Tool Calling
The capability of a large-language-model (LLM) to interface with external software, APIs, or datasets to execute actions or retrieve real-time information. Often implemented via Function Calling, where the model generates structured arguments to trigger specific code execution.
Core Concepts
- Function Calling: The mechanism by which an LLM identifies the need for an external tool and produces the necessary parameters (e.g., JSON) for execution.
- agentic-ai: Higher-level autonomous systems that utilize tool calling to navigate complex, multi-step workflows and environmental interactions.
- Extensibility: The ability to augment model reasoning with live, ecosystem-specific data.
Implementation & Examples
- gemini: Demonstrates advanced tool calling through native google-workspace integration.
- Workspace Integration: Leverages the
@symbol syntax to bridge LLM reasoning with live data from Gmail, Docs, and Drive. - Ecosystem Synergy: Uses native integration to act as an interface for the broader Google ecosystem.
- Workspace Integration: Leverages the
Source: 2026 04 14 New Gemini Tutorial
Source Notes
- 2026-04-14: “But OpenClaw is expensive…”
- 2026-04-07: OWASP Top 10 Security Risks for AI Agentic Applications Report · ▶ source
- 2026-04-13: Ollama and Zapier MCP Local LLM AI Agent Setup and Integration · ▶ source
- 2026-04-27: Claude AI · ▶ source
- 2026-04-29: OpenClaw · ▶ source
- 2026-05-01: Claude AI Productivity: Seven Secret Prompts Summary Report · ▶ source