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

Component	Problem it solves	Typical result
atlas-cloud Skill	Which 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 Skill	How 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 Skill	How do I reuse one video brief across different generation models?	One model-neutral prompt specification plus model-specific compilations.
Optional [email protected]	How 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.

Provenance and verification

The Skills are synchronized from AtlasCloudAI/atlas-cloud-skills. 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