Tune Harness

Analyze and adjust AI harness configurations to match codebase evolution.

3|Updated Mar 29, 2026
One-click install
npx skills add https://github.com/softwaresalt/autoharness --skill tune-harness
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: Tune Harness
Source: https://github.com/softwaresalt/autoharness/tree/main/.github/skills/tune-harness
Command: npx skills add https://github.com/softwaresalt/autoharness --skill tune-harness

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) and scripts (resource) and assets (resource) components.

What problem does it solve?

It enables developers to iteratively adapt and maintain their AI agent harnesses to match the current state of their codebases, reducing drift and ensuring operational integrity.

Core Features & Use Cases

  • Workspace Drift Analysis: Detects configuration, artifact, and structural drift in the workspace compared to the installed harness state.
  • Automated Tuning Proposals: Generates recommendations for schema migrations, backfills, and artifact updates based on version and schema verification.
  • Periodic Maintenance: Facilitates routine assessments after code changes, major updates, or configuration modifications to maintain harness effectiveness.
  • Use Case: When a repository undergoes significant restructuring or version upgrades, this skill helps align the harness seamlessly without manual reconfiguration.

Quick Start

Invoke this skill with paths to your autoharness installation and workspace to analyze and propose updates for your harness setup.

Frequently Asked Questions about Tune Harness

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

FAQPage Schema
How do I detect configuration drift in my AI agent harness?

To detect configuration drift in your AI agent harness, you need workspace drift analysis that compares your current codebase structure against the installed harness state to identify configuration, artifact, and structural inconsistencies.

What is automated schema migration for AI harnesses?

Automated schema migration for AI harnesses is the process of generating recommendations for schema updates, backfills, and artifact adjustments based on version and schema verification to align configurations with codebase evolution.

How do I update my harness configuration after a major codebase restructuring?

To update your harness configuration after a major codebase restructuring, you can use automated tuning proposals that analyze version and schema verification to recommend migrations, backfills, and artifact updates without manual reconfiguration.

Can I use automated drift detection for routine workspace maintenance?

Yes, you can use automated drift detection for routine workspace maintenance by running periodic assessments after code changes, major updates, or configuration modifications to maintain harness effectiveness and operational correctness.

What's the best way to maintain AI harness integrity during version upgrades?

The best way to maintain AI harness integrity during version upgrades is to perform automated workspace integrity checks that verify schema consistency and recommend remedial actions to ensure operational correctness across your evolving codebase.

Why does my AI agent harness stop working after repository changes?

Your AI agent harness stops working after repository changes due to configuration, artifact, and structural drift that occurs when the workspace state diverges from the installed harness configuration without proper schema migration.