multi-harness-portability

Convert universal SKILL.md files into harness-specific adapter configurations.

31|8|Updated Apr 10, 2026
One-click install
npx skills add https://github.com/itallstartedwithaidea/agent-skills --skill multi-harness-portability
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: multi-harness-portability
Source: https://github.com/itallstartedwithaidea/agent-skills/tree/main/skills/claude-mythos/multi-harness-portability
Command: npx skills add https://github.com/itallstartedwithaidea/agent-skills --skill multi-harness-portability

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Prevents your agent skills from becoming locked to a single editor, CLI, or model harness by standardizing a universal skill interface and mapping it to platform-specific loaders.

Core Features & Use Cases

  • Universal SKILL.md source: Defines the portable skill entry point once via YAML frontmatter plus operational instructions.
  • Platform adapter architecture: Converts the universal format into harness-native loading mechanisms (Claude Code, Cursor, Codex, Gemini CLI).
  • Cross-platform CI validation: Establishes repeatable tests that install and verify the skill across multiple harnesses to catch portability regressions early.

Quick Start

Ask your AI to port the skill so it can be installed and run consistently on Claude Code, Cursor, Codex, and Gemini CLI, using SKILL.md as the single source of truth.

Frequently Asked Questions about multi-harness-portability

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

FAQPage Schema
How do I make agent skills portable across multiple AI tools like Claude Code and Cursor?

Cross-platform CI validation installs and verifies the skill across multiple harnesses using deterministic steps, catching portability regressions early before deployment in multi-tool teams and CI/CD pipelines.

Can I use a single skill configuration file for different AI harnesses?

The platform adapter architecture converts the universal SKILL.md format into harness-native loading mechanisms, ensuring equivalent tool access and output formatting across different environments.

How do I validate AI skill portability in a CI/CD pipeline?

Cross-platform CI validation establishes repeatable tests that install and verify the skill across multiple harnesses, catching portability regressions early in multi-tool teams and CI/CD pipelines.

Why does my agent skill break when switching between Gemini CLI and Codex?

Skills break across harnesses due to platform-specific loading mechanisms; defining a universal SKILL.md interface and mapping it via platform adapters ensures consistent tool access and output formatting.

What is the best way to standardize prompt configuration for multi-tool AI teams?

Standardizing prompt configuration for multi-tool AI teams involves defining a universal SKILL.md source with YAML frontmatter, which adapters then translate into harness-native loading mechanisms for consistent behavior.