tools

Connecting an LLM application to external services via their APIs, enabling the model to read data from or trigger actions in other systems. API integration is how LLMs access the broader software eco...

Also: External API, Third-Party Integration, Service Integration

An API feature that allows LLMs to output structured function invocations rather than (or in addition to) natural language. The model is given function definitions (name, parameters, descriptions), an...

Also: Function Call, Tool Calling API

An API setting that constrains model output to be valid JSON, without specifying a particular schema. JSON mode guarantees parseable JSON but not any specific structure—the model chooses the keys and ...

Also: JSON Output Mode, JSON Response Format

An open protocol that standardizes how AI applications connect to external data sources and tools. MCP defines a client-server architecture where AI applications (clients) connect to MCP servers that ...

Also: MCP, Anthropic MCP

A software component that adds functionality to a host application without modifying its core code. In AI systems, plugins typically expose new tools, data sources, or integrations that agents can u...

Also: Extension, Add-on, Module

A packaged, reusable capability that can be loaded into an AI agent or coding assistant to provide specialized knowledge, workflows, or tool access for a specific domain or task. Skills encapsulate ...

Also: Agent Skill, Capability Module, Reusable Capability

Constraining an LLM's output to conform to a specified structure, typically a JSON Schema. Unlike free-form text generation, structured output guarantees the response matches a defined format—valid JS...

Also: Structured Generation, Constrained Output, Schema-Constrained Output

The process of connecting tool definitions to their implementations and making them available to an LLM or agent. Binding involves: defining the tool schema, implementing the execution logic, register...

Also: Tool Registration, Tool Configuration

A structured description of a tool that tells an LLM what the tool does, what inputs it accepts, and what outputs it produces. Tool definitions typically include: name, description (natural language),...

Also: Tool Schema, Function Definition, Tool Specification

The output returned after executing a tool invocation, which is then provided back to the LLM for incorporation into its reasoning or response. Tool results close the loop in tool use: model requests ...

Also: Function Result, Tool Output, Tool Response

The capability of an LLM to invoke external functions, APIs, or services to perform actions or retrieve information beyond text generation. Tool use extends LLMs from knowledge systems to action syste...

Also: Tool Usage, Tool Calling, External Tools