Technology
Tool calling reliability
Tool calling reliability is the consistency with which an LLM correctly invokes external functions with valid parameters — vs. malformed JSON, wrong tool, hallucinated parameters. Frontier models (Claude 4.5, GPT-4o) hit 95-98% reliability; older models below 80%.
More detail
Strategies to improve reliability: (1) clear tool descriptions with examples, (2) structured outputs with JSON schema validation, (3) limit available tools per task to 3-5 (more = confusion), (4) provide few-shot examples of correct tool calls, (5) retry on validation failure with the error message embedded. Aiprosol's agents each have <8 tools available, scoped to their role.