Two Approaches to Helping AI Agents Use Your API (And Why You Need Both) - Qdrant

This post introduces two complementary approaches for enabling AI agents to effectively use APIs: SKILL.md for providing static, pre-computed knowledge about API usage (known unknowns) and a REPL-first approach for dynamic, interactive discovery of the API's current state (unknown unknowns). It details how these methods address distinct failure modes in agentic API interaction and proposes a combined workflow where agents first consult SKILL.md for guidance on correct API usage (e.g., deprecated methods, anti-patterns) and then use a REPL to explore the live environment (e.g., list collections, inspect schemas) before generating code. The post provides implementation details for a Qdrant REPL tool and discusses the broader applicability of this pattern to any API with deprecated methods or user-specific state.