Skill Content Tools

Lightweight tools for LLMs to access skill content through function calling. Use when skills contain only reference content (no scripts to execute).

For skills with executable scripts, use Sandbox Tools with mounted skills instead.

Available Tools

Tool	Description
`get_skill`	Get skill metadata and file index
`get_skill_file`	Read a file from a skill

Quick Start

import json
import os
from acontext import AcontextClient
from acontext.agent.skill import SKILL_TOOLS
from openai import OpenAI

client = AcontextClient(api_key=os.getenv("ACONTEXT_API_KEY"))
openai_client = OpenAI()

# Preload skills by UUID
skill_ids = ["uuid-of-skill-1", "uuid-of-skill-2"]
ctx = SKILL_TOOLS.format_context(client, skill_ids)

tools = SKILL_TOOLS.to_openai_tool_schema()
skills_context = ctx.get_context_prompt()

messages = [
    {"role": "system", "content": f"You have skill access.\n\n{skills_context}"},
    {"role": "user", "content": "What guidelines are in the internal-comms skill?"}
]

# Agent loop
while True:
    response = openai_client.chat.completions.create(
        model="gpt-4.1", messages=messages, tools=tools
    )
    message = response.choices[0].message
    messages.append(message)

    if not message.tool_calls:
        print(f"Assistant: {message.content}")
        break

    for tc in message.tool_calls:
        result = SKILL_TOOLS.execute_tool(ctx, tc.function.name, json.loads(tc.function.arguments))
        messages.append({"role": "tool", "tool_call_id": tc.id, "content": result})

import { AcontextClient, SKILL_TOOLS } from '@acontext/acontext';
import OpenAI from 'openai';

const client = new AcontextClient({
    apiKey: process.env.ACONTEXT_API_KEY,
});
const openai = new OpenAI();

// Preload skills by UUID
const skillIds = ["uuid-of-skill-1", "uuid-of-skill-2"];
const ctx = await SKILL_TOOLS.formatContext(client, skillIds);

const tools = SKILL_TOOLS.toOpenAIToolSchema();
const skillsContext = ctx.getContextPrompt();

const messages: OpenAI.ChatCompletionMessageParam[] = [
    { role: "system", content: `You have skill access.\n\n${skillsContext}` },
    { role: "user", content: "What guidelines are in the internal-comms skill?" },
];

// Agent loop
while (true) {
    const response = await openai.chat.completions.create({
        model: "gpt-4.1",
        messages,
        tools,
    });
    const message = response.choices[0].message;
    messages.push(message);

    if (!message.tool_calls) {
        console.log(`Assistant: ${message.content}`);
        break;
    }

    for (const tc of message.tool_calls) {
        const result = await SKILL_TOOLS.executeTool(ctx, tc.function.name, JSON.parse(tc.function.arguments));
        messages.push({ role: "tool", tool_call_id: tc.id, content: result });
    }
}

Context Prompt

The context includes available skills as XML:

<available_skills>
<skill>
<name>data-extraction</name>
<description>Extract structured data from documents</description>
</skill>
</available_skills>

Tool Reference

get_skill

{"skill_name": "data-extraction"}

Returns: Skill ID, description, and file index with MIME types.

get_skill_file

{"skill_name": "data-extraction", "file_path": "SKILL.md"}

Returns: File content (text) or presigned URL (binary).

Read-only: These tools can only read skill content. To execute skill scripts, use Sandbox Tools.

Next Steps

Skills API

Upload and manage skills

Sandbox Tools

Execute skill scripts

Skill Memory

Build skills from agent sessions