arc

1. 安装并启动 DeepSeek Harness：npx @deepseek-ai/dsh web
2. 在终端执行上面的安装命令（CLI 会解析插件并核验来源）
3. 用 dsh plugins list 确认已安装，必要时重启 Harness 生效

插件以当前 dsh 进程的权限运行，安装时可能执行代码。请先通读仓库源码与许可证，确认无破坏性命令与越权访问；本站只做索引，不对第三方插件安全性作担保。

事实信息来自公开插件目录快照（2026-10-01），介绍文案由本站再加工。

以下为插件仓库 README 全文（原始内容，由公开目录抓取整理）。

# ARC

Agent Research Copilot (ARC) is a research toolkit for theoretical
physics. It supports paper discovery and analysis, research-domain
construction, proposer-reviewer loops, translation, companion readers, and
source-aware calculation workflows.

ARC is designed for coding-agent hosts such as Codex, Claude Code, and similar
agents.

## Who ARC is for

Use ARC when you need to:

- acquire, parse, search, or summarize research papers;
- construct a source-aware research domain from seed literature;
- run proposer-reviewer idea or calculation loops;
- translate scientific sources or build chapter-aware companion readers; or
- use durable, inspectable research workflows instead of ad hoc
  prompts.

## Citation

If ARC has played a role in your research, please consider citing the ARC manual.

Yanjiao Ma, Yi Wang, and Xingkai Zhang. _ARC: An LLM-Native Agent
Workflow for Theoretical Physics Research_. ChinaXiv:202606.00234, 2026.
https://chinaxiv.org/abs/202606.00234

```bibtex
@misc{ma2026arc,
  title         = {{ARC}: An {LLM}-Native Agent Workflow for Theoretical Physics Research},
  author        = {Ma, Yanjiao and Wang, Yi and Zhang, Xingkai},
  year          = {2026},
  month         = jun,
  publisher     = {ChinaXiv},
  eprint        = {202606.00234},
  archivePrefix = {ChinaXiv},
  url           = {https://chinaxiv.org/abs/202606.00234},
  note          = {Version 1}
}
```

## Install

### Remarks:

- Permission: the same as many heavy skills/plugins, ARC will need permissions to run Python scripts. Accepting permissions could be annoying. We recommend installing ARC within docker or a virtual machine, and allow all permissions in that virtual environment. As always for working with AI agents, be aware of risk to your data and system.

- Token usage. As measured using Claude + DeepSeek, a typical run of domain build + idea generation consumes about 1M uncached input tokens, and 0.5M output tokens, in about an hour's running time. The token usage may vary depending on the specific tasks and LLM used. Be aware of token usage and costs.

### Codex

```bash
codex plugin marketplace add tririver/arc --ref stable
codex plugin add arc@arc
```

### Claude Code

```text
/plugin marketplace add tririver/arc@stable
/plugin install arc
```

### Other coding agents

Give your coding agent this repository and ask it to inspect the repository and
install ARC for its environment.

### DeepSeek Harness

Install the DSH-compatible ARC bundle from npm:

```bash
dsh plugin --profile web add @troywjz/arc-dsh
```

For a pinned GitHub release instead:

```bash
dsh plugin --profile web add github:troywjz/arc#v0.1.1
```

For local development, install a checkout directly:

```bash
dsh plugin --profile web add /path/to/arc
```

After installation, verify the composed profile with:

```bash
dsh plugin --profile web list
dsh --profile web --dump-config
```

The DSH adapter registers the ARC Skill, ARC command wrappers, and a local
bridge to DSH's native model runtime. GitHub source installation and the npm
package both pin the ARC runtime to the matching release tag.

## Start with ARC

After installing ARC, ask for the research outcome directly:

```text
Use ARC to summarize a paper.
Use ARC to build a domain from arXiv:0911.3380 with new papers since 2024.
Use ARC to develop and review ideas from the resulting domain.
Use ARC to check this calculation.
```

An installed ARC plugin exposes its bundled Skill and manuals to the agent.
Those manuals provide task-oriented quick starts; built-in `--help` provides
exact commands, options, and error guidance.

## Development and release

ARC development requires Python 3.11 or newer. Read `AGENTS.md` before making
changes.

Keep research runs and generated output below the git-ignored `local/` tree.

Run focused package tests first, then the combined offline test and build
checks:

```bash
python -m pytest --import-mode=importlib packages/*/tests
scripts/check-packages.sh
```

Network and live-model tests are opt-in. Do not use them as the default
development check.

Releases are explicit human operations from a clean release checkout:

```bash
scripts/release-arc.sh
```

The helper validates the release, updates package and plugin versions, and
pauses before its mutating Git steps. See `AGENTS.md` for repository
development, verification, and release constraints.