agent-base-v2

内容来源：README.md（说明文档） · 原始地址 · 查看安装指南

原始内容

# Agent Harness

**The rig. Not the driver.**

A TypeScript runtime for configuring and running AI agents with any LLM.

[![Bun 1.3.4+](https://img.shields.io/badge/bun-1.3.4+-black.svg)](https://bun.sh/)
[![TypeScript 5.x](https://img.shields.io/badge/typescript-5.x-blue.svg)](https://www.typescriptlang.org/)
[![License: MIT](https://img.shields.io/badge/License-MIT-blue.svg)](https://opensource.org/licenses/MIT)

---

## What is a Harness?

A harness is infrastructure. It connects an AI model to tools and policies. Not intelligent itself, just reliable plumbing.

| | Harness (this project) | Agent (the LLM) |
|---|------------------------|-----------------|
| Decides actions | No | Yes |
| Executes tools | Yes | No |
| Enforces safety | Yes | No |
| Has goals | No | Yes (when configured) |
| Ships with behavior | No | Yes (when configured) |

---

## What You Get

**The harness provides:**

- **Model access** — multi-provider, swap between local and cloud at runtime
- **Tool handling** — filesystem, shell, and search tools
- **Safety layer** — workspace constraints and sandbox isolation
- **Session memory** — conversation persistence across interactions
- **Observability** — tracing and logs via OpenTelemetry
- **Extension points** — skills, commands, lifecycle hooks

You supply behavior through AGENTS.md, commands, and skills.

---

## Demo

```bash
agent

Agent - Conversational Assistant
Version 0.1.0 • OpenAI/gpt-4o
──────────────────────────────────────────────────────────────────────────────
> Say hello to Alice

✓ Complete (2.9s) - msg:1 tool:0

Hello, Alice!

──────────────────────────────────────────────────────────────────────────────
> What was the name I just mentioned?

✓ Complete (1.2s) - msg:1 tool:0

You mentioned "Alice."

──────────────────────────────────────────────────────────────────────────────
> exit
Goodbye!
```

---

## Install

**macOS / Linux / WSL**

```bash
curl -fsSL https://raw.githubusercontent.com/danielscholl/agent-harness/main/install.sh | bash
```

**Windows PowerShell**

```powershell
irm https://raw.githubusercontent.com/danielscholl/agent-harness/main/install.ps1 | iex
```

---

## Quick Start

**1. Initialize configuration**

```bash
agent config init
```

**2. Run interactive chat**

```bash
agent
```

**3. Run a single prompt** (great for scripts)

```bash
agent -p "Say hello to Alice"
```

> **Tip:** `-p` prints clean text by default. Add `--verbose` for traces and execution detail.

---

## Configuration

The harness uses `~/.agent/config.yaml` to manage providers, memory, and observability.

```bash
# View current configuration
agent config show

# Provider setup
agent config provider local       # Docker/Ollama
agent config provider github      # GitHub Models
agent config provider openai      # OpenAI
```

See [docs/architecture/configuration.md](https://github.com/danielscholl/agent-base-v2/blob/HEAD/docs/architecture/configuration.md) for complete options.

---

## Usage

```bash
# Interactive chat
agent

# Validate config
agent --check

# Show exposed tools
agent --tools

# Single prompt
agent -p "Analyze this text"

# Switch providers/models on the fly
agent --provider openai -p "Hello"
agent --provider anthropic --model claude-sonnet-4-5-20250929 -p "Hello"
```

---

## Supported LLM Providers

| Provider | Type | Auth Method |
|----------|------|-------------|
| Ollama | Local | None |
| Docker | Local | None |
| Azure AI Foundry | Both | Azure CLI (`az login`) |
| GitHub Models | Cloud | GitHub CLI (`gh auth login`) |
| Azure OpenAI | Cloud | Azure CLI (`az login`) |
| OpenAI | Cloud | API Key |
| Anthropic | Cloud | API Key |
| Google Gemini | Cloud | API Key |

---

## Security Model

| Layer | Mechanism | Protection |
|-------|-----------|------------|
| Application | Workspace root constraints | Tools can't access files outside the workspace |
| OS | `--sandbox` flag | Docker container isolation for process and filesystem |

```bash
# Run with sandbox isolation
agent --sandbox -p "Analyze this codebase"
```

See [docs/guides/sandbox.md](https://github.com/danielscholl/agent-base-v2/blob/HEAD/docs/guides/sandbox.md) for details.

