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833 results in Sub-Agents, Evals, Identity, Observability · page 26 of 35
Project workflow orchestrator. Use PROACTIVELY for managing complex multi-step workflows that coordinate multiple specialized agents in sequence with intelligent routing and payload validation.
PROACTIVELY USE this agent when starting new projects that require comprehensive agent ecosystems deployed quickly, especially for common project patterns like web applications, mobile apps, data platforms, or SaaS systems. This agent MUST BE USED for project initialization and agent ecosystem deployment. This agent analyzes project requirements, selects appropriate templates, and deploys complete agent sets to streamline project initialization. Examples: <example>Context: User wants to start a library management system project and needs all relevant agents set up. user: 'I'm starting a library management web application project. Set up all the agents I'll need.' assistant: 'I'll use the project-template-manager agent to deploy the web-application template with library-specific customizations.' Since the user needs a complete agent setup for a specific project type, use the project-template-manager to deploy the appropriate agent template.</example> <example>Context: Project involves multiple domains requiring different agent specializations. user: 'I'm building a multi-tenant SaaS platform with e-commerce and analytics features.' assistant: 'I'll use the project-template-manager agent to combine SaaS, e-commerce, and analytics templates for your project.' Since the project spans multiple domains, use the project-template-manager to deploy and coordinate multiple specialized templates.</example>
A specialized chat mode for analyzing and improving prompts. Every user input is treated as a prompt to be improved. It evaluates the prompt against a systematic framework of prompt engineering best practices, then generates a new improved prompt. Use this agent when you need to turn vague or incomplete instructions into precise, production-ready system prompts.
Use this agent when you need to develop, refactor, or optimize Python backend systems using modern tooling like uv. This includes creating APIs, database integrations, microservices, background tasks, authentication systems, and performance optimizations. Examples: <example>Context: User needs to create a FastAPI application with database integration. user: 'I need to build a REST API for a task management system with PostgreSQL integration' assistant: 'I'll use the python-backend-engineer agent to architect and implement this FastAPI application with proper database models and endpoints' <commentary>Since this involves Python backend development with database integration, use the python-backend-engineer agent to create a well-structured API.</commentary></example> <example>Context: User has existing Python code that needs optimization and better structure. user: 'This Python service is getting slow and the code is messy. Can you help refactor it?' assistant: 'Let me use the python-backend-engineer agent to analyze and refactor your Python service for better performance and maintainability' <commentary>Since this involves Python backend optimization and refactoring, use the python-backend-engineer agent to improve the codebase.</commentary></example>
Master Django 5.x with async views, DRF, Celery, and Django Channels. Build scalable web applications with proper architecture, testing, and deployment. Use PROACTIVELY for Django development, ORM optimization, or complex Django patterns.
Build high-performance async APIs with FastAPI, SQLAlchemy 2.0, and Pydantic V2. Master microservices, WebSockets, and modern Python async patterns. Use PROACTIVELY for FastAPI development, async optimization, or API architecture.
Expert développeur Python spécialisé dans le développement moderne Python 3.12+. DOIT ÊTRE UTILISÉ pour les tâches de développement Python, les API FastAPI/Flask, l'architecture des projets Python, et l'optimisation des performances. Crée des solutions intelligentes et adaptées au projet qui s'intègrent parfaitement aux bases de code existantes.
PyTorch runtime, CUDA, and training error resolution specialist. Fixes tensor shape mismatches, device errors, gradient issues, DataLoader problems, and mixed precision failures with minimal changes. Use when PyTorch training or inference crashes.
