Total 50,510 skills, AI & Machine Learning has 8479 skills
Showing 12 of 8479 skills
Gate every generation through a brand policy file.
Transform product photos via Picsart gen-ai — six modes.
Deterministic default-avatar generator per user.
Use when the user says "get started with Cekura", "set up Cekura", "onboard to Cekura", "I'm new to Cekura", "help me set up my agent", "how do I use Cekura", "walk me through Cekura", "configure my project", "first time using Cekura", or needs guidance on initial platform setup. Covers two onboarding paths: **testing** (default — build evaluators and run simulated calls) and **observability** (ingest production call logs and evaluate them).
Use when the user asks to "create a metric", "write a metric", "design a metric", "build a metric for", "evaluate agent performance", "measure call quality", "track a KPI", "add a workflow metric", "improve my metric", "fix a metric", "debug metric results", "set up quality scoring", or "what metrics do I need". Also relevant when discussing LLM judge prompts, custom code metrics, evaluation triggers, VALID_SKIP patterns, section extraction, or metric best practices for Cekura voice AI agents. Covers both creating new metrics and reviewing, iterating on, or troubleshooting existing ones.
Integrate the Agentic Commerce Protocol (ACP) for AI-driven commerce between buyers, agents, and businesses
Configure and use ktx to build an executable context layer for AI agents querying data warehouses with semantic layers, wiki knowledge, and approved metrics
Context layer for AI data agents - query warehouses accurately with semantic layers, metrics, and wiki knowledge through MCP
AI Agent learning roadmap and curated resources for building production-ready agents with modern patterns like Claude Code, OpenClaw, skills, MCP, and evaluation
Enable AI agents to safely make real-world merchant purchases using Snaplii's tokenized gift card payment layer with up to 10% savings.
Build modular Agentic RAG systems with LangGraph, featuring hierarchical indexing, conversation memory, and multi-agent query processing
Context layer for data agents - builds semantic layer, wiki, and warehouse metadata to enable accurate AI-powered analytics queries