Total 50,372 skills, AI & Machine Learning has 8465 skills
Showing 12 of 8465 skills
Full OpenAI-compatible GPT Image 2 coverage across images/generations, images/edits, and responses with the image_generation tool. Use when the one-shot image helper is not enough - text-to-image, mask edits, multi-image batches, streaming, partial_images, and mixed text+image Responses flows. Reads .env and respects process environment variables; works with any OpenAI-compatible gateway.
Create or edit images with Pilio Nano Banana 2 through the unified Pilio developer API. Use when the user wants Nano Banana 2 text-to-image generation, reference-image editing, product posters, or image composition from local inputs.
Only to be triggered by explicit /parallel-task commands.
Query the OpenAI developer documentation via the OpenAI Docs MCP server using CLI (curl/jq). Use whenever a task involves the OpenAI API (Responses, Chat Completions, Realtime, etc.), OpenAI SDKs, ChatGPT Apps SDK, Codex, MCP integrations, endpoint schemas, parameters, limits, or migrations and you need up-to-date official guidance.
Orchestrate a configurable, multi-member CLI planning council (Codex, Claude Code, Gemini, OpenCode, or custom) to produce independent implementation plans, anonymize and randomize them, then judge and merge into one final plan. Use when you need a robust, bias-resistant planning workflow, structured JSON outputs, retries, and failure handling across multiple CLI agents.
Build and run Gemini 2.5 Computer Use browser-control agents with Playwright. Use when a user wants to automate web browser tasks via the Gemini Computer Use model, needs an agent loop (screenshot → function_call → action → function_response), or asks to integrate safety confirmation for risky UI actions.
Create and install Codex custom agent roles in ~/.codex/config.toml, generate role config files, enforce supported keys, and guide users through required role inputs (model, reasoning effort, developer_instructions).
Only to be triggered by explicit super-swarm-spark commands.
Only to be triggered by explicit /parallel-task-spark commands.
Self-referential completion loop for AI CLI tools. Re-runs the agent on the same task across turns with fresh context each iteration, until the completion promise is detected or max iterations is reached.
Orchestrates BMAD workflows for structured AI-driven development. Routes work across Analysis, Planning, Solutioning, and Implementation phases.
OpenContext를 활용한 AI 에이전트 영구 메모리 및 컨텍스트 관리. 세션/레포/날짜 간 컨텍스트 유지, 결론 저장, 문서 검색 워크플로우 제공.