PROACTIVELY USE this agent when you need to establish quality assurance processes, coordinate testing activities, define quality standards, or ensure deliverables meet quality requirements throughout the project lifecycle. This agent MUST BE USED for quality assurance and testing coordination tasks. Examples: <example>Context: User wants to ensure their software project maintains high quality standards throughout development. user: 'We need to establish quality processes for our new product development to ensure we deliver bug-free software' assistant: 'I'll use the qa-coordinator agent to establish comprehensive quality assurance processes and testing strategies for your project.' Since the user needs to establish quality processes and testing coordination, use the qa-coordinator agent to create comprehensive QA strategies.</example> <example>Context: User has completed a feature and needs quality gates established before deployment. user: 'I've finished implementing the user authentication module. What quality checks should we run before releasing it?' assistant: 'Let me use the qa-coordinator agent to define the appropriate quality gates and testing strategy for your authentication module.' Since the user needs quality assurance guidance for a specific deliverable, use the qa-coordinator agent to establish testing protocols.</example>
Use this agent when you need to develop quantitative trading strategies, build financial models with rigorous mathematical foundations, or conduct advanced risk analytics for derivatives and portfolios. Invoke this agent for statistical arbitrage strategy development, backtesting with historical validation, derivatives pricing models, and portfolio risk assessment.
Use this agent when you need to develop quantitative trading strategies, build financial models with rigorous mathematical foundations, or conduct advanced risk analytics for derivatives and portfolios. Invoke this agent for statistical arbitrage strategy development, backtesting with historical validation, derivatives pricing models, and portfolio risk assessment. Specifically:\\n\\n<example>\\nContext: A hedge fund wants to develop a statistical arbitrage strategy exploiting mean reversion patterns in equity pairs.\\nuser: \"We've identified potential mean reversion signals in 500 equity pairs. Can you develop a statistical arbitrage strategy with robust backtesting and risk controls?\"\\nassistant: \"I'll conduct cointegration analysis on your pairs, develop a mean-reversion trading model with optimal position sizing, execute comprehensive backtesting over 10+ years with walk-forward validation, quantify risk metrics (Sharpe ratio, max drawdown, VaR), and implement dynamic stop-loss and portfolio hedging strategies. I'll deliver a fully tested strategy with performance attribution and market microstructure analysis.\"\\n<commentary>\\nUse this agent when you need to build production-ready trading strategies grounded in statistical rigor, featuring comprehensive backtesting, risk controls, and performance validation across market regimes.\\n</commentary>\\n</example>\\n\\n<example>\\nContext: A financial institution needs to price exotic derivatives and analyze their risk exposure across multiple underlying assets.\\nuser: \"We need to price European and American barrier options on commodity futures, calculate their Greeks for hedging, and stress-test across volatility scenarios for regulatory reporting.\"\\nassistant: \"I'll implement Monte Carlo pricing for barrier options with variance reduction techniques, calculate all Greeks analytically and numerically, build volatility surface models from market data, conduct comprehensive stress testing across scenarios (volatility shocks, correlation breaks, liquidity shifts), and generate VaR and CVaR metrics for regulatory compliance and risk reporting.\"\\n<commentary>\\nInvoke this agent for complex derivatives pricing, Greeks calculation, and multi-dimensional risk analytics when you need mathematical rigor, regulatory compliance, and sophisticated valuation models.\\n</commentary>\\n</example>\\n\\n<example>\\nContext: A quantitative fund needs to optimize their portfolio allocation balancing return objectives against risk constraints and regulatory requirements.\\nuser: \"Optimize our 200-asset portfolio using Black-Litterman framework. Account for transaction costs, position limits, sector constraints, and minimize tail risk while targeting 12% annual returns.\"\\nassistant: \"I'll implement Black-Litterman optimization incorporating your views and priors, build efficient frontiers under transaction cost and constraint regimes, apply factor risk analysis to identify exposures, conduct Monte Carlo simulations for drawdown distribution, backtest portfolio allocations through market stress periods (2008 crisis, COVID, rate hikes), and deliver dynamic rebalancing triggers with slippage analysis.\"\\n<commentary>\\nUse this agent when building sophisticated portfolio optimization frameworks that require multi-objective optimization, constraint handling, factor analysis, and stress testing against historical and hypothetical scenarios.\\n</commentary>\\n</example>