惯性聚合 高效追踪和阅读你感兴趣的博客、新闻、科技资讯
阅读原文 在惯性聚合中打开

推荐订阅源

奇客Solidot–传递最新科技情报
奇客Solidot–传递最新科技情报
小众软件
小众软件
博客园 - 三生石上(FineUI控件)
让小产品的独立变现更简单 - ezindie.com
让小产品的独立变现更简单 - ezindie.com
博客园_首页
Last Week in AI
Last Week in AI
美团技术团队
OSCHINA 社区最新新闻
OSCHINA 社区最新新闻
Apple Machine Learning Research
Apple Machine Learning Research
WordPress大学
WordPress大学
钛媒体:引领未来商业与生活新知
钛媒体:引领未来商业与生活新知
博客园 - Franky
The Cloudflare Blog
罗磊的独立博客
月光博客
月光博客
N
Netflix TechBlog - Medium
C
Check Point Blog
Microsoft Security Blog
Microsoft Security Blog
F
Fortinet All Blogs
freeCodeCamp Programming Tutorials: Python, JavaScript, Git & More
Microsoft Azure Blog
Microsoft Azure Blog
IT之家
IT之家
Jina AI
Jina AI
J
Java Code Geeks

DEV Community

Authentication Security Deep Dive: From Brute Force to Salted Hashing (With Java Examples) Why AI Systems Don’t Fail — They Drift Spilling beans for how i learn for exam😁"Reinforcement Learning Cheat Sheet" I Replaced Chrome with Safari for AI Browser Automation. Here's What Broke (and What Finally Worked) How Python Borrows Other People's Work The $40 Architecture: Processing 1 Billion API Requests with 99.99% Uptime Vibe Coding: A Workflow Guide (From Zero to SaaS) Most webhook security guides protect the wrong side. The scary part is delivery. Headless CMS for TanStack Start: Build a Blog with Cosmic EU Age Verification App "Hacked in 2 Minutes" — What Actually Happened Comfy Cloud’s delete function does not actually remove files Running AI Models on GPU Cloud Servers: A Beginner Guide Event-driven media intelligence with AWS Step Functions and Bedrock I scored 500 AI prompts across 8 quality dimensions — here's what broke How to Call Google Gemini API from Next.js (Free Tier, No Backend Needed) The Portal Protocol: Reclaiming Human Connection in the Age of AI How to Fix Your Team's Scattered Knowledge Problem With a Self-Hosted Forum Intro to tc Cloud Functors: A Graph-First Mental Model for the Modern Cloud Designing Multi-Tenant Backends With Both Ownership and Team Access I Built a Neumorphic CSS Library with 77+ Components — Here's What I Learned PostgreSQL Performance Optimization: Why Connection Pooling Is Critical at Scale Cómo construí un SaaS multi-rubro para gestionar expensas en Argentina con FastAPI + Vue 3 🚀 I Built an Ethical Hacking Scanner Tool – Open Source Project I Replaced /usage and /context in Claude Code With a Single Statusline A Pythonic Way to Handle Emails (IMAP/SMTP) with Auto-Discovery and AI-Ready Design I Collected 8.9 Million Polymarket Price Points — Here's What I Found About How Markets Really Move EcoTrack AI — Carbon Footprint Tracker & Dashboard Everyone's Using AI. No One Agrees How. 5 self-hosted ebook managers worth trying in 2026 Building Your First AI Agent with LangChain: From Chatbot to Autonomous Assistant
I got tired of AI agents roaming my codebase — so I built...
Enmanuel Mag · 2026-05-06 · via DEV Community

The problem

Every time I open Claude Code or any MCP-compatible AI tool, the same thing happens: the agent starts working, does something, and I have no idea what it changed, what it tried, or why it got stuck. Across sessions, it's even worse — the agent has no memory of what was already attempted.

If you want multiple agents working in parallel or in sequence, good luck coordinating them without race conditions, double work, or conflicting changes.

I wanted something I could actually trust to run on my codebase.

What I built

agent-harness-kit (ahk) is a scaffolding layer for structured multi-agent workflows. One command drops it into any project:

npx ahk init

Enter fullscreen mode Exit fullscreen mode

t creates a local MCP server (runs on stdio, no ports needed), a SQLite database, a task backlog, a health gate, and four agent definition files.

How it works

The 4-agent workflow

Lead → Explorer → Builder → Reviewer

Enter fullscreen mode Exit fullscreen mode

  • Lead decomposes the task into a plan. Never reads source files.
  • Explorer maps the codebase. Never writes files.
  • Builder implements. Only writes to writablePaths you define.
  • Reviewer checks acceptance criteria. Runs health check before approving.

Each role has its own Markdown file you can customize. They're created once and never overwritten.

Atomic task claiming

tasks.claim(id, agent)  // SQLite transaction — no double-work possible

Enter fullscreen mode Exit fullscreen mode

Two agents can't grab the same task. The second one gets task_already_claimed and moves on.

Health gate

Before any agent starts or closes a task, it runs your health.sh:

#!/usr/bin/env bash
npm test || exit 1
curl -sf http://localhost:3000/health > /dev/null || exit 1
echo "All checks passed."

Enter fullscreen mode Exit fullscreen mode

If it exits with anything other than 0, the task stays open. You define what "healthy" means for your project.

Full audit trail

Every action is recorded:

actions.start(taskId, agent)             // start
actions.write(actionId, 'files_modified', 'src/auth.ts, src/routes/login.ts')
actions.write(actionId, 'result', '...')
actions.complete(actionId, 'summary')    // close

Enter fullscreen mode Exit fullscreen mode

ahk export --json dumps the full history.

Provider-agnostic

Works with Claude Code today. Moving to OpenCode? One command:

ahk migrate --to opencode

Enter fullscreen mode Exit fullscreen mode

Your task history, agent definitions, and config stay intact.

No cloud, no native deps

Everything lives in .harness/harness.db (SQLite, gitignored). Uses node:sqlite built-in — no node-gyp, no native compilation.

Requirements: Node ≥ 22 or Bun.

Get started

npx ahk init

Enter fullscreen mode Exit fullscreen mode

Interactive setup. Asks for your project name, AI provider, docs path, and an optional first task. Creates everything in under a minute.


GitHub: link
npm: @cardor/agent-harness-kit

I'd love feedback on the health gate design and the atomic claiming approach — those were the trickiest parts to get right.