deepseekplugins

DeepSeek Harness plugin

dsh-airp

AIRP engine for DeepSeek Harness: WorldKernel + DSH host adapter

Tools & Capabilities
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Source facts

Repository
clarkzhao/dsh-airp
Latest update
Aug 20, 2026
Category
Tools & Capabilities
GitHub stars
1
Format
plugin
Catalog evidence
Upstream dsh.bundle evidence
Evidence path
package.json#dsh.bundle
Checked against
0.1.0-rc.8
Upstream check date
2026-08-20

This evidence comes from the upstream catalog. This site has not installed, run, or security-reviewed the plugin.

Install

Start with a prompt that asks an agent to review the GitHub repository and source. Switch to the command if you want to install it yourself.

Copy this prompt into DSH, Codex, or another agent and ask it to review the GitHub repository and source first.

Do not install or run any commands yet. Read this plugin's GitHub repository, README, and relevant source code. Then answer the questions below clearly and directly so I can decide whether it fits my needs:

1. What is this plugin, and what problem does it solve?
2. Who is it for, and what are its typical use cases?
3. How is it used after installation? Include one minimal example.
4. What known limitations or privacy, security, compatibility, or maintenance risks does it have?
5. Give a clear recommendation: recommend, conditionally recommend, or do not recommend, with reasons.

Distinguish statements documented by the repository, inferences from source code, and unknowns. If evidence is insufficient, say so explicitly. Do not guess or simply repeat the README.

GitHub: https://github.com/clarkzhao/dsh-airp
Plugin: dsh-airp
Author: clarkzhao

Check the source files

Read the README and other files from this plugin directory before installing.

File explorer3 files
README.mdSource · read only

dsh-airp

DeepSeek Harness 上的 AIRP 引擎：深 module WorldKernel + 浅 Host adapter。

  • GitHub：https://github.com/clarkzhao/dsh-airp
  • topic：dsh-plugin
  • 规范：[docs/engine.md](docs/engine.md) · agent 入口：[AGENTS.md](AGENTS.md) · 术语：[docs/glossary.md](docs/glossary.md) · 写包：[docs/worldbook-authoring.md](docs/worldbook-authoring.md) · 规划：[ROADMAP.md](ROADMAP.md)

一句话：LLM 只提案和叙述；规则把 State 从 T 写成 T+1。

能力

  • WorldKernel.turn / match：鉴定、叙事事实、GM、检索
  • Pack.load / validate / catalog：YAML 索引 + Markdown 细节；bundled + ~/.dsh/airp-packs + 自定义路径
  • 官方示例（不是产品主线）：packs/lotm-tingen、packs/jzdh-dingjiang。自己的包写到 ~/.dsh/airp-packs/
  • 工具名必须匹配 ^[a-zA-Z0-9_-]+$：lore_get / state_read / check_propose / state_propose_fact / check_match / pack_validate / pack_scaffold / pack_open_play / pack_interview

世界包生态

世界包是数据，不是插件代码。引擎只认目录里有没有合法的 pack.yaml。

packs/lotm-tingen/          # 官方 demo，进 git
packs/jzdh-dingjiang/       # 官方 demo，进 git
packs/<your-id>/            # 本地实验；默认被 .gitignore
~/.dsh/airp-packs/<id>/     # 推荐的用户/社区安装位置
任意/含 pack.yaml 的目录     # 开局卡底部粘贴路径

消费者（airp-play）开局选包；创造者（airp-author）用 pack_interview 取 8 问 → ask_user_question → pack_scaffold → 改文件 → pack_validate → pack_open_play。pack_open_play 不会热切本会话：已有产出不能换 preset，交接卡只告诉你新开一条 airp-play 并粘贴路径。

分享一个包：复制 templates/community-pack/，或把目录打成 zip / 开独立 git 仓。别人解压到 ~/.dsh/airp-packs/<id>/ 即可。本地校验：

npm run pack:validate -- ~/.dsh/airp-packs/my-pack

不要把社区包 PR 进本仓 packs/，除非它要成为下一个官方 demo。Issue 用仓库模板（pack / authoring / engine），说明见 [CONTRIBUTING.md](CONTRIBUTING.md)。

开发

npm install
npm test
npm run typecheck
npm run build

安装到 DSH web profile

dsh plugin --profile web add /path/to/dsh-airp
# 或
npx @deepseek-ai/dsh plugin --profile web add /path/to/dsh-airp

预设（从本仓复制，不要带 tool-cordis，也不要在 play preset 里挂 play-mask：tools.restrict 在挂载时全局工具表还是空的，New Session 会失败）：

cp -R presets/airp-play ~/.dsh/.agent-presets/airp-play
cp -R presets/airp-author ~/.dsh/.agent-presets/airp-author
  • AIRP 消费者（airp-play）会弹「加载世界」卡：新建或空白会话切到该 preset 都会问一次。
  • AIRP 创造者（airp-author）会弹「编辑世界」卡，并可「从零写一个新世界包」。
  • 卡片底部可粘贴含 pack.yaml 的目录；选自定义后不会再静默掉回廷根。

sandbox 只能写工作区。用户包推荐写到 ~/.dsh/airp-packs/（host 插件写盘，不经过 agent sandbox）。

/retry 由 HostRuntime 回放事件、把 State 裁到上一 check 之前；若 DSH 上有 sessions.fork 会顺带分叉会话日志。Kernel 自己不做时间旅行。

IC 文本按当前包的 pack.yaml tags 词表打标；命中则 Host 在 agent/pre-step 先 match，再让模型只叙述。

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