harness-settings

Name: harness-settings
Availability: InStock
Author: wild

Centralize provider-specific harness settings across Claude Code, OpenAI Codex CLI, and GitHub Copilot.

12|Updated Feb 6, 2026

Search Tags:#codex #claude #settings #copilot #harness #config-management #provider-config

Ready to run

npx skills add https://github.com/madebywild/agent-harness --skill harness-settings

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: harness-settings
Source: https://github.com/madebywild/agent-harness/tree/main/.claude/skills/harness-settings
Command: npx skills add https://github.com/madebywild/agent-harness --skill harness-settings

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Centralizes provider-specific configuration management across Claude Code, OpenAI Codex CLI, and GitHub Copilot by storing per-provider settings in the harness settings entity and applying them to each provider's native config location.

Core Features & Use Cases

Per-provider source files: claude.json, codex.json, copilot.json stored under .harness/src/settings; outputs mapped to .claude/settings.json, .codex/config.toml, and .github/copilot-settings.json.
CLI workflow: scaffold with harness add settings claude, codex, or copilot; plan to preview changes; apply to write provider artifacts.
Real-world use case: teams manage provider configurations consistently across CI/CD pipelines and multiple environments.

Quick Start

Scaffold a provider-specific settings source with harness add settings claude, then run harness plan and harness apply to write the provider configurations.

Frequently Asked Questions about harness-settings

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I centralize configuration settings across Claude Code, OpenAI Codex CLI, and GitHub Copilot?▼

Centralize provider-specific harness settings by storing per-provider source files under .harness/src/settings and applying them to native config locations like .claude/settings.json and .codex/config.toml. This enforces consistent configuration across multiple AI coding providers.

What is the best way to manage multi-provider AI coding configurations in CI/CD pipelines?▼

Manage multi-provider AI coding configurations by using harness plan and apply cycles to generate provider-specific files like .github/copilot-settings.json. This ensures teams maintain consistent provider configurations across CI/CD pipelines and multiple environments.

Can I scaffold provider-specific config files for Claude, Codex, and Copilot individually?▼

Yes, you can scaffold provider-specific config files individually using CLI commands like harness add settings claude, harness add settings codex, or harness add settings copilot. Each command generates the corresponding source file under .harness/src/settings.

How does the harness plan and apply workflow handle provider configuration generation?▼

The harness plan and apply workflow previews configuration changes and then writes provider artifacts to their native config locations. It maps source files like claude.json to outputs like .claude/settings.json, ensuring consistent application across providers.

Do I need separate source files for each AI provider's harness settings?▼

Yes, you need separate per-provider source files such as claude.json, codex.json, and copilot.json stored under .harness/src/settings. Each file targets a specific provider and maps to its respective native configuration format during the apply cycle.

Why do my harness settings not apply correctly to .codex/config.toml or .github/copilot-settings.json?▼

Harness settings may not apply correctly if the per-provider source files under .harness/src/settings are missing or misconfigured. Ensure you run harness plan to preview changes and harness apply to write the provider artifacts to their native config locations.