tool-use

Name: tool-use
Availability: InStock
Author: Entelligentsia

Orchestrate external tool calls for LLMs with defined schemas and error handling.

1|1|Updated Mar 30, 2026

Search Tags:#error-handling #api-integration #tool-use #function-calling #llm-safety #execution-loop

Ready to run

npx skills add https://github.com/Entelligentsia/skillforge --skill tool-use-entelligentsia

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: tool-use
Source: https://github.com/Entelligentsia/skillforge/tree/main/llm-patterns/skills/tool-use
Command: npx skills add https://github.com/Entelligentsia/skillforge --skill tool-use-entelligentsia

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

LLMs often struggle to obtain live data or perform actions that require external systems. This Skill defines tools and an execution model so the LLM can delegate work to deterministic functions rather than executing code itself, enabling reliable data retrieval, calculations, and side effects.

Core Features & Use Cases

Tool definitions: name, description, and input schema for clear selection criteria.
Execution loop: orchestrates tool calls, runs handlers, and returns results to the model.
Safety boundaries: automatic risk classification and prompts to confirm destructive actions.
Error handling: returns structured errors for retry or fallback, preventing silent failures.
Use Case: Build a chatbot that can check inventory, fetch order status, or trigger a job via an API based on user intent.

Quick Start

Describe the user's goal and let the system select and execute the appropriate tools to fulfill it.

Frequently Asked Questions about tool-use

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I safely orchestrate external API calls for LLMs?▼

Safely orchestrate external API calls by defining explicit tools with input schemas and using an execution loop that runs handlers, applies risk classification, and returns structured errors to prevent silent failures.

What is the best way to handle errors during LLM function calling?▼

Handle errors during LLM function calling by returning structured errors from the execution loop, allowing the model to retry the tool call or trigger a fallback response without silent failures.

Can I use LLM tool use to fetch live data from databases and files?▼

You can use LLM tool use to fetch live data from databases and files by defining deterministic functions as tools, allowing the model to delegate retrieval tasks rather than generating data itself.

How do I prevent destructive actions when an LLM triggers side effects?▼

Prevent destructive actions when an LLM triggers side effects by applying automatic risk classification to tool calls and prompting for user confirmation before executing high-risk operations.

Do I need explicit tool definitions for LLM API integration?▼

You need explicit tool definitions for LLM API integration to provide clear selection criteria, specifying the tool name, description, and input schema so the model can accurately delegate work to deterministic functions.

Why does my LLM execution loop fail to return API results to the model?▼

An LLM execution loop fails to return API results if tool handlers do not pass structured outputs back to the model, a step required to inform subsequent text generation or further tool calls.