deepseekplugins

DeepSeek Harness 插件

dsh-peak-avoidance

DeepSeek Harness 高峰期模型自动切换插件：高峰前自动切到指定替代模型，高峰后切回官方模型。· Auto-switch to an alternate model before DeepSeek peak hours and back to the official model afterwards. · 本插件由 AI 全权开发，作者无编程经验，请自行测试安全性；安装说明可能含（英文原文）

模型与服务商
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来源信息

GitHub 仓库
yuzuki-natsumi/dsh-peak-avoidance
最近更新
2026年8月17日
分类
模型与服务商
GitHub stars
0
载体类型
plugin
目录证据
上游声明已找到 dsh.bundle
证据路径
package.json#dsh.bundle
核对版本
0.1.0-rc.8
上游核对日期
2026-08-20

该证据由上游目录提供。本站没有安装、运行或安全审核这个插件。

安装

默认先复制一段 Prompt，让 Agent 读 GitHub 仓库和源码；需要自己装时再切到命令。

复制这段 Prompt，发给 DSH、Codex 或其他 Agent，让它先读 GitHub 仓库和源码。

请先不要安装或执行任何命令。阅读这个插件的 GitHub 仓库、README 和关键源码，然后用清楚、直接的方式回答以下问题，帮助我判断它是否适合我的需求：

1. 这个插件是什么，解决什么问题；
2. 适合哪些用户和典型使用场景；
3. 安装后如何使用，并给出一个最小使用示例；
4. 有哪些已知限制，以及隐私、安全、兼容性或维护风险；
5. 给出“推荐 / 有条件推荐 / 不推荐”的明确建议和理由。

请区分仓库明确说明、根据源码推断和未知信息。证据不足时请明确说明，不要猜测或照抄 README。

GitHub：https://github.com/yuzuki-natsumi/dsh-peak-avoidance
插件名：dsh-peak-avoidance
作者：yuzuki-natsumi

检查来源文件

安装前先看这个插件目录里的 README 和其他文件。

文件资源管理器3 个文件
README.md来源说明 · 只读预览

dsh-peak-avoidance

Auto-switch to an alternate model before DeepSeek peak hours and back to the official model afterwards — avoiding official peak-hour pricing.

![npm version](https://www.npmjs.com/package/dsh-peak-avoidance) ![npm downloads](https://www.npmjs.com/package/dsh-peak-avoidance) ![License: MIT](LICENSE) ![Node](package.json)

Maintainer: 柚木夏实 · Code written by AI (DeepSeek Harness)

Disclaimer

> This plugin was developed entirely by DSH (AI). The author has no programming experience, and the code has not been professionally reviewed. > Users must test it themselves and judge its safety, stability, and correctness before use. > The installation instructions in this repository may contain AI hallucinations (inaccurate or nonexistent steps, package names, or paths) — verify everything before executing. > The author accepts no liability for any consequences of using this plugin.

Features

  • Scheduled switching: enter avoidance at window start − leadMinutes (default 30), restore at window end.
  • Both routes: agentDefaultModel (default route) + apiProxy.sessions.selectModel (live sessions, takes effect next turn).
  • Multiple windows, cross-midnight supported (e.g. 22:00-02:00).
  • Reasoning effort per model (high, …), dropdown populated from the live model catalog.
  • Provider/model dropdowns fetched live from the llm service.
  • Switch toast: frame-wide banner on enter/exit (toggleable; polling stops when off).
  • Manual control: card buttons plus model tools peak_avoidance_status / peak_avoidance_control.
  • Safe: sessions manually reverted during peak are never forced back; originals are restored on stop (restoreOnStop).

Install

Option 1 — npm (recommended for DSH users):

npm install dsh-peak-avoidance

> The @deepseek-ai runtime deps are peerDependencies, provided by DSH itself — nothing extra to install. Installing outside DSH requires providing the peers (@deepseek-ai/dsh-settings, @deepseek-ai/dsh-tools, @deepseek-ai/cordis) yourself.

Option 2 — from source: clone this repo and place lib/ + package.json into a DSH-resolvable directory (e.g. $DSH_HOME/profiles/node_modules/dsh-peak-avoidance/).

Both options then require appending to $DSH_HOME/cordis.patch.yml:

- insert:
    - id: peak-avoidance
      name: 'dsh-peak-avoidance'

and restarting DSH.

Usage

  • Settings → Plugins → Configurable → Peak Avoidance card: status, config, manual enter/restore.
  • Config lives in DSH settings (peak-avoidance section of settings.yaml); changes apply immediately.
  • Required: peakModel (avoidance target) and normalModel (official model; copy the current default on first run).

Privacy & security

  • No API keys are read, stored, or emitted; only model selections and its own config.
  • The client bridge accepts loopback requests only.
  • All catalog/model/effort data comes live from the DSH llm service — no deployment-specific hardcoding.

Development

  • No build step: lib/index.js (host, Cordis plugin module) + lib/client.js (browser, module-loader format).
  • Deps: @deepseek-ai/dsh-settings, @deepseek-ai/dsh-tools, @deepseek-ai/schemastery.

License

MIT

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