Claude代码智能工作流

The Mindshift: From "Building Agents" to Building Harnesses

When someone says "I am building an agent," they can only mean one of two things:

1. Training a model. Adjusting weights through reinforcement learning, fine-tuning, RLHF, or another gradient-based method. Collecting trajectory data -- real-world sequences of perception, reasoning, and action in a target domain -- and using it to shape the model's behavior. This is what DeepMind, OpenAI, Tencent AI Lab, and Anthropic do.

2. Building a harness. Writing the code that gives a model an operational environment. This is what most of us do, and it is the core of this repository.

A harness is everything an agent needs to work in a specific domain:

Harness = Tools + Knowledge + Observation + Action Interfaces + Permissions

    Tools:          file I/O, shell, network, database, browser
    Knowledge:      product docs, domain references, API specs, style guides
    Observation:    git diff, error logs, browser state, sensor data
    Action:         CLI commands, API calls, UI interactions
    Permissions:    sandbox isolation, approval workflows, trust boundaries

The model decides. The harness executes. The model reasons. The harness provides context. The model is the driver. The harness is the vehicle.

This repository teaches you to build the vehicle. A vehicle for coding. But the design patterns generalize to any domain.

Quick Start

Sister Tutorial: From Passive Sessions to Always-On Assistants

The harness taught in this repository is the use-and-discard kind -- open a terminal, give the agent a task, close when done, next session starts fresh. Claude Code works this way.

But OpenClaw proves another possibility: on the same agent core, two additional harness mechanisms turn an agent from "poke it and it moves" into "wakes itself every 30 seconds to look for work":

• Heartbeat -- every 30 seconds the harness sends the agent a message, letting it check for pending work. Nothing to do? Keep sleeping. Something appeared? Act immediately.
• Cron -- the agent can schedule its own future tasks, which fire automatically when the time arrives.

Add IM multi-channel routing (WhatsApp / Telegram / Slack / Discord and 13+ other platforms), persistent context memory, and a Soul personality system, and the agent transforms from a disposable tool into an always-on personal AI assistant.

claw0 is our sister teaching repository, breaking down these harness mechanisms from scratch:

claw agent = agent core + heartbeat + cron + IM chat + memory + soul

learn-claude-code                   claw0
(agent harness internals:            (always-on harness:
 loop, tools, planning,               heartbeat, cron, IM channels,
 teams, worktree isolation)            memory, Soul personality)

Kode Agent CLI -- Open-Source Coding Agent CLI

npm i -g @shareai-lab/kode

Skill and LSP support, Windows compatible, works with GLM / MiniMax / DeepSeek and other open models. Install and go.

GitHub: shareAI-lab/Kode-Agent

Kode Agent SDK -- Embed Agent Capabilities in Your Application

A standalone library with no per-user process overhead. Embed it in backends, browser extensions, embedded devices, or any runtime.

GitHub: shareAI-lab/kode-agent-sdk

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