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Found 6,537 Skills
Validates code changes against DeepRead's mandatory patterns and standards defined in AGENTS.md. Use this after writing or modifying code to catch violations before committing.
Comprehensive patterns for building AI-powered code generation tools, code assistants, automated refactoring, code review, and structured output generation using LLMs with function calling and tool use. Use when "code generation, AI code assistant, function calling, structured output, code review AI, automated refactoring, tool use, code completion, agent code, " mentioned.
SmartACE (Agentic Context Engineering) workflow engine with MCP-B (Master Client Bridge) and AMUM-QCI-ETHIC module. Dual database architecture using DuckDB (analytics) + SurrealDB (graph). Uses Blender 5.0 (bpy) and UE5 Remote Control. Use when (1) MCP-B agent-to-agent communication (INQC protocol), (2) AMUM 3→6→9 progressive alignment, (3) QCI quantum coherence states, (4) ETHIC principles enforcement (Marcel/Anthropic/EU AI Act), (5) SurrealDB graph relationships, (6) DuckDB SQL workflows, (7) ML inference with infera/vss, (8) Blender 5.0 headless processing, (9) UE5 scene control, (10) DuckLake time travel.
Guide AI agents through Electron app development with React including security patterns, type-safe IPC, React integration, packaging with code signing, and testing. Keywords: electron, electron-vite, electron-forge, contextBridge, IPC, security, react, packaging, code signing, notarization, playwright, desktop app.
Update all documentation in .plans, AGENTS.md files, docs, and .tasks to match current codebase state. Use when user asks to update docs, refresh documentation, sync docs with code, or validate documentation accuracy.
Z.ai API integration for building applications with GLM models. Use when working with Z.ai/ZhipuAI APIs for: (1) Chat completions with GLM-4.7/4.6/4.5 models, (2) Vision/multimodal tasks with GLM-4.6V, (3) Image generation with GLM-Image or CogView-4, (4) Video generation with CogVideoX-3 or Vidu models, (5) Audio transcription with GLM-ASR-2512, (6) Function calling and tool use, (7) Web search integration, (8) Translation, slide/poster generation agents. Triggers: Z.ai, ZhipuAI, GLM, BigModel, Zhipu, CogVideoX, CogView, Vidu.
Browser automation skill for UI testing via Chrome MCP tools. Use when: (1) QA Agent needs to verify UI visually or test interactions, (2) UI/UX Designer needs to check responsive design or component states, (3) Frontend Dev needs quick visual verification during development, (4) Test Writer needs to document user flows with screenshots/GIFs, (5) Any agent needs to test web interfaces, record demos, or debug UI issues. Capabilities: screenshots, interaction testing, accessibility checks, GIF recording, responsive testing, console/network debugging.
Generate AI-friendly Python CLIs using Click, Pydantic, and uv. Use when user wants to create a new CLI tool that follows best practices for agentic coding environments.
Use when you have 2+ tasks that Codex agents should execute. Runtime-native: Codex sub-agents when available, Codex CLI fallback otherwise. Handles file conflicts via merge/wave strategies. Triggers: "codex team", "spawn codex", "codex agents", "use codex for", "codex fix".
Multi-source comprehensive research using perplexity-researcher, claude-researcher, and gemini-researcher agents. Launches up to 10 parallel research agents for fast results. USE WHEN user says 'do research', 'research X', 'find information about', 'investigate', 'analyze trends', 'current events', or any research-related request.
Use this agent when you need to verify that a UI implementation matches its Figma design specifications. This agent should be called after code has been written to implement a design, particularly after HTML/CSS/React components have been created or modified. The agent will visually compare the live implementation against the Figma design and provide detailed feedback on discrepancies.\n\nExamples:\n- <example>\n Context: The user has just implemented a new component based on a Figma design.\n user: "I've finished implementing the hero section based on the Figma design"\n assistant: "I'll review how well your implementation matches the Figma design."\n <commentary>\n Since UI implementation has been completed, use the design-implementation-reviewer agent to compare the live version with Figma.\n </commentary>\n </example>\n- <example>\n Context: After the general code agent has implemented design changes.\n user: "Update the button styles to match the new design system"\n assistant: "I've updated the butto...
Use this agent when you need to perform security audits, vulnerability assessments, or security reviews of code. This includes checking for common security vulnerabilities, validating input handling, reviewing authentication/authorization implementations, scanning for hardcoded secrets, and ensuring OWASP compliance. <example>Context: The user wants to ensure their newly implemented API endpoints are secure before deployment.\nuser: "I've just finished implementing the user authentication endpoints. Can you check them for security issues?"\nassistant: "I'll use the security-sentinel agent to perform a comprehensive security review of your authentication endpoints."\n<commentary>Since the user is asking for a security review of authentication code, use the security-sentinel agent to scan for vulnerabilities and ensure secure implementation.</commentary></example> <example>Context: The user is concerned about potential SQL injection vulnerabilities in their database queries.\nuser: "I'm worried about SQL inj...