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H3 Seg Prompt Design — DSH Plugin for DeepSeek Harness
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dsh-h3-seg-prompt-design

H3 Seg Prompt Design

H3 long-video segmented prompt design skill bundle for DeepSeek Harness

The plugin will be installed here. Keep web if you are unsure.

npx -y @deepseek-ai/dsh plugin --profile web add github:northern-penguin/dsh-h3-seg-prompt-design#4f94409369b1acafa920a3df8ae30c028a37ad68
READMECompatibilityVersions

Compatibility and provenance

H3 Seg Prompt Design is published as dsh-h3-seg-prompt-design and currently resolves to version 0.1.0. The Hub verifies its manifest and preserves the exact installation source for reproducible installs.

DSH compatibility
*
Runtime surfaces
any
Release source
github
Registry updated
9/2/2026

Versions

0.1.0stable
9/2/2026
Latest
0.1.0
DSH
*
HMR
Process restart
Tree shaking
Safe tree shaking not declared
Unpacked size
Unavailable
Files
Unavailable
Surface
any
License
MIT
Source
github
GitHub
★ 0
Weekly downloads
0
Last push
9/2/2026
View source ↗
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README

dsh-h3-seg-prompt-design

An installable DeepSeek Harness plugin bundle that registers the h3-seg-prompt-design skill. The skill turns a long-form H3 video idea into a locally organized, repeatable package of H3-compliant per-segment prompts.

H3 generates at most 15 seconds per call, so a long video is produced by looping many generation segments. This skill manages the whole loop: brainstorming, locking reference assets, designing 5–15 second segments, and writing the prompts for each segment.

What it does

  1. Inspiration — when you have no concrete concept, propose several distinct, segment-friendly directions.
  2. Project folder — once a theme exists, create a folder named after the video theme inside the workspace.
  3. Asset mapping — confirm your reference images / videos / audio, assign unique aliases, and write 素材映射.md (paths may stay empty so prompts can be planned before assets exist; a reference video's picture and its companion audio are two independent assets).
  4. Storyboard — expand the idea into 5–15 second segments, estimate each duration, mark spans that continue across segments with (接续分镜NN), and write 分镜设计.md. Enforces H3's per-generation caps: ≤9 images, ≤3 videos, ≤3 audio tracks.
  5. Prompts — write H3分镜提示词.md following the official H3 guide, except reference assets are cited as {{ref:别名}} (companion audio as {{ref:别名.audio}}) instead of the official <Picture N> / <Video N> / <Audio N> numbering.

Install

The bundle is a plain package with a dsh.bundle.patch declaration and no build step. Install it into a profile with dsh plugin (which forwards to pnpm):

# From a local checkout (the plugin folder itself):
dsh plugin --profile web add .

# Or from a published git repo:
dsh plugin --profile web add github:<owner>/dsh-h3-seg-prompt-design

Git-hosted plugins that ship a prepare build need pnpm's allowBuilds allowance; this bundle ships committed plain-JS, so no build allowance is required.

After the profile starts, the skill appears in the model's skill catalog. Use it by asking for segmented H3 prompts, or invoke it directly with /h3-seg-prompt-design.

Layout

dsh-h3-seg-prompt-design/
├─ package.json            # dsh.bundle.patch → ./cordis.patch.yml
├─ cordis.patch.yml        # mounts the provider plugin
├─ index.js                # Cordis plugin: registers the skill on ctx.skills
└─ skill/                  # the bundled skill (resourceBase)
   ├─ SKILL.md             # workflow + invariants
   ├─ references/          # workflow rules + the two official H3 guides
   ├─ assets/              # 素材映射 / 分镜设计 / H3分镜提示词 templates
   └─ scripts/
      └─ validate_project.py

Notes

  • The skill name is h3-seg-prompt-design; the npm package is dsh-h3-seg-prompt-design.
  • index.js has no runtime dependencies — skills resolves as a Cordis service, so the package needs nothing beyond the dsh installation.
  • Keep the provider DESCRIPTION in index.js in sync with the skill summary you want shown in the catalog.
  • Replace MIT with your preferred license before publishing; no LICENSE file ships here.