n-agentic-harnesses

Design and evaluate agentic harness architectures for AI products.

Updated Apr 4, 2026
One-click install
npx skills add https://github.com/robwestz/ob1_workspace --skill n-agentic-harnesses-robwestz
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: n-agentic-harnesses
Source: https://github.com/robwestz/ob1_workspace/tree/main/skills/n-agentic-harnesses
Command: npx skills add https://github.com/robwestz/ob1_workspace --skill n-agentic-harnesses-robwestz

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This Skill helps you turn vague agent architecture problems into concrete, buildable harness decisions, especially when the real issues are tool boundaries, approval flow, state handling, memory, evaluation, or operator visibility.

Core Features & Use Cases

  • Harness Design: Choose a lean, maintainable architecture for chat assistants, code agents, workflow orchestrators, embedded AI features, or hybrid systems.
  • Safety and Permissions: Define capability registries, trust tiers, approval gates, and audit-friendly execution boundaries for risky actions.
  • Durability and Evaluation: Plan workflow state, resumability, retries, provenance-aware context, and regression tests so the system works in production, not just demos.
  • Use Case: Use this Skill when an AI product keeps doing unexpected things, loses context, cannot resume after failures, or needs a clearer path from idea to implementation.

Quick Start

Ask the skill to design, evaluate, or improve the harness for your AI product and include the product type, tools, constraints, and failure symptoms.

Frequently Asked Questions about n-agentic-harnesses

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

FAQPage Schema
How do I design an agent harness with tool permissions and approval gates?

Agent harness design requires defining capability registries, trust tiers, and approval gates to establish audit-friendly execution boundaries for risky actions. This skill structures those safety boundaries to ensure your AI product maintains strict tool permissions during operation.

What is an agentic harness architecture and when do I need one?

An agentic harness architecture is the structural framework governing AI assistants, copilots, or workflow runtimes requiring tool boundaries, state, memory, and observability. You need one when your AI product loses context, cannot resume after failures, or performs unexpected actions.

How do I add resumable workflow state and provenance-aware context to my AI agent?

Adding resumable workflow state and provenance-aware context involves planning durable state handling, retries, and context assembly within your agent harness. This skill designs those durability mechanisms so your system maintains workflow state and context properly in production.

Can I use this approach for embedded AI features and developer tools?

Yes, this harness architecture approach applies to developer tools, chat assistants, workflow orchestrators, copilots, and embedded AI features. It helps choose a lean, maintainable architecture tailored to your specific product type and operational constraints.

Why does my AI agent lose context and fail to resume after errors?

Your AI agent loses context and fails to resume because it lacks proper workflow state management, resumability, and provenance-aware context assembly within its harness. This skill solves those failure symptoms by designing durable state handling and operator diagnostics.

How do I set up evaluation coverage and observability for an agent workflow runtime?

Setting up evaluation coverage and observability requires planning regression tests and human-readable operator diagnostics within your agent harness. This skill integrates evaluation coverage and diagnostics to ensure your workflow runtime functions reliably beyond initial demos.