Learning path · Tools & MCP · 68
Tool Calling
Pattern where models emit structured calls to external tools—APIs, databases, code—instead of only natural language.
Why it matters
- Turns reasoning into action with auditable interfaces.
- Core bridge between LLM and enterprise systems.
- Schema design quality determines reliability.
Key ideas
- Structured invocations
- Tool schemas
- Result feedback
Tool calling extends the LLM with hands: search tickets, run SQL, create calendar events. Define tools with strict JSON schemas, human-readable descriptions, and idempotency hints. Feed results back as tool messages in the conversation. Validate outputs before executing side effects—never trust raw model JSON for destructive operations without checks. Wrap destructive tools with confirmation tokens tied to human approvals or risk-scored automation policies. Ship only after eval gates pass on representative production failures.
Updated 2026-08-09 · Full learning path