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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.

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Usage

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.")

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

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Parameters

ParameterTypeDefaultDescription
auto_selectboolFalseEnable embedding-based skill selection
max_skillsint5Maximum skills to include in system prompt
embedding_providerobjectNoneProvider with embed_texts() method