## Prerequisites ## Choosing a model ## Specifying client tools ### Tool use system prompt ### Best practices for tool definitions ## Providing tool use examples ### Basic usage ### Requirements and limitations ## Controlling Claude's output ### Forcing tool use ### Model responses with tools ## Next steps
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---
title: Define tools
url: https://platform.claude.com/docs/en/agents-and-tools/tool-use/define-tools
description: Specify tool schemas, write effective descriptions, and control when Claude calls your tools.
---
## Prerequisites
* Familiarity with the [tool use overview](https://platform.claude.com/docs/en/agents-and-tools/tool-use/overview)
* A Claude API key and a working SDK or cURL setup
## Choosing a model
Use the latest Claude Opus model, Claude Opus 5, for complex tools and ambiguous queries; it handles multiple tools better and seeks clarification when needed.
Use Claude Haiku models for straightforward tools, but note they may infer missing parameters.
<Tip>
If using Claude with tool use and thinking, see [Thinking](https://platform.claude.com/docs/en/build-with-claude/thinking) for more information.
</Tip>
## Specifying client tools
Client tools (both Anthropic-schema and user-defined) are specified in the `tools` top-level parameter of the API request. Each tool definition includes:
| Parameter | Description |
| ---------------- | -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `name` | The name of the tool. Must match the regex `^[a-zA-Z0-9_-]{1,64}$`. |
| `description` | A detailed plaintext description of what the tool does, when it should be used, and how it behaves. |
| `input_schema` | A [JSON Schema](https://json-schema.org/) object defining the expected parameters for the tool. |
| `input_examples` | (Optional) An array of example input objects to help Claude understand how to use the tool. See [Providing tool use examples](https://platform.claude.com/docs/en/agents-and-tools/tool-use/define-tools#providing-tool-use-examples). |
For the full set of optional properties available on any tool definition, including `cache_control`, `strict`, `defer_loading`, and `allowed_callers`, see the [Tool reference](https://platform.claude.com/docs/en/agents-and-tools/tool-use/tool-reference#tool-definition-properties).
<Accordion title="Example simple tool definition">
```json JSON
{
"name": "get_weather",
"description": "Get the current weather in a given location",
"input_schema": {
"type": "object",
"properties": {
"location": {
"type": "string",
"description": "The city and state, e.g. San Francisco, CA"
},
"unit": {
"type": "string",
"enum": ["celsius", "fahrenheit"],
"description": "The unit of temperature, either 'celsius' or 'fahrenheit'"
}
},
"required": ["location"]
}
}
```
This tool, named `get_weather`, expects an input object with a required `location` string and an optional `unit` string that must be either "celsius" or "fahrenheit".
</Accordion>
### Tool use system prompt
When you call the Claude API with the `tools` parameter, the API constructs a special system prompt from the tool definitions, tool configuration, and any user-specified system prompt. The constructed prompt is designed to instruct the model to use the specified tool(s) and provide the necessary context for the tool to operate properly:
```text wrap
In this environment you have access to a set of tools you can use to answer the user's question.
{{ FORMATTING INSTRUCTIONS }}
String and scalar parameters should be specified as is, while lists and objects should use JSON format. Note that spaces for string values are not stripped. The output is not expected to be valid XML and is parsed with regular expressions.
Here are the functions available in JSONSchema format:
{{ TOOL DEFINITIONS IN JSON SCHEMA }}
{{ USER SYSTEM PROMPT }}
{{ TOOL CONFIGURATION }}
```
### Best practices for tool definitions
To get the best performance out of Claude when using tools, follow these guidelines:
* **Provide extremely detailed descriptions.** This is by far the most important factor in tool performance. Your descriptions should explain every detail about the tool, including:
* What the tool does
* When it should be used (and when it shouldn't)
* What each parameter means and how it affects the tool's behavior
* Any important caveats or limitations, such as what information the tool does not return if the tool name is unclear. The more context you can give Claude about your tools, the better it will be at deciding when and how to use them. Aim for at least 3–4 sentences for each tool description, more if the tool is complex.
* **Prioritize descriptions, but consider using `input_examples` for complex tools.** Clear descriptions are most important, but for tools with complex inputs, nested objects, or format-sensitive parameters, you can use the `input_examples` field to provide schema-validated examples. See [Providing tool use examples](https://platform.claude.com/docs/en/agents-and-tools/tool-use/define-tools#providing-tool-use-examples) for details.
* **Consolidate related operations into fewer tools.** Rather than creating a separate tool for every action (`create_pr`, `review_pr`, `merge_pr`), group them into a single tool with an `action` parameter. Fewer, more capable tools reduce selection ambiguity and make your tool surface easier for Claude to navigate.
* **Use meaningful namespacing in tool names.** When your tools span multiple services or resources, prefix names with the service (for example, `github_list_prs`, `slack_send_message`). This makes tool selection unambiguous as your library grows, and is especially important when using [tool search](https://platform.claude.com/docs/en/agents-and-tools/tool-use/tool-search-tool).
