cap_11","uri":"capability://planning.reasoning.operational.incident.investigation.and.diagnostics","name":"operational incident investigation and diagnostics","description":"Analyzes operational incidents, logs, and error messages to diagnose root causes and suggest remediation steps. The system understands AWS service error patterns, network diagnostics, and application-level issues, providing actionable guidance for resolving incidents. Integrates with AWS CloudWatch and operational dashboards.","intents":["I want to understand why my application is failing based on error logs","I need to diagnose network connectivity issues in my AWS infrastructure","I want to identify the root cause of performance degradation"],"best_for":["DevOps engineers troubleshooting production issues","on-call engineers responding to incidents","teams seeking faster incident resolution"],"limitations":["Scope of incident analysis (application-level vs. infrastructure-level) is undocumented","Accuracy of root cause diagnosis is undocumented","Integration with AWS CloudWatch and monitoring tools is not detailed","Handling of complex multi-service failures is unclear","No information on incident severity assessment or escalation logic"],"requires":["AWS account with Amazon Q Developer access","Access to logs and error messages (CloudWatch, application logs, etc.)","AWS infrastructure context (services, configurations)"],"input_types":["error logs and stack traces","CloudWatch metrics and logs","application performance data","network diagnostics output"],"output_types":["root cause analysis","remediation suggestions","diagnostic reports","escalation recommendations"],"categories":["planning-reasoning","data-processing-analysis"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"amazon-q-developer__cap_12","uri":"capability://planning.reasoning.network.diagnostics.and.connectivity.troubleshooting","name":"network diagnostics and connectivity troubleshooting","description":"Diagnoses network connectivity issues, VPC configuration problems, and security group misconfigurations by analyzing network logs, routing tables, and security policies. The system provides step-by-step troubleshooting guidance and suggests configuration fixes for common networking problems in AWS environments.","intents":["I want to diagnose why my EC2 instance can't reach a database","I need to understand VPC routing and security group configuration issues","I want to troubleshoot connectivity problems between AWS services"],"best_for":["DevOps engineers managing AWS networking","cloud architects designing VPC configurations","teams troubleshooting connectivity issues"],"limitations":["Scope of network diagnostics (VPC, security groups, NACLs, routing) is undocumented","Accuracy of diagnosis for complex multi-VPC or hybrid cloud scenarios is unclear","Integration with AWS VPC Flow Logs and network monitoring tools is not detailed","Handling of advanced networking scenarios (VPN, Direct Connect, Transit Gateway) is undocumented","No information on compliance or security policy validation"],"requires":["AWS account with Amazon Q Developer access","Access to VPC configuration and network logs","AWS networking knowledge (implied)"],"input_types":["VPC configuration (subnets, route tables, security groups)","VPC Flow Logs","network connectivity test results","application error messages"],"output_types":["network diagnostics report","configuration recommendations","troubleshooting steps","security group/NACL fixes"],"categories":["planning-reasoning","data-processing-analysis"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"amazon-q-developer__cap_13","uri":"capability://tool.use.integration.ide.plugin.installation.and.configuration","name":"ide plugin installation and configuration","description":"Provides IDE plugin installation and setup for VS Code, JetBrains IDEs (IntelliJ, PyCharm, WebStorm, etc.), Visual Studio, and Eclipse. The plugin integrates Amazon Q Developer capabilities directly into the IDE, enabling inline code suggestions, refactoring, and other features without leaving the editor. Installation is claimed to take 'a few minutes' with minimal configuration.","intents":["I want to install Amazon Q Developer in my IDE","I need to configure Amazon Q to work with my AWS account","I want to enable code suggestions and other features in my editor"],"best_for":["developers using VS Code, JetBrains, Visual Studio, or Eclipse","teams standardizing on Amazon Q Developer across IDEs","organizations with existing AWS accounts"],"limitations":["Specific IDE versions supported are not documented","Configuration complexity for enterprise environments (SSO, proxy, etc.) is undocumented","No information on offline mode or local-only operation","Plugin update frequency and compatibility guarantees are not specified","Support for IDE extensions and plugin conflicts is undocumented"],"requires":["VS Code, JetBrains IDE, Visual Studio, or Eclipse installed","AWS account (free tier available)","Internet connection for plugin download and cloud inference"],"input_types":["IDE selection","AWS credentials"],"output_types":["installed and configured IDE plugin","inline code suggestions","IDE integration status"],"categories":["tool-use-integration","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"amazon-q-developer__cap_14","uri":"capability://tool.use.integration.cli.tool.for.command.line.code.assistance","name":"cli tool for command-line code assistance","description":"Provides command-line interface for accessing Amazon Q Developer capabilities outside of IDE environments. The CLI enables code generation, refactoring, testing, and