mddl harness

Visual orchestrator for DeepSeek Harness. Drag models and tools onto a canvas, then export a real cordis.patch.yml overlay.

This is not a fork of dsh and not a child-process wrapper around npx @deepseek-ai/dsh. Upstream already ships a web profile, Cordis patches, and session/event telemetry. We compile graphs into that overlay format so the work can later mount as a dsh-plugin.

Why this stack

Packages

• @mddl/graph-schema — graph IR and the shipped DSH row catalog
• @mddl/compiler — graph → Cordis patch YAML, plus overlay linting
• @mddl/studio — visual editor
• dsh-blueprint — Blueprint tab inside the DSH web client (readme)

Run

pnpm install
pnpm dev

Studio: http://localhost:5173

pnpm test
pnpm typecheck

The canvas is saved to localStorage as you edit, so a reload keeps your graph. Reset in the header restores the starter graph.

Find modules in the palette by name, row id, package, or description. Press / to jump to search, and Not on canvas hides what you already placed.

Apply an exported overlay. --patch is resolved from your terminal cwd, not the studio. Running ./cordis.patch.yml from ~ looks for /Users/<you>/cordis.patch.yml.

After Export (typical macOS download):

npx @deepseek-ai/dsh web --patch "$HOME/Downloads/cordis.patch.yml"

Or use the starter overlay in this repo (from the repo root):

npx @deepseek-ai/dsh web --patch "$PWD/examples/cordis.patch.yml"

What Phase 1 does not do

Live harness execution, profile install, or a DSH client slot. "Preview telemetry" is a local animation that proves the glow/edge path. Real run state comes from session/event in a later phase.

Roadmap

Shipped in dsh-blueprint 0.2.0: reading the live loader tree, and linting the config you actually booted (failed entries, entries stuck waiting on a service, disabled rows something still requires). Next, in order:

1. Write the overlay back, behind a marker-delimited block that leaves hand-written YAML untouched: revision check, backup, atomic replace, and verification that the running tree matches before the change is kept.
2. Import the live tree onto the canvas, so you can edit the config you have rather than rebuild it.
3. Map session/event onto canvas telemetry, and English/中文 both first class.

Status

Early. DSH is itself a developer preview with breaking changes between release candidates, so the row ids and patch shape here track a moving target. Verified against @deepseek-ai/dsh 0.1.0-rc.7.

License

MIT. See LICENSE.