DeepSeek Harness plugin

dsh-promotion-toolkit

DeepSeek Harness-native publicity toolkit: turn any long-form source into a source-grounded, platform-native promotion matrix.

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Source facts

Repository
lhmd/dsh-promotion-toolkit
Latest update
Aug 13, 2026
Category
Remote & Mobile
GitHub stars
9
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/lhmd/dsh-promotion-toolkit
Plugin: dsh-promotion-toolkit
Author: lhmd

Check the source files

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

File explorer4 files
README.en.mdSource · read only
README language

DSH Promotion Toolkit

中文 README · Live showcase · [Live demo set](examples/live-demos.md)

> Turn any idea into platform-native publicity.

![DeepSeek Harness](https://github.com/deepseek-ai/deepseek-harness) ![Model](examples/live-demos.json) ![License](LICENSE)

![DSH Promotion Toolkit preview](docs/preview.svg)

What it does

DSH Promotion Toolkit is a DeepSeek Harness-native plugin for turning a product, open-source project, article, course, event, personal point of view, or rough idea into platform-native publicity.

It extracts the thesis, quotable evidence, risk flags, and canonical URL first. Then it changes the reading path for every platform instead of shrinking one paragraph seventeen times.

Any idea / source / README
            |
            v
Thesis + evidence + claim boundaries + canonical URL
            |
            v
17 native long-form drafts, posts, video scripts, and CTAs

Platform-native by design

SurfaceDraft format
XiaohongshuPain-point opening, saveable checklist, restrained emoji, hashtags, CTA
ZhihuMarkdown explainer with conclusion, background, method, limits, and source link
WeChatLong-form article with title, lead, sections, examples, and ending
WeChat MomentsShort personal share with human tone and controlled information density
Bilibili / Douyin / KuaishouShots, timestamps, voiceover, captions, cover title, and CTA
Weibo / X / ThreadsConcise, opinionated openings with platform-specific interaction prompts
LinkedInProfessional context, product background, lessons, and discussion-led CTA
RedditCommunity context, question-led title, evidence, and restrained self-promotion
TikTok / YouTubeShort-video script with visuals, voiceover, captions, and closing prompt
MediumEnglish long-form structure, section headings, context, and source link
Facebook / InstagramCommunity share or visual short copy with emoji, tags, and canonical URL

Supported surfaces: xiaohongshu, zhihu, wechat, wechat_moments, weibo, bilibili, douyin, kuaishou, x, threads, linkedin, reddit, tiktok, youtube, medium, facebook, and instagram.

Real DeepSeek demo

The checked-in fixture was generated end to end with deepseek-v4-pro: four long-form sources, Chinese and English output, and 17 platform drafts per language. One source is this repository, so the examples are ready to publish.

English LinkedIn

One source should not become the same paragraph everywhere.

DSH Promotion Toolkit turns a product story, open-source project, article, course, event, or personal idea into platform-native publicity. It extracts the thesis, evidence, risk flags, and canonical URL first, then changes the reading path for each surface.

Source and live examples: https://github.com/lhmd/dsh-promotion-toolkit

English X

Tired of rewriting one idea for every platform?

DSH Promotion Toolkit extracts the claims and evidence first, then generates native drafts for X, LinkedIn, Reddit, Zhihu, Xiaohongshu, video platforms, and more. Same source. Different entry points. Canonical links stay attached.

Repo: https://github.com/lhmd/dsh-promotion-toolkit

See the [full JSON fixture](examples/live-demos.json), [readable code-block excerpts](examples/live-demos.md), or the bilingual showcase.

Install into DeepSeek Harness

This repository follows the DSH profile-bundle shape. cordis.patch.yml mounts the package; src/index.js exports apply(ctx) and registers the viral_kit tool; src/skill.js provides the runtime Skill; and skills/viral-kit/SKILL.md is the readable mirror.

npm install -g @deepseek-ai/dsh
dsh plugin --profile web add /absolute/path/to/dsh-promotion-toolkit
dsh web

For local development:

npm test
npm run check:release
npm run demo

CLI

node scripts/viral-kit.mjs \
  --text "Paste your product brief, article, course, event, or idea" \
  --language auto \
  --platform linkedin \
  --source-url https://github.com/lhmd/dsh-promotion-toolkit \
  --json

Language routing is platform-aware: Chinese surfaces default to Chinese; global surfaces default to English. An explicit --language zh|en|auto always wins. Pass --source-url when the source has a repository, product page, article, signup page, or other canonical link. The plugin places that URL in the platform-native CTA and never invents one.

Output contract

Every call returns structured JSON with the thesis, evidence, shareability signals, title angles, platform drafts, image prompt, hashtags, and risk flags:

{
  "coreIdea": "A source-grounded thesis",
  "evidence": ["Evidence to preserve"],
  "shareability": {"score": 0, "signals": []},
  "titles": ["Angle one", "Angle two", "Angle three"],
  "platformDrafts": {
    "xiaohongshu": "Saveable note",
    "zhihu": "Markdown explainer",
    "wechat_moments": "Short personal share"
  },
  "riskFlags": ["Verify before publishing"]
}

The model can polish language but must not add unsupported users, customers, metrics, dates, prices, outcomes, or links. Verify attribution, numbers, dates, and absolute claims before publishing.

Live showcase

Open the bilingual showcase to switch between four DeepSeek examples, Chinese / English, and 17 platform tabs. The source is [docs/](docs/).

License

MIT