deepseekplugins

DeepSeek Harness plugin

dsh-media-gen

Plan and execute Atlas Cloud image, video, audio, and 3D workflows in DeepSeek Harness.

Tools & Capabilities
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Source facts

Repository
AtlasCloudAI/dsh-media-gen
Latest update
Aug 17, 2026
Category
Tools & Capabilities
GitHub stars
0
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/AtlasCloudAI/dsh-media-gen
Plugin: dsh-media-gen
Author: AtlasCloudAI

Check the source files

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

File explorer4 files
README.mdSource · read only
README language

dsh-media-gen

简体中文

Turn one media brief into a model choice, production-ready prompt, and—when you opt in to MCP—an executable Atlas Cloud workflow.

dsh-media-gen is an independent DeepSeek Harness profile bundle maintained by AtlasCloudAI. It covers image, video, audio, and 3D workflows. The three Skills become discoverable after installation; the optional Atlas Cloud MCP bridge is included but disabled by default.

Quick start

Install the bundle into the DSH profile where you want to use it:

dsh plugin --profile web add 'github:AtlasCloudAI/dsh-media-gen#v0.2.0'
dsh --profile web --dump-config

Use --profile headless instead for a headless profile. Pin a release tag or full commit for reproducible installations.

Try it

Start that DSH profile and paste this no-submit demo:

> Plan an 8-second coffee product video. Compare Seedance with one available alternative, recommend a model, and produce a three-shot storyboard, final prompt, and exact parameters. Do not submit generation; wait for my confirmation.

Depending on the request, DSH can use the bundled Skills to compare model approaches, turn the brief into a coherent storyboard, and prepare the selected model's input. The demo does not ask DSH to submit a generation request.

What each component does

ComponentProblem it solvesTypical result
atlas-cloud SkillWhich Atlas Cloud model, API, and schema should I use for image, video, audio, 3D, ASR, or LLM work?A model ID, validated parameters, and a REST, CLI, or MCP execution path.
seedance-2-5-skill SkillHow do I plan a controllable, consistent Seedance video across shots and references?A storyboard, continuity plan, and Seedance-ready prompt and parameters.
universal-video-prompt-skill SkillHow do I reuse one video brief across different generation models?One model-neutral prompt specification plus model-specific compilations.
Optional atlascloud-mcp@1.5.0How can DSH call supported Atlas Cloud operations without hand-wiring each request?Tools for model and schema lookup, media upload, generation, polling, and account usage checks.

In short: Skills teach DSH how to plan and integrate; MCP gives it callable execution tools.

Credentials and execution

Installing and discovering the Skills requires no Atlas Cloud credential and submits no Atlas Cloud API request.

For execution, obtain a key from the Atlas Cloud console and set it in the process that starts DSH:

export ATLASCLOUD_API_KEY="<your-key>"

Do not paste the key into chat or commit it to this repository.

Enable MCP execution (optional)

The bundle's atlascloud-mcp row is disabled by default because a stdio MCP server is a trusted child process that runs outside the agent sandbox.

To opt in, add this later-layer override to the target profile's $DSH_HOME/profiles/<profile>/cordis.patch.yml:

- id: atlascloud-mcp
  disabled: false

Restart the profile and inspect the resolved configuration:

dsh --profile web --dump-config

DSH exposes qualified tool names such as mcp__atlascloud__atlas_list_models; the underlying MCP tool name remains atlas_list_models. Operations that submit generation or transcription can be billable, so review the exact model and parameters before approving a submission.

Compatibility

OpenAI/Codex plugins and DSH bundles use different host manifests. The Skill content can be reused, but the host integration cannot be installed unchanged: DSH requires package.json with dsh.bundle.patch and a Cordis MCP row. This repository uses the current DSH profile-bundle format, not the retired .dsh-plugin format.

See [the full compatibility decision](docs/compatibility.md).

Provenance and verification

The Skills are synchronized from AtlasCloudAI/atlas-cloud-skills. [skills/SOURCE.json](skills/SOURCE.json) records the exact source commit and local DSH adaptations.

npm test
npm pack --dry-run

The checks validate the bundle manifest, default-off MCP policy, pinned MCP executable, Skill frontmatter, public-language guard, source pin, and packaged relative resources. They do not submit generation, upload media, transcribe audio, or call a billable Atlas Cloud endpoint.

License

[MIT](LICENSE)

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