Agent skill

cloud-provider-detector

View SKILL.md on GitHub Repository
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Install this agent skill to your Project

npx add-skill https://github.com/FortiumPartners/ai-mesh/tree/main/skills/cloud-provider-detector

SKILL.md

Cloud Provider Detection Skill

Auto-detect AWS, GCP, or Azure usage with 95%+ accuracy using multi-signal analysis.

Quick Start

javascript
const { detectCloudProvider } = require('./detect-cloud-provider.js');

// Auto-detect cloud provider
const result = await detectCloudProvider('/path/to/project');

if (result.detected) {
  console.log(`Detected: ${result.name}`);
  console.log(`Confidence: ${(result.confidence * 100).toFixed(1)}%`);
  console.log(`Signals: ${result.signal_count}`);
}

// Manual override
const awsResult = await detectCloudProvider('/path/to/project', {
  provider: 'aws'
});

Detection Signals

Signal Types (Weighted)

  1. Terraform (weight: 0.5) - Highest priority

    • Provider declarations: provider "aws", provider "google", provider "azurerm"
    • Resource types: aws_vpc, google_compute_instance, azurerm_storage_account

  2. Package Manifests (weight: 0.3)

    • NPM: @aws-sdk/, @google-cloud/, @azure/
    • Python: boto3, google-cloud-*, azure-*

  3. Config Files (weight: 0.3)

    • .aws/config, .gcloud/, .azure/
    • cloudformation.yml, cloudbuild.yaml, azuredeploy.json

  4. CLI Scripts (weight: 0.2)

    • aws configure, gcloud compute, az vm
    • Command patterns in .sh files

  5. Docker (weight: 0.2)

    • Base images: FROM public.ecr.aws, FROM gcr.io, FROM mcr.microsoft.com

Confidence Scoring

Base Score = Σ(detected_signals × signal_weight) / Σ(all_signal_weights)

Multi-Signal Boost:
  if (signal_count >= 3) {
    confidence += 0.2  // Up to maximum of 1.0
  }

Detection Threshold: ≥0.7 (70%)

CLI Usage

bash
# Detect in current directory
node detect-cloud-provider.js

# Detect in specific project
node detect-cloud-provider.js /path/to/project

# Manual override
node detect-cloud-provider.js /path/to/project --provider aws

# Custom confidence threshold
node detect-cloud-provider.js /path/to/project --min-confidence 0.8

# Exit codes:
#   0 = Provider detected
#   1 = No provider detected
#   2 = Error occurred

Response Format

json
{
  "detected": true,
  "provider": "aws",
  "name": "Amazon Web Services (AWS)",
  "confidence": 0.95,
  "signals": {
    "terraform": true,
    "npm": true,
    "python": false,
    "cli": true,
    "docker": true,
    "config": true
  },
  "signal_count": 5,
  "all_results": [
    {
      "provider": "aws",
      "name": "Amazon Web Services (AWS)",
      "confidence": 0.95,
      "signals": {...},
      "signal_count": 5
    },
    {
      "provider": "gcp",
      "name": "Google Cloud Platform (GCP)",
      "confidence": 0.12,
      "signals": {...},
      "signal_count": 1
    }
  ]
}

Integration Examples

infrastructure-specialist Agent

yaml
# In agent YAML behavior section:

**Cloud Provider Detection**:
- **Auto-detect**: Run `node skills/cloud-provider-detector/detect-cloud-provider.js`
  at task start to identify AWS/GCP/Azure usage
- **Load Skills**: If AWS detected (≥70% confidence), load AWS cloud skill
- **Multi-cloud**: If multiple providers detected, load all relevant skills
- **Manual Override**: Accept `--cloud-provider` flag to bypass detection

Example Workflow

javascript
// 1. Detect cloud provider
const detection = await detectCloudProvider(projectPath);

