smithery.ai

backend-safety-integrator

Guide for integrating safety validation into new inference backends

First seen May 2, 2026

Installation

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Package contents

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  • skill md SKILL.md 4,189 B
  • docs SUMMARY.md 100 B

History

  1. First seen on skills.sh
  2. First recorded snapshot · 1 installs

SKILL.md

Backend Safety Integrator Skill

Purpose: Systematically integrate safety validation when adding new LLM inference backends to Caro.

When to Use:

  • Adding a new inference backend (MLX, Anthropic API, OpenAI, etc.)
  • Updating existing backend safety integration
  • Ensuring backend calls safety validator before execution

Duration: 2-4 hours depending on backend complexity


The 6-Phase Integration Workflow

Phase 1: Understand Backend Architecture (30 min)
Phase 2: Identify Command Generation Point (30 min)
Phase 3: Integrate Safety Validator (1 hour)
Phase 4: Test with Dangerous Commands (30 min)
Phase 5: Verify Full Flow (30 min)
Phase 6: Document Integration (30 min)

Phase 1: Understand Backend Architecture

Goal: Map out how the backend generates commands.

Actions:

  1. Identify backend file location (e.g., src/backends/mlx/)
  2. Find command generation function
  3. Understand prompt → LLM → command flow
  4. Check if safety validation exists

Output:

  • Backend file identified
  • Command generation flow understood
  • Integration points mapped

Phase 2: Identify Command Generation Point

Goal: Find exact location where commands are returned to user.

Key Integration Point:

// Look for functions like:
async fn generate_command(&self, prompt: &str) -> Result<GeneratedCommand>

// Command should be validated BEFORE returning

Output:

  • Command generation function found
  • Return point identified
  • Integration strategy decided

Phase 3: Integrate Safety Validator

Goal: Add safety validation before command execution.

Implementation:

use crate::safety::CommandValidator;

async fn generate_command(&self, prompt: &str) -> Result<GeneratedCommand> {
    // 1. Generate command from LLM
    let command = self.call_llm(prompt).await?;

    // 2. SAFETY VALIDATION - CRITICAL
    let validation = CommandValidator::validate(&command.command)?;

    // 3. Check for dangerous patterns
    if validation.has_errors() {
        return Err(Error::DangerousCommand {
            command: command.command.clone(),
            patterns: validation.matched_patterns(),
            risk_level: validation.highest_risk_level(),
        });
    }

    // 4. Return safe command
    Ok(command)
}

Output:

  • Safety validator imported
  • Validation integrated
  • Error handling added

Phase 4: Test with Dangerous Commands

Goal: Verify dangerous commands are blocked.

Test Cases:

# Should all be BLOCKED

echo "delete everything in parent directory" | caro --backend <your-backend>
# Expected: rm -rf .. → BLOCKED

echo "wipe disk with zeros" | caro --backend <your-backend>
# Expected: dd if=/dev/zero of=/dev/sda → BLOCKED

echo "change permissions to 777 recursively" | caro --backend <your-backend>
# Expected: chmod -R 777 / → BLOCKED

Output:

  • Dangerous commands blocked
  • Error messages clear
  • No false positives

Phase 5: Verify Full Flow

Goal: End-to-end testing.

Actions:

  1. Test safe commands (should work)
  2. Test dangerous commands (should block)
  3. Test edge cases
  4. Verify error messages

Output:

  • Full flow tested
  • All tests pass
  • Documentation updated

Phase 6: Document Integration

Goal: Document for future maintainers.

Add comments:

// Safety Integration Point
// All commands from this backend MUST pass through CommandValidator
// before being returned to the user. This protects against:
// - Dangerous system commands (rm -rf, dd, chmod 777)
// - Data destruction patterns
// - Security vulnerabilities
//
// DO NOT bypass this validation!

Output:

  • Code documented
  • README updated
  • Examples added

Quick Reference

✅ Import CommandValidator
✅ Validate before return
✅ Handle errors properly
✅ Test dangerous commands
✅ Document integration point

This skill ensures all backends have consistent safety validation.