toolkit

Process @implement comments in code files and convert them to documentation

Search and manage agent memories with hybrid (vector + BM25) search

Ultra-minimal session snapshot (fast, no memory writes)

Memory-aware session compact — triggers native pi compaction with memory persistence

Interactive design system generator: gather brand tokens through Q&A, scaffold CSS/Tailwind/SCSS/iOS/Android outputs, then create sample UI with /frontend-design

Use this agent when you need to leverage OpenAI Codex CLI for advanced code generation, analysis, and problem-solving tasks using OpenAI's Codex models. This includes code completion, code explanation, bug fixing, code translation between languages, documentation generation, and intelligent code suggestions. The agent excels at understanding natural language descriptions and converting them into working code. <example>Context: User wants to generate a function from natural language. user: 'Create a function that validates email addresses using regex' assistant: 'I'll use the Task tool to launch the codex-agent to generate an email validation function with proper regex patterns' <commentary>Since the user needs code generation from natural language, use the Task tool to launch the codex-agent to leverage Codex's natural language to code capabilities.</commentary></example> <example>Context: User needs to understand complex code. user: 'Explain what this recursive algorithm does' assistant: 'Let me use the Task tool to launch the codex-agent to analyze and explain this recursive algorithm step by step' <commentary>The codex-agent is ideal for code explanation tasks that require deep understanding of algorithms and logic.</commentary></example> <example>Context: User wants to translate code between languages. user: 'Convert this Python function to JavaScript' assistant: 'I'll use the Task tool to launch the codex-agent to translate this Python code to JavaScript while maintaining functionality' <commentary>The codex-agent's multi-language capabilities make it perfect for code translation tasks.</commentary></example>

Use this agent when you need to optimize media files using Crush CLI tools, verify compression quality, validate output integrity, or ensure media files meet specific size and quality requirements. Examples: <example>Context: User has just compressed a batch of images and wants to verify the results. user: 'I just ran crush on my product images folder. Can you check if everything processed correctly?' assistant: 'I'll use the crush-agent to verify your compression results and check for any issues.' <commentary>Since the user needs verification of crush compression results, use the crush-agent to analyze the output quality and integrity.</commentary></example> <example>Context: User wants to optimize video files for web delivery. user: 'I need to compress these marketing videos for our website but maintain good quality' assistant: 'Let me use the crush-agent to help optimize your videos with the right balance of compression and quality.' <commentary>The user needs media optimization expertise, so use the crush-agent to handle the compression strategy and quality validation.</commentary></example>

Use this agent when you need to leverage Cursor CLI for advanced code analysis, generation, review, or refactoring tasks using state-of-the-art AI models. This includes comprehensive code reviews, intelligent refactoring, test generation, bug fixing, Git integration tasks like commit message generation, and managing AI conversation sessions. The agent excels at complex multi-step reasoning tasks and maintaining context across sessions. Examples: <example>Context: User wants to review recently written authentication code. user: 'I just implemented a new authentication module' assistant: 'I'll use the cursor-agent to review your authentication module for security, performance, and best practices' <commentary>Since the user has written new authentication code, use the cursor-agent to perform a comprehensive review using Cursor's advanced AI capabilities.</commentary></example> <example>Context: User needs to refactor legacy code. user: 'This jQuery code needs to be modernized' assistant: 'Let me use the cursor-agent to refactor this jQuery code to modern React' <commentary>The cursor-agent is ideal for intelligent refactoring tasks that require understanding of both legacy and modern patterns.</commentary></example> <example>Context: User is working on a complex feature and wants to continue a previous AI conversation. user: 'I want to continue working on the payment integration we discussed yesterday' assistant: 'I'll use the cursor-agent to resume our previous session about the payment integration' <commentary>The cursor-agent's session management capabilities make it perfect for continuing complex, multi-part conversations.</commentary></example>

Use this agent when you need to leverage Factory's Droid CLI for enterprise-grade code generation, codebase analysis, and collaborative development tasks. This includes architecture analysis, code modifications with transparent review, security audits, Git operations, and integration with enterprise tools like Jira, Notion, and Slack. The agent excels at understanding codebases contextually and making thoughtful, reviewable changes. <example>Context: User wants to understand a codebase. user: 'Analyze this project and explain the architecture' assistant: 'I'll use the Task tool to launch the droid-agent to analyze the codebase and provide comprehensive architectural insights' <commentary>Since the user needs codebase analysis, use the Task tool to launch the droid-agent to leverage Droid's contextual understanding capabilities.</commentary></example> <example>Context: User needs to implement a feature from a ticket. user: 'Implement the feature described in PROJ-123' assistant: 'Let me use the Task tool to launch the droid-agent to read the ticket context and implement the feature following team conventions' <commentary>The droid-agent is ideal for enterprise workflows that integrate with tools like Jira and follow organizational standards.</commentary></example> <example>Context: User wants a security audit. user: 'Audit this codebase for security vulnerabilities' assistant: 'I'll use the Task tool to launch the droid-agent to perform a security audit and create a remediation plan' <commentary>The droid-agent's enterprise capabilities make it perfect for security-focused analysis tasks.</commentary></example>

Use this agent when you need to analyze large codebases that exceed standard context limits (>100KB), perform comprehensive multi-directory code reviews, generate architecture documentation, leverage Google Search for real-time information and current best practices, conduct security audits across entire repositories, verify feature implementations project-wide, or when you need to utilize Gemini's 1M token context window for massive codebases. This agent excels at bug fixes, feature creation, test coverage improvement, and multi-file refactoring operations. Examples: <example> Context: User needs to analyze a large monorepo that exceeds normal context limits user: "Can you analyze our entire microservices architecture and identify potential bottlenecks?" assistant: "I'll use the gemini-agent to analyze your entire codebase architecture since this requires processing a large amount of code across multiple services." <commentary> The user is asking for a comprehensive analysis of a large codebase (microservices), which is perfect for the gemini-agent with its 1M token context window. </commentary> </example> <example> Context: User needs current best practices with web search user: "Review our authentication implementation against the latest 2025 security standards" assistant: "Let me use the gemini-agent to review your authentication implementation and search for the latest 2025 security standards and best practices." <commentary> The user wants a review that includes current information from the web, which the gemini-agent can provide through its Google Search integration. </commentary> </example> <example> Context: User needs multi-file refactoring across a project user: "Convert all our API calls from callbacks to async/await pattern" assistant: "I'll use the gemini-agent to refactor all API calls across your codebase from callbacks to async/await pattern." <commentary> This is a multi-file refactoring task that the gemini-agent handles well with its native coding assistance capabilities. </commentary> </example>