// 2. Load appropriate skill
if (detection.detected) {
  if (detection.provider === 'aws') {
    await loadSkill('skills/aws-cloud/SKILL.md');
  } else if (detection.provider === 'gcp') {
    await loadSkill('skills/gcp-cloud/SKILL.md');
  } else if (detection.provider === 'azure') {
    await loadSkill('skills/azure-cloud/SKILL.md');
  }
}

// 3. Execute infrastructure tasks with cloud-specific knowledge

Detection Patterns

AWS Indicators

  • Terraform: aws_vpc, aws_s3_bucket, aws_lambda_function
  • NPM: @aws-sdk/client-s3, aws-cdk-lib
  • Python: boto3, botocore
  • CLI: aws configure, aws s3 sync
  • Docker: FROM public.ecr.aws/lambda/nodejs

GCP Indicators

  • Terraform: google_compute_instance, google_storage_bucket
  • NPM: @google-cloud/storage, googleapis
  • Python: google-cloud-storage, google-api-python-client
  • CLI: gcloud compute, gsutil cp
  • Docker: FROM gcr.io/google-appengine/nodejs

Azure Indicators

  • Terraform: azurerm_virtual_machine, azurerm_storage_account
  • NPM: @azure/storage-blob, azure-functions-core-tools
  • Python: azure-storage-blob, msrestazure
  • CLI: az vm create, az storage account
  • Docker: FROM mcr.microsoft.com/azure-functions/node

Performance

  • Detection Time: <100ms for typical projects
  • Accuracy: ≥95% on projects with clear cloud provider usage
  • File Scanning: Optimized with glob patterns and ignore lists
  • Memory: Low memory footprint with streaming file reads

Error Handling

javascript
try {
  const result = await detectCloudProvider(projectPath);
} catch (error) {
  if (error.code === 'ENOENT') {
    console.error('Project directory not found');
  } else if (error.message.includes('patterns.json')) {
    console.error('Detection patterns file missing or invalid');
  } else {
    console.error('Detection failed:', error.message);
  }
}

Common Issues

Low Confidence Scores (<0.7):

  • Project may use multiple cloud providers (check all_results)
  • Limited cloud-specific patterns (consider manual override)
  • Infrastructure as code not in Terraform (update detection patterns)

False Positives:

  • Reduce minimum confidence threshold
  • Check which signals were detected
  • Review pattern matches in source files

No Detection:

  • Ensure project path is correct
  • Check that cloud provider files are not in ignored directories
  • Verify patterns.json includes expected indicators

Customization

Adding New Providers

Edit cloud-provider-patterns.json:

json
{
  "providers": {
    "digitalocean": {
      "name": "DigitalOcean",
      "confidence_boost": 0.3,
      "detection_signals": {
        "terraform": {
          "weight": 0.5,
          "patterns": ["provider \"digitalocean\"", "digitalocean_droplet"]
        }
      }
    }
  }
}

Adjusting Detection Rules

json
{
  "detection_rules": {
    "minimum_confidence": 0.6,        // Lower = more permissive
    "multi_signal_boost": 0.3,        // Higher = favor multi-signal
    "minimum_signals_for_boost": 2    // Lower = boost earlier
  }
}

Best Practices

  1. Run Early: Detect cloud provider at task start for optimal skill loading
  2. Check Confidence: Log confidence scores to monitor detection accuracy
  3. Manual Override: Provide --provider flag for edge cases
  4. Multi-Cloud: Handle projects using multiple cloud providers gracefully
  5. Cache Results: Cache detection results per session to avoid re-scanning

Dependencies

  • Node.js: ≥18.0.0 required for glob and fs.promises
  • NPM Package: glob for file pattern matching

Install with:

bash
npm install glob

File Size

  • SKILL.md: ~8KB (quick reference)
  • detect-cloud-provider.js: ~12KB (implementation)
  • cloud-provider-patterns.json: ~6KB (detection rules)
  • Total: ~26KB for complete cloud provider detection system

Version

  • Version: 1.0.0
  • Last Updated: October 2025
  • Maintainer: Fortium Infrastructure Team

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