---

## Making it Yours

Agent Harness ships neutral. Here's how to configure it:

<img src="docs/images/harness-architecture.jpg" alt="Agent Harness architecture showing Skills and AGENTS.md defining the agent, with the harness providing tool handling, prompt presets, lifecycle hooks, filesystem access, and a safety layer" width="320">

### AGENTS.md

Create an `AGENTS.md` file in your workspace root to define agent behavior, goals, and constraints. The harness discovers and injects this into the system prompt.

### Custom Commands

Add slash commands in `~/.agent/commands/` to create reusable workflows. Commands are markdown files with YAML frontmatter.

### Skills

Install skills to add capabilities. Skills use progressive disclosure — they inject documentation only when relevant to the user's query.

### Claude Code Compatibility

Agent Harness supports the `.claude/` directory structure for Claude Code compatibility. This allows you to maintain a single set of workspace customizations that work across both tools:

```
<workspace>/.claude/
├── skills/           # Claude Code compatible skills
│   └── my-skill/
│       └── SKILL.md
└── commands/         # Claude Code compatible commands
    └── deploy.md
```

Skills and commands in `.claude/` are automatically discovered. If you have both `.agent/` and `.claude/` directories, `.agent/` takes precedence.

---

## Uninstall

**macOS / Linux / WSL**

```bash
rm -f ~/.local/bin/agent
rm -rf ~/.agent/repo ~/.agent/bin
rm -rf ~/.agent  # optional: remove config
```

**Windows PowerShell**

```powershell
Remove-Item "$env:LOCALAPPDATA\Microsoft\WindowsApps\agent.exe" -Force -ErrorAction SilentlyContinue
Remove-Item "$env:LOCALAPPDATA\Microsoft\WindowsApps\agent.cmd" -Force -ErrorAction SilentlyContinue
Remove-Item "$env:LOCALAPPDATA\Programs\agent-harness" -Recurse -Force -ErrorAction SilentlyContinue
Remove-Item "$env:USERPROFILE\.agent" -Recurse -Force -ErrorAction SilentlyContinue  # removes config, assets, and sessions
```

---

## Architecture

See [Architecture](https://github.com/danielscholl/agent-base-v2/blob/HEAD/docs/architecture/README.md).

---

## Contributing

See [CONTRIBUTING.md](https://github.com/danielscholl/agent-base-v2/blob/HEAD/CONTRIBUTING.md) for development setup, code quality guidelines, and contribution workflow.

---

## License

MIT — see [LICENSE](https://github.com/danielscholl/agent-base-v2/tree/HEAD/LICENSE).

Agent Harness

The rig. Not the driver.

A TypeScript runtime for configuring and running AI agents with any LLM.

What is a Harness?

A harness is infrastructure. It connects an AI model to tools and policies. Not intelligent itself, just reliable plumbing.

	Harness (this project)	Agent (the LLM)
Decides actions	No	Yes
Executes tools	Yes	No
Enforces safety	Yes	No
Has goals	No	Yes (when configured)
Ships with behavior	No	Yes (when configured)

What You Get

The harness provides:

Model access — multi-provider, swap between local and cloud at runtime
Tool handling — filesystem, shell, and search tools
Safety layer — workspace constraints and sandbox isolation
Session memory — conversation persistence across interactions
Observability — tracing and logs via OpenTelemetry
Extension points — skills, commands, lifecycle hooks

You supply behavior through AGENTS.md, commands, and skills.

Demo

agent

Agent - Conversational Assistant
Version 0.1.0 • OpenAI/gpt-4o
──────────────────────────────────────────────────────────────────────────────
> Say hello to Alice

✓ Complete (2.9s) - msg:1 tool:0

Hello, Alice!