documentation generation from the terminal, supporting batch processing and CI/CD pipeline integration. Supports piping and scripting for automation.","intents":["I want to use Amazon Q Developer from the command line without opening an IDE","I need to integrate Amazon Q into my CI/CD pipeline for automated code generation","I want to batch process multiple files for refactoring or documentation"],"best_for":["DevOps engineers integrating Amazon Q into CI/CD pipelines","developers preferring command-line workflows","teams automating code generation and refactoring"],"limitations":["CLI command syntax and available options are not documented","Integration with CI/CD systems (GitHub Actions, GitLab CI, Jenkins, etc.) is not detailed","Batch processing capabilities and performance are undocumented","Output format options (JSON, plain text, etc.) are not specified","No information on error handling or retry logic"],"requires":["CLI tool installed (installation method undocumented)","AWS account with Amazon Q Developer access","AWS credentials configured (AWS CLI or environment variables)","Command-line shell (bash, PowerShell, etc.)"],"input_types":["source code files or directories","command-line arguments and options","piped input (stdin)"],"output_types":["generated code","refactored code","test code","documentation","CLI output (format undocumented)"],"categories":["tool-use-integration","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"amazon-q-developer__cap_15","uri":"capability://tool.use.integration.aws.management.console.integration.for.cloud.native.guidance","name":"aws management console integration for cloud-native guidance","description":"Integrates Amazon Q Developer directly into AWS Management Console, providing context-aware guidance for AWS service configuration, troubleshooting, and best practices. The system understands the current AWS service being viewed and provides relevant code examples, configuration recommendations, and operational guidance without leaving the console.","intents":["I want guidance on configuring an AWS service while in the Management Console","I need code examples for using the AWS service I'm currently viewing","I want to understand best practices for the AWS resource I'm managing"],"best_for":["AWS users managing infrastructure through the Management Console","teams learning AWS services and best practices","developers seeking code examples for AWS services"],"limitations":["Scope of AWS services supported is undocumented","Integration depth with Management Console UI is unclear","Accuracy of guidance for complex multi-service scenarios is undocumented","No information on handling of custom or third-party AWS services","Real-time context awareness limitations are undocumented"],"requires":["AWS account with Amazon Q Developer access","AWS Management Console access","Internet connection"],"input_types":["AWS service context (current service, resource type)","user queries or requests (implicit from console context)"],"output_types":["code examples","configuration recommendations","best practice guidance","troubleshooting steps"],"categories":["tool-use-integration","planning-reasoning"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"amazon-q-developer__cap_16","uri":"capability://tool.use.integration.slack.and.microsoft.teams.integration.for.team.collaboration","name":"slack and microsoft teams integration for team collaboration","description":"Integrates Amazon Q Developer into Slack and Microsoft Teams, enabling team members to ask questions about AWS services, get code examples, and receive guidance without leaving chat platforms. The bot responds to queries with AWS-specific information, code snippets, and best practice recommendations, supporting asynchronous team collaboration.","intents":["I want to ask about AWS services in Slack without opening the console or IDE","I need to share code examples and guidance with my team in Teams","I want to get quick answers to AWS questions during team discussions"],"best_for":["distributed teams collaborating on AWS projects","teams using Slack or Teams as primary communication platform","organizations seeking to democratize AWS knowledge"],"limitations":["Scope of capabilities available in chat (vs. IDE/console) is undocumented","Message length and context limitations are unclear","Integration depth with Slack/Teams workflows is undocumented","No information on handling of sensitive information in chat","Accuracy of responses in asynchronous chat context is undocumented"],"requires":["Slack or Microsoft Teams workspace","Amazon Q Developer bot installed in workspace","AWS account with Amazon Q Developer access","Appropriate permissions in Slack/Teams"],"input_types":["natural language questions in chat","AWS service names or topics","code snippets (optional)"],"output_types":["AWS guidance and explanations","code examples","best practice recommendations","links to documentation"],"categories":["tool-use-integration","text-generation-language"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"amazon-q-developer__cap_2","uri":"capability://code.generation.editing.net.windows.to.linux.porting.agent","name":".net windows-to-linux porting agent","description":"Agentic capability that automatically transforms .NET applications from Windows-specific implementations to cross-platform Linux-compatible code. The agent identifies Windows API dependencies, replaces them with cross-platform alternatives, and updates project configurations. Operates autonomously across multi-file .NET projects with claimed production application support.","intents":["I need to port a Windows .NET application to run on Linux","I want to remove Windows-specific API dependencies from my .NET codebase","I need to containerize a legacy .NET application for cloud deployment"],"best_for":["enterprises migrating .NET applications to cloud/containerized environments","teams modernizing Windows-only .NET codebases for cross-platform deployment","organizations adopting Linux-based infrastructure"],"limitations":["Scope of .NET versions supported (Framework vs. Core vs. 5+) is undocumented","Handling of complex Windows API dependencies (WinForms, WPF, Registry, etc.) is not detailed","No information on third-party library compatibility assessment","Success rate and accuracy metrics are not publicly disclosed","Requires AWS account integration"],"requires":[".NET application codebase (version undocumented)","AWS account with Amazon Q Developer access","IDE plugin or CLI tool installed","Git repository for version control (implied)"],"input_types":[".NET source code (C#, VB.NET)","project files (.csproj, .vbproj)","configuration files (app.config, appsettings.json)"],"output_types":["refactored .NET source code (Linux-compatible)","updated project configuration","dependency replacement mappings (undocumented)"],"categories":["code-generation-editing","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"amazon-q-developer__cap_3","uri":"capability://code.generation.editing.aws.aware.code.generation.with.service.recommendations","name":"aws-aware code generation with service recommendations","description":"Generates code with AWS service recommendations integrated into suggestions, providing context-aware guidance on which AWS services (EC2, S3, Lambda, RDS, etc.) are appropriate for the task at hand. The system understands AWS architectural patterns and best practices, offering suggestions that align with AWS Well-Architected Framework principles. Available in IDE plugins and AWS Management Console.","intents":["I want code suggestions that recommend the right AWS service for my use case","I need to understand AWS architectural best practices while coding","I want to avoid anti-patterns and follow AWS Well-Architected Framework"],"best_for":["developers building applications on AWS","teams new to AWS seeking guidance on service selection","enterprises standardizing on AWS architecture patterns"],"limitations":["AWS-specific knowledge may not generalize to other cloud providers (Azure, GCP)","Recommendations are based on undocumented training data and patterns","No information on how recommendations handle multi-region or hybrid cloud scenarios","Accuracy of recommendations for niche or newer AWS services is undocumented"],"requires":["AWS account with Amazon Q Developer access","IDE plugin or AWS Management Console access","Basic familiarity with AWS services (implied)"],"input_types":["code context (current file, surrounding code)","natural language prompts describing the use case","implicit AWS context (AWS region, account metadata)"],"output_types":["code suggestions with AWS service integration","service recommendation explanations","architectural guidance"],"categories":["code-generation-editing","planning-reasoning"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"amazon-q-developer__cap_4","uri":"capability://planning.reasoning.cloud.cost.optimization.analysis.and.guidance","name":"cloud cost optimization analysis and guidance","description":"Analyzes code and infrastructure configurations to identify cost optimization opportunities within AWS, providing recommendations for reducing compute, storage, and data transfer costs. The system understands AWS pricing models and suggests architectural changes (e.g., reserved instances, spot instances, storage tiering) that maintain performance while reducing costs.","intents":["I want to understand where my AWS costs are coming from in my code","I need recommendations for reducing my AWS bill without sacrificing performance","I want to optimize resource allocation across my application"],"best_for":["teams managing large AWS infrastructure costs","startups optimizing cloud spending","enterprises conducting cost optimization reviews"],"limitations":["Scope of cost analysis (code-level vs. infrastructure-level) is undocumented","Recommendations are based on undocumented cost models and assumptions","No information on handling of reserved instance commitments or savings plans","Accuracy of recommendations for complex multi-service architectures is undocumented","Real-time cost data integration is not mentioned"],"requires":["AWS account with Amazon Q Developer access","Code or infrastructure configuration files","AWS Cost Explorer data (implied but not explicitly required)"],"input_types":["application code (Python, Java, Node.js, etc.)","infrastructure configuration (CloudFormation, Terraform, CDK)","AWS resource metadata (implicit)"],"output_types":["cost optimization recommendations","estimated savings calculations (undocumented)","architectural refactoring suggestions"],"categories":["planning-reasoning","data-processing-analysis"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"amazon-q-developer__cap_5","uri":"capability://code.generation.editing.automated.code.review.with.security.and.quality.checks","name":"automated code review with security and quality checks","description":"Performs automated code review by analyzing code for security vulnerabilities, code quality issues, and best practice violations. The system provides inline feedback within the IDE or as standalone review reports, identifying issues such as SQL injection risks, insecure API usage, and performance anti-patterns. Integrates with