environment-diagnostics

Environment diagnostics skill for validating configuration and system state.

When to activate

Use this skill when tests fail with configuration or environment errors, when setting up a new development or staging environment, when a deployment fails with missing config or dependency issues, or when onboarding a new developer who needs to verify their local setup.

Environment variables

Check that required variables are set and non-empty:

python -c "
import os, sys
required = ['DATABASE_URL', 'API_KEY', 'SECRET_KEY']
missing = [v for v in required if not os.environ.get(v)]
if missing:
    print('Missing or empty:', ', '.join(missing))
    sys.exit(1)
print('All required variables present')
"

Common patterns to check:

• DATABASE_URL -- connection string for the primary database
• API_KEY / API_SECRET -- external service credentials
• SECRET_KEY / JWT_SECRET -- application signing keys
• REDIS_URL / CACHE_URL -- cache connection strings
• LOG_LEVEL -- logging configuration
• NODE_ENV / FLASK_ENV / RAILS_ENV -- runtime environment designation

For each variable, verify not just presence but also basic format validity (e.g., DATABASE_URL starts with a known scheme like postgres:// or mysql://).

Config files

Verify expected configuration files exist and parse correctly:

1. Existence -- check that each expected config file is present.
2. Syntax -- attempt to parse the file in its format:

python -c "import json; json.load(open('config.json'))"      # JSON
python -c "import yaml; yaml.safe_load(open('config.yaml'))"  # YAML
python -c "import tomllib; tomllib.load(open('pyproject.toml','rb'))"  # TOML

1. Required fields -- after parsing, verify that mandatory keys exist in the config structure.
2. Value validation -- check that numeric values are in expected ranges, URLs are well-formed, and enum values match allowed options.

Port conflicts

Check if expected ports are available or already bound: