adaptive-harness

Name: adaptive-harness
Availability: InStock
Author: hiddink-ai

Analyze project directories to detect technology stacks and manage agent activation states.

1|Updated May 21, 2026

Search Tags:#automation #optimization #orchestration #harness #agent-management #project-profile

Ready to run

npx skills add https://github.com/hiddink-ai/hiddink-harness --skill adaptive-harness-hiddink-ai

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: adaptive-harness
Source: https://github.com/hiddink-ai/hiddink-harness/tree/main/templates/skills/adaptive-harness
Command: npx skills add https://github.com/hiddink-ai/hiddink-harness --skill adaptive-harness-hiddink-ai

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This skill eliminates the manual overhead of configuring and maintaining AI agent environments by automatically detecting project requirements and pruning unused agents to keep the workspace clean and efficient.

Core Features & Use Cases

Context-Aware Optimization: Automatically scans project files to identify the tech stack and activates only the relevant specialist agents.
Failure Pattern Learning: Analyzes session history to identify recurring errors and suggests rule overrides or model escalations to improve reliability.
Portable Profiles: Generates project-specific profiles that can be exported and imported to ensure consistent agent behavior across different environments or team members.

Quick Start

Run the adaptive-harness skill to scan your current project directory and automatically optimize your active agent configuration.

Frequently Asked Questions about adaptive-harness

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

FAQPage Schema

How do I automatically optimize AI agent orchestration for my project?▼

To optimize agent orchestration, scan your project directory structure to detect the technology stack and dynamically manage agent activation states. This eliminates manual configuration overhead by activating only relevant specialist agents and pruning unused ones.

How does failure pattern learning work for AI agent management?▼

Failure pattern learning analyzes session history to identify recurring errors in agent execution. It then suggests rule overrides or model escalations to improve reliability and resolve persistent configuration gaps automatically.

How do I ensure consistent AI agent behavior across different development environments?▼

To ensure consistent agent behavior, generate portable project-specific profiles within the .claude directory. These profiles can be exported and imported across different environments or team members to maintain identical agent configurations.

What permissions are needed to scan project manifests and manage agent profiles?▼

Managing agent profiles requires read-only access to project manifest files to detect technology stacks. It also needs write access to the .claude directory to save and maintain project-specific profile configurations.

When should I prune unused AI agents from my workspace?▼

Prune unused agents when your workspace becomes inefficient or cluttered with irrelevant specialist agents. The system automatically handles this by scanning project files and deactivating agents that do not match your detected tech stack.

Can I resolve configuration gaps in AI agent environments automatically?▼

You can resolve configuration gaps automatically by operating within the hiddink-harness ecosystem. It analyzes execution patterns and project structures to identify missing settings and suggest appropriate rule overrides.