What problem does it solve? Building AI applications requires managing prompts, knowledge bases, model calls, and observability across environments. This Skill provides the integration knowledge for ByteDance's Fornax AI Agent Ops platform, covering SDK setup, authentication, and usage patterns in Golang, Python, and Node.js. ## Core Features & Use Cases - Prompt as a Service: Pull published Prompt templates from Prompt Hub, render variables, and execute synchronously or via streaming in remote or local execution modes. - RAG Knowledge Retrieval: Query Fornax-managed knowledge bases with configurable channels, TopK, and score thresholds. - Trace Observability: Auto-report OpenTelemetry-based traces, create custom spans, and force-flush data before process exit. - OpenAPI Authentication: Issue JWT tokens via AKSK signing for Prompt Hub, PTaaS, dataset, and annotation job APIs. - Use Case: A backend developer integrating a travel-assistant prompt into a Go microservice initializes the Fornax client once, executes the published prompt with variables, and monitors token usage and latency in the Fornax observability console. ## Quick Start Use the fornax-knowledge skill to show me how to initialize the Fornax Python SDK and execute a published prompt with variables.