Total 50,313 skills, AI & Machine Learning has 8452 skills
Showing 12 of 8452 skills
AI design workflow with DESIGN.md, anti-patterns, and optional Stitch MCP
Watch a tutorial, demo, or walkthrough video and generate a Claude Code skill from it. Extracts the workflow, commands, tools, and patterns demonstrated and produces a SKILL.md with implementation. Supports Loom, YouTube, and local files.
Selects a base model and fine-tuning technique (SFT, DPO, or RLVR) for the user's use case by querying SageMaker Hub. Use when the user asks which model or technique to use, wants to start fine-tuning, or mentions a model name or family (e.g., "Llama", "Mistral") — always activate even for known model names because the exact Hub model ID must be resolved. Queries available models, validates technique compatibility, and confirms selections.
Validates dataset formatting and quality for SageMaker model fine-tuning (SFT, DPO, or RLVR). Use when the user says "is my dataset okay", "evaluate my data", "check my training data", "I have my own data", or before starting any fine-tuning job. Detects file format, checks schema compliance against the selected model and technique, and reports whether the data is ready for training or evaluation.
Creates a reusable use case specification file that defines the business problem, stakeholders, and measurable success criteria for model customization, as recommended by the AWS Responsible AI Lens. Use as the default first step in any model customization plan. Skip only if the user explicitly declines or already has a use case specification to reuse. Captures problem statement, primary users, and LLM-as-a-Judge success tenets.
Generates a Jupyter notebook that fine-tunes a base model using SageMaker serverless training jobs. Use when the user says "start training", "fine-tune my model", "I'm ready to train", or when the plan reaches the finetuning step. Supports SFT, DPO, and RLVR trainers, including RLVR Lambda reward function creation.
Use when reporting progress in autonomous loop iterations. Triggers at the end of every autonomous loop iteration, when the autonomous-loop skill completes a BUILD phase, when progress reporting is needed for monitoring or exit evaluation, or when producing machine-parseable RALPH_STATUS blocks with exit signal protocol.
Standalone squad manager — creates, inspects, validates, and manages squads (multi-agent teams). Scaffolds directories, agents, tasks, workflows. Registers squads for slash commands. Works independently without AIOS. Activates on: create squad, list squads, add agent, validate squad, run workflow, inspect squad, manage squad.
Document a recently solved problem to compound your team's knowledge
Send physical mail (letters and postcards) in the US via PostalForm using x402 USDC payments on Base from the awal agent wallet. Use when the user asks to send mail, post a letter, mail a document, send a postcard, mail a PDF, send physical mail, or "mail it to [someone]". Supports user-provided PDFs, auto-generation from text, and AI image generation for postcards via fal.ai (also paid with x402). Recipient must be in the US. Single recipient per send.
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".
Generate UGC-style (User Generated Content) lifestyle photos of a person wearing or using your product — authentic, relatable, social-media-native imagery.