> ## Documentation Index
> Fetch the complete documentation index at: https://docs.upsonic.ai/llms.txt
> Use this file to discover all available pages before exploring further.

# Auto-Selection

> Automatically select the most relevant skills for each task using embeddings

## Overview

When you have many skills loaded, auto-selection uses embedding similarity to pick only the most relevant ones for each task. This keeps the agent's system prompt lean and focused.

## Usage

```python theme={null}
from upsonic import Agent
from upsonic.skills import Skills, LocalSkills

skills = Skills(
    loaders=[LocalSkills("./many-skills")],  # Directory with 20+ skills
    auto_select=True,
    max_skills=5,
    embedding_provider=my_embedding_provider,
)

agent = Agent(
    model="anthropic/claude-sonnet-4-6",
    name="Agent",
    role="Versatile Assistant",
    goal="Handle diverse tasks with the right expertise",
    skills=skills,
)

# Only the 5 most relevant skills appear in the system prompt
result = agent.print_do("Analyze the sales data from Q4.")
```

## How It Works

1. Skill descriptions and the task description are converted to embedding vectors
2. Cosine similarity is computed between each skill's description and the task
3. The top `max_skills` skills are included in the system prompt

Without auto-select, **all** loaded skills appear in the system prompt regardless of relevance.

<Info>
  If auto-select fails (e.g. embedding provider error), it falls back to returning the first `max_skills` skills in load order.
</Info>

## Parameters

| Parameter            | Type   | Default | Description                                |
| -------------------- | ------ | ------- | ------------------------------------------ |
| `auto_select`        | `bool` | `False` | Enable embedding-based skill selection     |
| `max_skills`         | `int`  | `5`     | Maximum skills to include in system prompt |
| `embedding_provider` | object | `None`  | Provider with `embed_texts()` method       |