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Found 338 Skills
An image generation/editing Skill for GPT Image 2. It can be used in 3 environments: (A) Garden Local Mode: directly generate and save images via OpenAI-compatible APIs; (B) Host-Native Mode: treat this Skill as a prompt engineering guide, and pass the rendered prompt to the image tool built into the host Agent for image generation; (C) Advisor Mode: degrade to a high-quality prompt consultant when the host has no image tools. It covers 18 major categories and over 80 structured templates, including scenarios such as posters, UI, products, infographics, academic figures, technical architecture diagrams, comics, avatars, process boards, storyboards, IP peripherals, and editing workflows.
Review AI API key leakage patterns and redaction strategies. Use for identifying exposed keys for OpenAI, Anthropic, Gemini, and 10+ other providers. Use proactively when code integrates AI providers or when environment variables/keys are present. Examples: - user: "Check for leaked OpenAI keys" → scan for `sk-` patterns and client-side exposure - user: "Is my Gemini integration secure?" → audit vertex AI config and key redaction - user: "Review AI provider logging" → ensure secrets are redacted from logs - user: "Scan for Anthropic secrets" → check for `ant-` keys in code and configs - user: "Audit Vertex AI integration" → verify proper IAM roles and service account usage
AI image generation with OpenAI, Azure OpenAI, Google, OpenRouter, DashScope, MiniMax, Jimeng, Seedream and Replicate APIs. Supports text-to-image, reference images, aspect ratios, and batch generation from saved prompt files. Sequential by default; use batch parallel generation when the user already has multiple prompts or wants stable multi-image throughput. Use when user asks to generate, create, or draw images.
Implement the Syncfusion React AI AssistView component. Use this skill to handle AI-powered conversational interfaces, AssistView setup, conversation flow, speech input or output, file attachments, UI customization, state management, and AI service integration such as OpenAI or Azure AI in React applications.
Generate images with GPT Image 2 (ChatGPT Images 2.0) inside Claude Code, using your existing ChatGPT Plus or Pro subscription — no separate OpenAI access, no per-image billing. Supports text-to-image, image-to-image editing, style transfer, and multi-reference composition via the local Codex CLI. Triggers on "gpt image 2", "gpt-image-2", "ChatGPT Images 2.0", "image 2", or any explicit ask to generate or edit an image through the user's ChatGPT plan.
Latest AI models reference - Claude, OpenAI, Gemini, Eleven Labs, Replicate
End-of-session knowledge cleanup with OCD-level rigor — reconciles project docs (CLAUDE.md, README.md, docs/) and agent memory against the code so nothing rots. OCD-level review and synchronization of project documents and agent memory after a session. MUST trigger when the user says: "sync up", "tidy up docs", "update memory", "clean up docs", "/sync", "/neat", "sync up", "tidy up docs", "tidy up", "update memory", "organize", "wrap up", "this phase is done", "newcomers can start directly", or any phrase suggesting a development milestone where knowledge needs reconciliation. Also trigger when the user reports stale docs, conflicting memories, or wants a clean handoff to teammates or other agents. A standalone "tidy" with prior development context counts — do not under-trigger. Cross-platform: works on Claude Code, OpenAI Codex, OpenCode, and OpenClaw.
Serves LLMs with high throughput using vLLM's PagedAttention and continuous batching. Use when deploying production LLM APIs, optimizing inference latency/throughput, or serving models with limited GPU memory. Supports OpenAI-compatible endpoints, quantization (GPTQ/AWQ/FP8), and tensor parallelism.
Use to select models to run locally with llama.cpp and GGUF on CPU, Mac Metal, CUDA, or ROCm. Covers finding GGUFs, quant selection, running servers, exact GGUF file lookup, conversion, and OpenAI-compatible local serving.
Build AI agents that interact with computers like humans do - viewing screens, moving cursors, clicking buttons, and typing text. Covers Anthropic's Computer Use, OpenAI's Operator/CUA, and open-source alternatives. Critical focus on sandboxing, security, and handling the unique challenges of vision-based control. Use when: computer use, desktop automation agent, screen control AI, vision-based agent, GUI automation.
Patterns and techniques for adding governance, safety, and trust controls to AI agent systems. Use this skill when: - Building AI agents that call external tools (APIs, databases, file systems) - Implementing policy-based access controls for agent tool usage - Adding semantic intent classification to detect dangerous prompts - Creating trust scoring systems for multi-agent workflows - Building audit trails for agent actions and decisions - Enforcing rate limits, content filters, or tool restrictions on agents - Working with any agent framework (PydanticAI, CrewAI, OpenAI Agents, LangChain, AutoGen)
BYOK — register a custom LLM endpoint (Anthropic, OpenAI, Qwen, DeepSeek, etc.) with your own API key