Total 56,856 skills, AI & Machine Learning has 9454 skills
Showing 12 of 9454 skills
Audit token waste across agent systems (Claude Code, OpenClaw, Hermes, OpenCode). Detect idle burns, model misrouting, and config bloat with dollar savings.
Initialize the memory system in the current directory, generating CLAUDE.md (optional AGENT.md for Cursor), MEMORY.md, and the memory/ directory. Triggered when the user says "initialize memory", "set up memory", "memory init", or "/memory-init".
Generate photorealistic digital twins and avatar clones using each::sense AI. Create AI-powered digital representations for video calls, corporate communications, customer service, and multilingual content.
Discover PUDA experiment workflows for bears and choose the right experiment for the task. Use when you need to run, set up, or understand a PUDA experiment such as colour mixing optimization.
Read production traces, identify what's failing, and build failure taxonomies using open coding and axial coding methodology. Use when debugging agent or pipeline quality, investigating "why are my outputs bad?", or before building any evaluator — error analysis must come first. Do NOT use when you already have identified failure modes and need evaluators (use build-evaluator) or datasets (use generate-synthetic-dataset).
Interactive lesson-level quiz for Claude Code tutorials. Tests understanding of a specific lesson (01-10) with 8-10 questions mixing conceptual and practical knowledge. Use before a lesson to pre-test, during to check progress, or after to verify mastery. Use when asked to "quiz me on hooks", "test my knowledge of lesson 3", "lesson quiz", "practice quiz for MCP", or "do I understand skills".
Coordinate parallel feature development with file ownership strategies, conflict avoidance rules, and integration patterns for multi-agent implementation. Use this skill when decomposing features for parallel development, establishing file ownership boundaries, or managing integration between parallel work streams.
Multi-agent workflow examples to work together on the OpenServ Platform. Covers agent discovery, multi-agent workspaces, task dependencies, and workflow orchestration using the Platform Client. Read reference.md for the full API reference. Read openserv-agent-sdk and openserv-client for building and running agents.
Generate extractive summaries from long text documents. Control summary length, extract key sentences, and process multiple documents.
Complete guide to using @openserv-labs/client for managing agents, workflows, triggers, and tasks on the OpenServ Platform. Covers provisioning, authentication, x402 payments, ERC-8004 on-chain identity, and the full Platform API. IMPORTANT - Always read the companion skill openserv-agent-sdk alongside this skill, as both packages are required to build any agent. Read reference.md for the full API reference.
Retrieval-augmented generation (RAG) skill for the D&D 5e System Reference Document (SRD). Use when answering questions about D&D 5e core rules, spells, combat, equipment, conditions, monsters, and other SRD content. This skill provides agentic search-based access to the SRD split into page-range markdown files.
Model Context Protocol (MCP) server implementation patterns with LangChain4j. Use when building MCP servers to extend AI capabilities with custom tools, resources, and prompt templates.