* **Design tool responses to return only high-signal information.** Return semantic, stable identifiers (for example, slugs or UUIDs) rather than opaque internal references, and include only the fields Claude needs to reason about its next step. Bloated responses waste context and make it harder for Claude to extract what matters.
<AccordionGroup>
<Accordion title="Example of a good tool description">
```json JSON
{
"name": "get_stock_price",
"description": "Retrieves the current stock price for a given ticker symbol. The ticker symbol must be a valid symbol for a publicly traded company on a major US stock exchange like NYSE or NASDAQ. The tool will return the latest trade price in USD. It should be used when the user asks about the current or most recent price of a specific stock. It will not provide any other information about the stock or company.",
"input_schema": {
"type": "object",
"properties": {
"ticker": {
"type": "string",
"description": "The stock ticker symbol, e.g. AAPL for Apple Inc."
}
},
"required": ["ticker"]
}
}
```
</Accordion>
<Accordion title="Example poor tool description">
```json JSON
{
"name": "get_stock_price",
"description": "Gets the stock price for a ticker.",
"input_schema": {
"type": "object",
"properties": {
"ticker": {
"type": "string"
}
},
"required": ["ticker"]
}
}
```
</Accordion>
</AccordionGroup>
The good description clearly explains what the tool does, when to use it, what data it returns, and what the `ticker` parameter means. The poor description is too brief and leaves Claude with many open questions about the tool's behavior and usage.
<Tip>
For deeper guidance on tool design (consolidation, naming, and response shaping), see [Writing tools for agents](https://www.anthropic.com/engineering/writing-tools-for-agents).
</Tip>
## Providing tool use examples
You can provide concrete examples of valid tool inputs to help Claude understand how to use your tools more effectively. This is particularly useful for complex tools with nested objects, optional parameters, or format-sensitive inputs.
### Basic usage
Add an optional `input_examples` field to your tool definition with an array of example input objects. Each example must be valid according to the tool's `input_schema`:
<CodeGroup>
```bash cURL
curl -sS https://api.anthropic.com/v1/messages \
-H "content-type: application/json" \
-H "x-api-key: $ANTHROPIC_API_KEY" \
-H "anthropic-version: 2023-06-01" \
-d @- <<'EOF'
{
"model": "claude-opus-5",
"max_tokens": 1024,
"tools": [
{
"name": "get_weather",
"description": "Get the current weather in a given location",
"input_schema": {
"type": "object",
"properties": {
"location": {
"type": "string",
"description": "The city and state, e.g. San Francisco, CA"
},
"unit": {
"type": "string",
"enum": ["celsius", "fahrenheit"],
"description": "The unit of temperature"
}
},
"required": ["location"]
},
"input_examples": [
{"location": "San Francisco, CA", "unit": "fahrenheit"},
{"location": "Tokyo, Japan", "unit": "celsius"},
{"location": "New York, NY"}
]
}
],
"messages": [
{"role": "user", "content": "What's the weather like in San Francisco?"}
]
}
EOF
```
```bash CLI
ant messages create <<'YAML'
model: claude-opus-5
max_tokens: 1024
tools:
- name: get_weather
description: Get the current weather in a given location
input_schema:
type: object
properties:
location:
type: string
description: The city and state, e.g. San Francisco, CA
unit:
type: string
enum: [celsius, fahrenheit]
description: The unit of temperature
required: [location]
input_examples:
- location: San Francisco, CA
unit: fahrenheit
- location: Tokyo, Japan
unit: celsius
- location: New York, NY # 'unit' is optional
messages:
- role: user
content: What's the weather like in San Francisco?
YAML
```
```python Python
client = anthropic.Anthropic()
response = client.messages.create(
model="claude-opus-5",
max_tokens=1024,
tools=[
{
"name": "get_weather",
"description": "Get the current weather in a given location",
"input_schema": {
"type": "object",
"properties": {
"location": {
"type": "string",
"description": "The city and state, e.g. San Francisco, CA",
},
"unit": {
"type": "string",
"enum": ["celsius", "fahrenheit"],
"description": "The unit of temperature",
},
},
"required": ["location"],
},
"input_examples": [
{"location": "San Francisco, CA", "unit": "fahrenheit"},
{"location": "Tokyo, Japan", "unit": "celsius"},
{
"location": "New York, NY" # 'unit' is optional
},
],
}
],
messages=[{"role": "user", "content": "What's the weather like in San Francisco?"}],
)
print(response)
```
```typescript TypeScript
const client = new Anthropic();
const response = await client.messages.create({
model: "claude-opus-5",
max_tokens: 1024,
tools: [
{
name: "get_weather",
description: "Get the current weather in a given location",
input_schema: {
type: "object",
properties: {
location: {
type: "string",
description: "The city and state, e.g. San Francisco, CA"
},
unit: {
type: "string",
enum: ["celsius", "fahrenheit"],
description: "The unit of temperature"
}
},
required: ["location"]
},
input_examples: [
{
location: "San Francisco, CA",
unit: "fahrenheit"
},
{
location: "Tokyo, Japan",
unit: "celsius"
},
{
location: "New York, NY"
// Demonstrates that 'unit' is optional
}
]
}
],
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