clade-embeddings-search

Implement tool use (function calling) with Claude to let it execute actions, Use when working with embeddings-search patterns. query databases, call APIs, and interact with external systems. Trigger with "anthropic tool use", "claude function calling", "claude tools", "anthropic structured output with tools".

25 stars

Best use case

clade-embeddings-search is best used when you need a repeatable AI agent workflow instead of a one-off prompt.

Implement tool use (function calling) with Claude to let it execute actions, Use when working with embeddings-search patterns. query databases, call APIs, and interact with external systems. Trigger with "anthropic tool use", "claude function calling", "claude tools", "anthropic structured output with tools".

Teams using clade-embeddings-search should expect a more consistent output, faster repeated execution, less prompt rewriting.

When to use this skill

  • You want a reusable workflow that can be run more than once with consistent structure.

When not to use this skill

  • You only need a quick one-off answer and do not need a reusable workflow.
  • You cannot install or maintain the underlying files, dependencies, or repository context.

Installation

Claude Code / Cursor / Codex

$curl -o ~/.claude/skills/clade-embeddings-search/SKILL.md --create-dirs "https://raw.githubusercontent.com/ComeOnOliver/skillshub/main/skills/jeremylongshore/claude-code-plugins-plus-skills/clade-embeddings-search/SKILL.md"

Manual Installation

  1. Download SKILL.md from GitHub
  2. Place it in .claude/skills/clade-embeddings-search/SKILL.md inside your project
  3. Restart your AI agent — it will auto-discover the skill

How clade-embeddings-search Compares

Feature / Agentclade-embeddings-searchStandard Approach
Platform SupportNot specifiedLimited / Varies
Context Awareness High Baseline
Installation ComplexityUnknownN/A

Frequently Asked Questions

What does this skill do?

Implement tool use (function calling) with Claude to let it execute actions, Use when working with embeddings-search patterns. query databases, call APIs, and interact with external systems. Trigger with "anthropic tool use", "claude function calling", "claude tools", "anthropic structured output with tools".

Where can I find the source code?

You can find the source code on GitHub using the link provided at the top of the page.

SKILL.md Source

# Anthropic Tool Use (Function Calling)

## Overview
Tool use lets Claude call functions you define — query databases, hit APIs, read files, do math. Claude decides when to call a tool, you execute it, and feed the result back. This is how you build Claude-powered agents.

> **Note:** Anthropic does not offer an embeddings API. For embeddings + vector search, pair Claude with a dedicated embedding model (OpenAI, Cohere, or Voyage).

## Prerequisites
- Completed `clade-model-inference`
- Understanding of JSON Schema for tool definitions

## Instructions

### Step 1: Define Tools
```typescript
import Anthropic from '@claude-ai/sdk';

const client = new Anthropic();

const tools: Anthropic.Tool[] = [
  {
    name: 'get_weather',
    description: 'Get current weather for a city. Call this when the user asks about weather.',
    input_schema: {
      type: 'object',
      properties: {
        city: { type: 'string', description: 'City name, e.g. "San Francisco"' },
        unit: { type: 'string', enum: ['celsius', 'fahrenheit'], description: 'Temperature unit' },
      },
      required: ['city'],
    },
  },
];
```

### Step 2: Send Message with Tools
```typescript
const response = await client.messages.create({
  model: 'claude-sonnet-4-20250514',
  max_tokens: 1024,
  tools,
  messages: [{ role: 'user', content: "What's the weather in San Francisco?" }],
});

// Claude responds with stop_reason: 'tool_use'
// response.content includes a tool_use block:
// { type: 'tool_use', id: 'toolu_01...', name: 'get_weather', input: { city: 'San Francisco' } }
```

### Step 3: Execute Tool and Return Result
```typescript
// Find the tool use block
const toolUse = response.content.find(block => block.type === 'tool_use');

// Execute your function
const weatherData = await fetchWeather(toolUse.input.city);

// Send result back to Claude
const finalResponse = await client.messages.create({
  model: 'claude-sonnet-4-20250514',
  max_tokens: 1024,
  tools,
  messages: [
    { role: 'user', content: "What's the weather in San Francisco?" },
    { role: 'assistant', content: response.content },
    {
      role: 'user',
      content: [{
        type: 'tool_result',
        tool_use_id: toolUse.id,
        content: JSON.stringify(weatherData),
      }],
    },
  ],
});

console.log(finalResponse.content[0].text);
// "The weather in San Francisco is currently 65°F and partly cloudy."
```

## Python Example
```python
import anthropic

client = anthropic.Anthropic()

tools = [{
    "name": "get_weather",
    "description": "Get current weather for a city.",
    "input_schema": {
        "type": "object",
        "properties": {
            "city": {"type": "string"},
        },
        "required": ["city"],
    },
}]

response = client.messages.create(
    model="claude-sonnet-4-20250514",
    max_tokens=1024,
    tools=tools,
    messages=[{"role": "user", "content": "Weather in Paris?"}],
)

# Process tool_use blocks in response.content
for block in response.content:
    if block.type == "tool_use":
        result = execute_tool(block.name, block.input)
        # Send tool_result back...
```

## Agentic Tool Loop
```typescript
// Keep calling Claude until it stops requesting tools
let messages = [{ role: 'user', content: userInput }];

while (true) {
  const response = await client.messages.create({
    model: 'claude-sonnet-4-20250514',
    max_tokens: 4096,
    tools,
    messages,
  });

  // Add assistant response to conversation
  messages.push({ role: 'assistant', content: response.content });

  if (response.stop_reason === 'end_turn') {
    // Claude is done — extract final text
    const text = response.content.find(b => b.type === 'text')?.text;
    console.log(text);
    break;
  }

  // Execute all tool calls and send results
  const toolResults = [];
  for (const block of response.content) {
    if (block.type === 'tool_use') {
      const result = await executeTool(block.name, block.input);
      toolResults.push({
        type: 'tool_result',
        tool_use_id: block.id,
        content: JSON.stringify(result),
      });
    }
  }
  messages.push({ role: 'user', content: toolResults });
}
```

## Output
- `tool_use` content blocks with `name` and `input` when Claude wants to call a tool
- `stop_reason: "tool_use"` indicating Claude is waiting for tool results
- Final text response after all tool results are provided
- Complete agentic loop until `stop_reason: "end_turn"`

## Error Handling
| Error | Cause | Solution |
|-------|-------|----------|
| `invalid_request_error` | Bad tool schema | Validate JSON Schema. `input_schema` must be a valid JSON Schema object |
| `tool_use` with no matching name | Claude hallucinated a tool | Check `tool_use.name` against your defined tools before executing |
| `tool_result` mismatch | Wrong `tool_use_id` | Each `tool_result` must reference the exact `id` from the `tool_use` block |

## Examples
See Step 1 (tool definition), Step 2 (sending with tools), Step 3 (executing and returning results), and the full agentic tool loop example above.

## Resources
- [Tool Use Guide](https://docs.anthropic.com/en/docs/build-with-claude/tool-use)
- [Tool Use API Reference](https://docs.anthropic.com/en/api/messages)

## Next Steps
See `clade-common-errors` for error handling patterns.

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