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Autonomous Tool Discovery & Creation

AI agents can autonomously expand their capabilities by generating new tools when they encounter tasks beyond their current abilities. AVM sandboxes provide the isolated testing environment needed to safely validate these tools before committing them to the agent’s permanent toolkit.

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Power of Sandboxes

Sandboxes provide complete isolation for testing untrusted code. When an agent generates new tool code, it can execute that code in a sandbox without risking the agent’s stability, corrupting data, or affecting other running processes. Each test run happens in a fresh, isolated environment where failures are contained and don’t propagate to the main agent system.

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Why It Makes Agents Better

Without sandboxes, agents would need to either trust generated code blindly (risky) or require human validation for every new tool (slow). With sandboxes, agents can:

• Autonomously expand capabilities: Agents can identify missing functionality and create tools to fill gaps without human intervention
• Validate before committing: Test tools thoroughly in isolated environments before adding them to the permanent toolkit
• Iterate safely: Quickly test multiple implementations and edge cases without affecting the agent’s core functionality
• Build confidence: Verify tool correctness and handle errors gracefully before deployment

This enables truly autonomous agents that can adapt and grow their capabilities over time.

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Use Cases

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E-commerce Agents

Customer service agents that encounter new API integrations can generate and test custom data processing tools for specific e-commerce platforms.

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Business Intelligence Agents

Analytics agents that need custom data transformation tools can create, test, and validate new tools for specific business logic requirements.

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Content Processing Agents

Agents that process various content formats can autonomously create tools for new file types or processing requirements as they encounter them.

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Scenario: Dynamic Tool Creation

An agent is processing customer data but encounters a new data format it doesn’t have a tool for. Instead of failing or requesting human help, the agent generates Python code to handle the new format, tests it in a sandbox, validates the output, and then saves it as a reusable tool for future use.

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Implementation: Safe Tool Validation

1. Identify Need
   Agent encounters task requiring functionality not in current toolkit.

2. Generate Code
   Agent uses LLM to generate Python tool code for the required functionality.

3. Create Test Sandbox
   Agent creates a temporary sandbox for isolated testing.

4. Execute Tests
   Agent runs the generated code with test cases in the sandbox.

5. Validate Results
   Agent checks output correctness and error handling.

6. Create Tool
   If validation passes, agent creates permanent tool via AVM Tools API.

7. Reuse
   Agent can now use the validated tool in future tasks.

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Example (TypeScript)

import SandboxSDK from '@avmcodes/sandbox-sdk';
import { generateText } from 'ai';
import { openai } from '@ai-sdk/openai';

const client = new SandboxSDK({
  apiKey: process.env['SANDBOX_SDK_API_KEY'],
});

async function createAndValidateTool(taskDescription: string, testCases: any[]) {
  // Generate tool code using LLM
  const { text: toolCode } = await generateText({
    model: openai('gpt-4o'),
    prompt: `Write a Python function execute(input) that ${taskDescription}`,
  });

  // Create temporary sandbox for testing
  const sandbox = await client.sandboxes.create({
    name: 'Tool Validation Sandbox',
  });

  try {
    // Test the generated code
    const testResults = await Promise.all(
      testCases.map(testCase =>
        client.sandboxes.execute(sandbox.id, {
          command: `python -c "${toolCode.replace(/"/g, '\\"')}"`,
          env: { INPUT: JSON.stringify(testCase.input) },
        })
      )
    );

    // Validate all tests passed
    const allPassed = testResults.every(
      result => result.status === 'completed' && result.exit_code === 0
    );

    if (allPassed) {
      // Create permanent tool via Tools API
      // Tool creation would happen here via API
      console.log('Tool validated successfully');
      return toolCode;
    } else {
      throw new Error('Tool validation failed');
    }
  } finally {
    // Clean up test sandbox
    // Sandbox cleanup would happen here
  }
}

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Next Steps

• Integrate tool creation API for automatic tool registration
• Add versioning support for tool iterations
• Implement tool dependency management
• Build tool testing frameworks for agents