──────────────────────────────────────────────────────────────────────────────
> What was the name I just mentioned?

✓ Complete (1.2s) - msg:1 tool:0

You mentioned "Alice."

──────────────────────────────────────────────────────────────────────────────
> exit
Goodbye!

Install

macOS / Linux / WSL

curl -fsSL https://raw.githubusercontent.com/danielscholl/agent-harness/main/install.sh | bash

Windows PowerShell

irm https://raw.githubusercontent.com/danielscholl/agent-harness/main/install.ps1 | iex

Quick Start

1. Initialize configuration

agent config init

2. Run interactive chat

agent

3. Run a single prompt (great for scripts)

agent -p "Say hello to Alice"

Tip: -p prints clean text by default. Add --verbose for traces and execution detail.

Configuration

The harness uses ~/.agent/config.yaml to manage providers, memory, and observability.

# View current configuration
agent config show

# Provider setup
agent config provider local       # Docker/Ollama
agent config provider github      # GitHub Models
agent config provider openai      # OpenAI

See docs/architecture/configuration.md for complete options.

Usage

# Interactive chat
agent

# Validate config
agent --check

# Show exposed tools
agent --tools

# Single prompt
agent -p "Analyze this text"

# Switch providers/models on the fly
agent --provider openai -p "Hello"
agent --provider anthropic --model claude-sonnet-4-5-20250929 -p "Hello"

Supported LLM Providers

Provider	Type	Auth Method
Ollama	Local	None
Docker	Local	None
Azure AI Foundry	Both	Azure CLI (`az login`)
GitHub Models	Cloud	GitHub CLI (`gh auth login`)
Azure OpenAI	Cloud	Azure CLI (`az login`)
OpenAI	Cloud	API Key
Anthropic	Cloud	API Key
Google Gemini	Cloud	API Key

Security Model

Layer	Mechanism	Protection
Application	Workspace root constraints	Tools can't access files outside the workspace
OS	`--sandbox` flag	Docker container isolation for process and filesystem

# Run with sandbox isolation
agent --sandbox -p "Analyze this codebase"

See docs/guides/sandbox.md for details.

Making it Yours

Agent Harness ships neutral. Here's how to configure it:

AGENTS.md

Create an AGENTS.md file in your workspace root to define agent behavior, goals, and constraints. The harness discovers and injects this into the system prompt.

Custom Commands

Add slash commands in ~/.agent/commands/ to create reusable workflows. Commands are markdown files with YAML frontmatter.

Skills

Install skills to add capabilities. Skills use progressive disclosure — they inject documentation only when relevant to the user's query.

Claude Code Compatibility

Agent Harness supports the .claude/ directory structure for Claude Code compatibility. This allows you to maintain a single set of workspace customizations that work across both tools:

<workspace>/.claude/
├── skills/           # Claude Code compatible skills
│   └── my-skill/
│       └── SKILL.md
└── commands/         # Claude Code compatible commands
    └── deploy.md

Skills and commands in .claude/ are automatically discovered. If you have both .agent/ and .claude/ directories, .agent/ takes precedence.

Uninstall

macOS / Linux / WSL

rm -f ~/.local/bin/agent
rm -rf ~/.agent/repo ~/.agent/bin
rm -rf ~/.agent  # optional: remove config

Windows PowerShell

Remove-Item "$env:LOCALAPPDATA\Microsoft\WindowsApps\agent.exe" -Force -ErrorAction SilentlyContinue
Remove-Item "$env:LOCALAPPDATA\Microsoft\WindowsApps\agent.cmd" -Force -ErrorAction SilentlyContinue
Remove-Item "$env:LOCALAPPDATA\Programs\agent-harness" -Recurse -Force -ErrorAction SilentlyContinue
Remove-Item "$env:USERPROFILE\.agent" -Recurse -Force -ErrorAction SilentlyContinue  # removes config, assets, and sessions

Architecture

See Architecture.

Contributing

See CONTRIBUTING.md for development setup, code quality guidelines, and contribution workflow.

License

MIT — see LICENSE.