agentforge-harness

Apply harness-level constraints, hooks, and verification loops to recurring agent failures.

Updated Apr 8, 2026
One-click install
npx skills add https://github.com/Kingxiao/agentforge --skill agentforge-harness
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: agentforge-harness
Source: https://github.com/Kingxiao/agentforge/tree/main/agentforge-harness
Command: npx skills add https://github.com/Kingxiao/agentforge --skill agentforge-harness

SYSTEM DOCUMENTATION & REQUIREMENTS

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

What problem does it solve?

Harness Engineering provides a disciplined, repeatable framework to prevent AI agent failures by encoding constraints, tests, and verification into CLAUDE.md rules, hooks, and a shared governance model.

Core Features & Use Cases

  • Hashimoto Loop implementation: observe failures, diagnose, classify fixes (behavioral, mechanical, structural, or context), and apply patches with verification.
  • Seven-layer harness architecture: Context Engineering, Tool Orchestration, Memory & State, Architectural Constraints, Verification & Feedback, Entropy Management, and Human-in-the-Loop.
  • Long-running and HTTP service harness patterns: heartbeat, checkpointing, auto-resume, health checks, idempotency, and graceful shutdown.
  • Team harness collaboration and multi-agent coordination: git-backed memory, CLAUDE.md governance, shared hooks, and PR-review discipline.
  • Self-evolution concepts: trajectory capture, safety gates, and patch-based skill improvements under user approval.

Quick Start

Start by cloning the harness repository and running the CLAUDE.md-driven setup to begin diagnosing and patching agent failures.

Frequently Asked Questions about agentforge-harness

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

FAQPage Schema
How do I prevent recurring AI agent failures during long-running operations?▼

Prevent recurring AI agent failures by applying harness-level constraints, mechanical hooks, and verification loops via CLAUDE.md rules. This framework implements heartbeat, checkpointing, and auto-resume patterns to ensure stability during long-running operations.

What is the Hashimoto Loop for agent failure diagnosis?▼

The Hashimoto Loop is an agent failure diagnosis process where you observe failures, diagnose root causes, classify fixes as behavioral, mechanical, structural, or context-based, and apply patches with verification to ensure stability.

How do I coordinate multi-agent systems using CLAUDE.md governance?▼

Coordinate multi-agent systems by establishing git-backed memory, shared hooks, and PR-review discipline within a CLAUDE.md governance model. This team harness collaboration framework ensures structured progress tracking and consistent multi-agent coordination.

Does harness engineering work with Claude Code for CI-CD pipelines?▼

Yes, harness engineering works with Claude Code by encoding constraints, tests, and verification into CLAUDE.md rules and hooks. This integration applies across CI-CD phases from prompt discipline to multi-agent coordination and team collaboration.

What are the limitations of using hooks for AI agent stability?▼

Hooks for AI agent stability require a CLAUDE.md-based rule set and structured progress tracking to validate fixes before deployment. Without mechanical hooks and verification loops, the harness cannot effectively classify and patch behavioral or structural agent failures.