Total 58,116 skills, AI & Machine Learning has 9659 skills
Showing 12 of 9659 skills
Build complex AI systems with declarative programming, optimize prompts automatically, create modular RAG systems and agents with DSPy - Stanford NLP's framework for systematic LM programming
Complete setup for automated agent-driven development. Define features as user stories with testable acceptance criteria, then run AI agents in a loop until all stories pass.
Provides comprehensive guidance for Midjourney AI image generation including prompt engineering, image generation, parameters, and best practices. Use when the user asks about Midjourney, needs to generate AI images, create prompts, or work with Midjourney features.
Autonomous multi-round research review loop. Repeatedly reviews via Codex MCP, implements fixes, and re-reviews until positive assessment or max rounds reached. Use when user says "auto review loop", "review until it passes", or wants autonomous iterative improvement.
Open source harness for generating 3D CAD models from text using AI coding agents with build123d/OpenCascade, exporting STEP/STL/URDF, and previewing in a local CAD Explorer viewer.
Use learned patterns and current state to predict the optimal next action
Creates new Claude Code skills following repository conventions with proper structure, frontmatter, workflows, code examples, and reference files. Use when users request "create a skill", "new skill", "generate skill", or "add skill to collection".
Api4ai integration. Manage Leads, Persons, Organizations, Deals, Projects, Pipelines and more. Use when the user wants to interact with Api4ai data.
Orchestrator that runs first for lead generation requests. Gathers business context via website analysis or questions, identifies competitors, builds ICP, and routes to signal skills with pre-filled inputs.
Eval enablement accelerator — help customers think through "what does good look like" for their AI agent, then generate a structured eval plan and test cases they can use immediately. No running agent required. Works from a description, an idea, or even a vague goal. Use when anyone mentions agent evaluation, eval planning, "what should we test", "how do we know if the agent is good", test case generation, or interpreting eval results.
Restore session state from handoff artifacts and route to the next action. Priority cascade: HANDOFF.json (highest) > .continue-here.md > incomplete task_plan.md > git log. Presents a status dashboard, then executes the next action. Use for "resume", "continue", "pick up where I left off", "what was I doing", "continue work". Do NOT use for starting new tasks (use /do), reviewing past sessions (use /retro), or reading task plans (read task_plan.md directly).
Analyze images — segment objects, detect, run OCR, describe, and answer visual questions via fal.ai vision models.