Glossary

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Glossary / Evaluation and implementation guide

Function Calling

Function calling, also called tool calling, is a model capability where an AI outputs a structured request to execute a predefined function instead of plain text.

Your application receives the request, validates it, runs the actual operation (an API call, database update, or internal script), and returns the result to the model. The model never executes code itself; your infrastructure does.

A practical example

Example: an agent asked to "reschedule the demo for Thursday" returns a function call with arguments like event_id and new_time.

Your system validates the arguments against your calendar API, executes the update, and feeds confirmation back to the model.

What to evaluate before investing

  • Test how the vendor handles invalid or hallucinated arguments, such as nonexistent IDs, and whether you can enforce schemas and validation rules.
  • Ask whether tool selection can be constrained per agent or workflow, limiting which functions a given agent may invoke.
  • Verify observability: can you log every function call with inputs, outputs, and latency for auditing and debugging?

Limitations and tradeoffs

Function calling reliability varies by model and task complexity; ambiguous instructions or too many similar tools increase wrong selections, so workflows need guardrails, confirmation steps, and human approval for irreversible actions.

Plan your next step with MeshLine

Connect this decision to your automation, organic marketing and customer lifecycle management. In a MeshLine demo, discuss your existing tools, the scope you need and how to measure the result.