Openclaw Config

OpenClaw Config is a configuration management skill for OpenClaw projects that handles environment setup, feature flags, runtime parameters, and deployment configuration through structured files. It covers configuration schemas, environment variable management, feature toggle systems, validation rules, and multi-environment deployment settings that enable consistent application configuration.

What Is This?

Overview

OpenClaw Config provides structured approaches to managing application configuration across environments. It handles defining configuration schemas with typed fields and default values, loading settings from environment variables, files, and command line arguments with priority ordering, validating configuration values against schema constraints at startup, managing feature flags that toggle functionality without redeployment, supporting environment-specific overrides for development, staging, and production, and generating configuration documentation from schema definitions.

Who Should Use This

This skill serves developers configuring applications for multiple deployment environments, DevOps engineers managing environment-specific settings across infrastructure, platform teams building configuration standards for microservice fleets, and teams implementing feature flag systems.

Why Use It?

Problems It Solves

Hardcoded configuration values require code changes and redeployment for environment adjustments. Without validation, misconfigured settings cause runtime failures that are difficult to diagnose. Managing feature flags through code branches increases merge complexity and deployment risk. Inconsistent configuration formats across services make infrastructure automation fragile.

Core Highlights

Schema validation catches misconfiguration at startup before the application serves traffic. Environment layering applies base settings with environment-specific overrides in a predictable order. Feature flags enable runtime toggling of functionality without code deployment. Typed configuration provides IDE support and prevents type mismatch errors.

How to Use It?

Basic Usage

import os
from dataclasses import dataclass, field

@dataclass
class DatabaseConfig:
    host: str = "localhost"
    port: int = 5432
    name: str = "app_db"
    pool_size: int = 10

@dataclass
class AppConfig:
    env: str = "development"
    debug: bool = False
    port: int = 8080
    db: DatabaseConfig = field(default_factory=DatabaseConfig)
    features: dict = field(default_factory=dict)

def load_config():
    config = AppConfig(
        env=os.getenv("APP_ENV", "development"),
        debug=os.getenv("APP_DEBUG", "").lower() == "true",
        port=int(os.getenv("APP_PORT", "8080")),
        db=DatabaseConfig(
            host=os.getenv("DB_HOST", "localhost"),
            port=int(os.getenv("DB_PORT", "5432")),
            name=os.getenv("DB_NAME", "app_db"),
            pool_size=int(os.getenv("DB_POOL", "10"))
        )
    )
    return config

config = load_config()
print(f"Running on port {config.port} ({config.env})")

Real-World Examples

import json
from pathlib import Path

class ConfigManager:
    def __init__(self, base_path="config"):
        self.base_path = Path(base_path)
        self.config = {}
        self.features = {}

    def load(self, environment):
        base = self.read_file("base.json")
        env_file = f"{environment}.json"
        overrides = self.read_file(env_file)
        self.config = self.merge(base, overrides)
        self.apply_env_vars()
        self.features = self.config.get("features", {})
        self.validate()
        return self.config

    def read_file(self, filename):
        path = self.base_path / filename
        if path.exists():
            with open(path) as f:
                return json.load(f)
        return {}

    def merge(self, base, overrides):
        result = base.copy()
        for key, value in overrides.items():
            if isinstance(value, dict) and key in result:
                result[key] = self.merge(result[key], value)
            else:
                result[key] = value
        return result

    def apply_env_vars(self):
        for key, value in os.environ.items():
            if key.startswith("APP_"):
                config_key = key[4:].lower()
                self.config[config_key] = value

    def validate(self):
        required = ["port", "database"]
        missing = [
            k for k in required if k not in self.config
        ]
        if missing:
            raise ValueError(
                f"Missing required config: {missing}"
            )

    def is_enabled(self, feature_name):
        return self.features.get(feature_name, False)

mgr = ConfigManager()
config = mgr.load("production")
if mgr.is_enabled("new_dashboard"):
    print("New dashboard enabled")

Advanced Tips

Use schema validation libraries to enforce type constraints and value ranges at startup rather than discovering issues at runtime. Implement configuration diffing between environments to catch unintended divergence. Log loaded configuration at startup with sensitive values masked for debugging.

When to Use It?

Use Cases

Use OpenClaw Config when managing application settings across development, staging, and production environments, when implementing feature flags for gradual rollouts, when validating configuration at startup to catch errors early, or when standardizing configuration patterns across services.

Related Topics

Environment variable management, feature flag platforms, configuration validation libraries, secrets management with Vault, and twelve-factor app configuration principles complement OpenClaw Config.

Important Notes

Requirements

Configuration files for each target environment. Environment variable access in the deployment platform. Schema definitions for validation rules.

Usage Recommendations

Do: validate all configuration at application startup to surface errors immediately. Use environment variables for secrets and sensitive values rather than configuration files. Document every configuration field with its purpose and valid value ranges.

Don't: store secrets in configuration files that get committed to version control. Change production configuration without review and approval processes. Allow applications to start with invalid configuration by skipping validation.

Limitations

File-based configuration requires redeployment or restart to apply changes. Feature flag evaluation adds minor overhead to request processing paths. Complex configuration hierarchies can become difficult to debug when values override unexpectedly.