development workflow to catch issues before code review.","intents":["I want automated feedback on security issues in my code before submitting for review","I need to identify code quality problems and best practice violations","I want to enforce coding standards across my team automatically"],"best_for":["development teams seeking to reduce security vulnerabilities","organizations enforcing code quality standards","teams with limited code review capacity"],"limitations":["Specific vulnerability classes and detection methods are undocumented","False positive rates and accuracy metrics are not disclosed","Scope of security scanning (SAST, DAST, dependency scanning) is unclear","No information on handling of custom security rules or compliance requirements","Integration with CI/CD pipelines is not documented"],"requires":["IDE plugin or CLI tool installed","AWS account with Amazon Q Developer access","Code repository (Git implied)"],"input_types":["source code (multiple languages)","code context (surrounding code, file history)"],"output_types":["security vulnerability reports","code quality feedback","remediation suggestions","inline IDE annotations"],"categories":["code-generation-editing","safety-moderation"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"amazon-q-developer__cap_6","uri":"capability://code.generation.editing.test.case.generation.from.code.context","name":"test case generation from code context","description":"Automatically generates unit tests, integration tests, and test cases based on code context and function signatures. The system analyzes code logic, identifies edge cases, and produces test code in the same language as the source code. Tests are generated with assertions and setup/teardown logic, ready for execution.","intents":["I want to generate unit tests for my functions without writing boilerplate","I need test cases that cover edge cases and error conditions","I want to improve test coverage quickly"],"best_for":["developers seeking to increase test coverage rapidly","teams with limited QA resources","projects transitioning to test-driven development"],"limitations":["Test quality and edge case coverage are undocumented","Supported testing frameworks (JUnit, pytest, xUnit, etc.) are not listed","No information on handling of complex dependencies or mocking requirements","Accuracy for domain-specific logic or business rules is undocumented","Generated tests still require manual review and execution"],"requires":["IDE plugin or CLI tool installed","AWS account with Amazon Q Developer access","Source code with clear function signatures"],"input_types":["source code (functions, classes, modules)","code context (surrounding code, type hints)"],"output_types":["test code (same language as source)","test cases with assertions","setup/teardown code"],"categories":["code-generation-editing","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"amazon-q-developer__cap_7","uri":"capability://text.generation.language.code.documentation.generation.from.source","name":"code documentation generation from source","description":"Automatically generates documentation (docstrings, comments, README sections) from source code by analyzing function signatures, logic flow, and code context. The system produces documentation in standard formats (Javadoc, JSDoc, Python docstrings, XML comments) that match the source language and coding conventions.","intents":["I want to generate documentation for my code without manual writing","I need to maintain consistent documentation style across my codebase","I want to create API documentation from my code automatically"],"best_for":["developers maintaining large codebases with poor documentation","teams standardizing documentation formats","open-source projects seeking to improve documentation"],"limitations":["Documentation quality and accuracy are undocumented","Supported documentation formats (Javadoc, JSDoc, Sphinx, etc.) are not listed","No information on handling of complex algorithms or business logic explanation","Generated documentation may require manual review and enhancement","Scope of documentation (function-level vs. module-level vs. architecture) is unclear"],"requires":["IDE plugin or CLI tool installed","AWS account with Amazon Q Developer access","Source code with clear structure"],"input_types":["source code (functions, classes, modules)","code context (surrounding code, type hints)"],"output_types":["docstrings (language-specific format)","inline comments","README sections","API documentation"],"categories":["text-generation-language","code-generation-editing"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"amazon-q-developer__cap_8","uri":"capability://code.generation.editing.code.refactoring.with.pattern.recognition","name":"code refactoring with pattern recognition","description":"Suggests and applies code refactoring transformations by recognizing code patterns and proposing improvements for readability, maintainability, and performance. The system identifies opportunities such as extracting methods, simplifying conditionals, removing duplication, and applying design patterns. Refactorings are applied across multiple files with consistency.","intents":["I want to identify code smells and refactoring opportunities in my codebase","I need to extract duplicated code into reusable functions","I want to apply design patterns to improve code structure"],"best_for":["teams improving code quality and maintainability","developers learning refactoring techniques","projects undergoing technical debt reduction"],"limitations":["Refactoring scope (method-level vs. class-level vs. module-level) is undocumented","Supported refactoring patterns and transformations are not listed","No information on handling of complex dependencies or side effects","Risk assessment for refactorings is undocumented","Requires manual review before applying refactorings"],"requires":["IDE plugin or CLI tool installed","AWS account with Amazon Q Developer access","Source code with clear structure","Git repository for version control (implied)"],"input_types":["source code (functions, classes, modules)","code context (surrounding code, dependencies)"],"output_types":["refactored source code","refactoring suggestions with explanations","impact analysis (undocumented)"],"categories":["code-generation-editing","planning-reasoning"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"amazon-q-developer__cap_9","uri":"capability://code.generation.editing.natural.language.to.sql.query.translation","name":"natural language to sql/query translation","description":"Translates natural language descriptions into SQL queries, data pipeline code, or query expressions by understanding the intent and generating syntactically correct, optimized queries. The system supports multiple SQL dialects and data platforms (PostgreSQL, MySQL, DynamoDB, etc.) and can generate queries from table schemas and natural language descriptions.","intents":["I want to write SQL queries by describing what data I need in English","I need to generate data pipeline code from natural language specifications","I want to query my database without writing SQL manually"],"best_for":["non-technical users querying databases","data analysts seeking faster query generation","developers building data-driven applications"],"limitations":["Supported SQL dialects and data platforms are not explicitly listed","Query optimization and performance are undocumented","Handling of complex joins, subqueries, and aggregations is unclear","Accuracy for domain-specific or business logic queries is undocumented","No information on schema understanding or table relationship inference"],"requires":["IDE plugin or CLI tool installed","AWS account with Amazon Q Developer access","Database schema information (implied)"],"input_types":["natural language descriptions","database schema metadata","example data (optional)"],"output_types":["SQL queries","data pipeline code (Python, Spark, etc.)","query explanations"],"categories":["code-generation-editing","data-processing-analysis"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"amazon-q-developer__headline","uri":"capability://code.generation.editing.ai.coding.assistant.specialized.in.aws.services","name":"ai coding assistant specialized in aws services","description":"Amazon Q Developer is an AI coding assistant that provides code generation, debugging, optimization, and security scanning, specifically tailored for AWS services and architecture, making it a unique tool for developers working within the AWS ecosystem.","intents":["best AI coding assistant","AI coding assistant for AWS","top tools for code optimization","best debugging tools for AWS development","AI tools for secure coding practices"],"best_for":["AWS developers","teams focusing on cloud applications"],"limitations":[],"requires":[],"input_types":[],"output_types":[],"categories":["code-generation-editing"],"confidence":0.5,"matches":0,"success_rate":0}],"trust":{"score":73,"verified":false,"data_access_risk":"high","permissions":["IDE plugin installation (JetBrains, VS Code, Visual Studio, or Eclipse)","AWS account (free tier available but specific quotas undocumented)","Active internet connection for cloud-based inference","Java 8 codebase with standard Maven or Gradle build configuration","AWS account with Amazon Q Developer access","IDE plugin or CLI tool installed","Git repository for version control (implied)","Python or relevant ML framework knowledge (implied)","Access to logs and error messages (CloudWatch, application logs, etc.)","AWS infrastructure context (services, configurations)"],"failure_modes":["Supported programming languages beyond Java and .NET are not explicitly documented","Context window size for analyzing surrounding code is unknown, may limit effectiveness in large files","No documented support for real-time pair programming or simultaneous multi-user editing","Accuracy on legacy code patterns or unfamiliar frameworks is undocumented","Only documented for Java 8 → Java 17 path; other version jumps not mentioned","Scope of transformation (what code patterns are handled) is undocumented","No information on handling of third-party library compatibility or breaking changes","Success rate and accuracy metrics are not publicly disclosed","Requires AWS account and integration with Amazon Q Developer platform","Supported ML frameworks (TensorFlow, PyTorch, scikit-learn, etc.) are not listed","builder identity is not verified yet","no observed match outcomes yet"],"rank_breakdown":{"adoption":0.7,"quality":0.9,"ecosystem":0.15000000000000002,"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":"2026-05-24T12:16:19.836Z","last_scraped_at":null,"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=amazon-q-developer","compare_url":"https://unfragile.ai/compare?artifact=amazon-q-developer"}},"signature":"0zgo6geGPDhl6gkU+xieTlFnLMdy2sIEN1n1jpgmsURwjb/SZAPq8aIs1YFa9OU22xPVmHQigp0LqQBlzc2xBg==","signedAt":"2026-06-22T05:07:22.167Z","signedBy":"unfragile.ai","version":1},"_links":{"self":"https://unfragile.ai/api/v1/passport/amazon-q-developer","artifact":"https://unfragile.ai/amazon-q-developer","verify":"https://unfragile.ai/api/v1/verify?slug=amazon-q-developer","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"}}