Yichen Jiang 59e759ce13 fix(tasks-local): layer control surfaces and listeners by registering scope
One host registry serves every composition in the process, so its two
service-wide collections answered per-owner questions process-wide. `start()`
asked only whether SOME surface was attached, so an agent whose own composition
loads no `tool-tasks` could start work it has no tool to collect or stop as soon
as any other preset attached one — and the answer changed depending on which
sessions happened to be open. `settle()` walked every registered listener, so a
task settling without a waiter injected one completion notice per mounted
preset into the same owner.

Both collections now sit in `ScopedLayers`, the layered-registry primitive
`tools` and `skills` already use: a registration files into its registering
context's scope, and a read unions the global layer with the owner's scope
chain. A surface or listener registered from an unscoped context lands in the
global layer and serves every owner, which is exactly the host-plane
composition's own controls, so the TUI path is unchanged without a special
case.

This supersedes the consumer-side filter in the previous commit. That filter
produced the right notices but sat in the wrong layer: it left the `start()`
gate process-wide, it could not be enforced against a producer that resolves
the registry directly, and it made a Consumer carry scope knowledge that the
other layered registries keep in the registry. `tool-tasks` is scope-agnostic
again and the `dsh-scope` edge moves to `tasks-local`.

`start()`'s refusal is now owner-relative, so its model-visible text names the
agent rather than the process. The shipped `minimal` preset keeps
`enableRunInBackground: false`, no longer as the safety boundary — the registry
owns that now — but so an agent that could never collect a task is not offered
the parameter at all.

Refs #2141
2026-08-10 16:12:41 +08:00

DeepSeek Harness

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DeepSeek Harness (dsh) is an open-source coding agent built on the DeepSeek Harness SDK.

It uses an architecture where everything is a plugin.

Internal testing notice

DeepSeek Harness is under internal testing. Features and interfaces may change.

The internal build uploads all Session Logs by default to help diagnose reported problems. Set DSH_TELEMETRY_DISABLED=1 to disable telemetry. Send feedback through the internal WeChat group.

Install

Clone the repository, then run the installer:

git clone <repo-url>
cd deepseek-harness
scripts/install.sh

The installer requires git and Node ^22.19 || >=24, offers to install pnpm when it is missing, prompts for a DeepSeek API key, builds the required repository artifacts, and launches the Web UI.

The default active checkout is ~/.dsh/source/current, and the launcher is linked into ~/.local/bin. Re-run the installer to update. scripts/install.sh owns alternate locations, update mechanics, and recovery options.

Use DeepSeek Harness

Web UI

For the recommended local interface, choose Web UI when the installer finishes. To start it later, or after updating the active checkout, build the repository and run:

(cd ~/.dsh/source/current && pnpm run build)
dsh web

The path above is the installer's default. If you set DSH_SOURCE or DSH_CURRENT, or reused an existing checkout, replace ~/.dsh/source/current with that checkout path; see scripts/install.sh for details. The Web UI is served at http://127.0.0.1:3080 by default.

Profiles

dsh boots profiles — ordered stacks of plugin-bundle patch layers under your own overrides in $DSH_HOME/profiles/<name>:

dsh --profile web                       # the browser UI (same as: dsh web)
dsh plugin --profile tui add <package>  # install a plugin into a custom profile
dsh --profile tui                       # boot it

The CLI contract describes profile layout, layer semantics, and config dump commands.

Headless

Run one task, print the final answer, and exit:

dsh run "summarize this workspace"

Automation and SDKs

From a source checkout with DEEPSEEK_API_KEY in the environment or its root .env, start the ACP automation server:

pnpm run demo:acp

The Python SDK drives a bundled JSON-RPC runtime. The examples cover the runnable headless, ACP, JSON-RPC, Code Mode, and self-referential compositions.

Why DeepSeek Harness

Built-in capabilities cover file reading, editing, and search; shell and persistent PTY execution; reusable skills; task tracking, goals, plans, todos, and background tasks; subagents and workflows; sandboxing and approvals; settings and credentials; persistent, resumable, forkable, and queryable sessions; LSP and web access; context compaction; and telemetry. Each composition selects the subset appropriate to its surface. The Web UI includes Plan Mode.

  • Everything is a plugin. Models, tools, policies, storage, context management, and interfaces are composable Cordis plugins, so deployments can extend or replace behavior without forking the agent loop. See the architecture for the underlying design.
  • Runs are reconstructable. Anything visible to the model is logged in the authoritative session stream; persistence, resume/fork/query, replay, telemetry, and UIs derive from the same events. See the session-log architecture.
  • Code Mode (opt-in). It exposes a run_code tool and a generated TypeScript SDK; only program output re-enters model context. See Code Mode.
  • Self-referential Cordis tools are opt-in. They let the agent inspect its live runtime and mount or unmount plugins while it runs. See the Cordis tools.

Community

Follow DeepSeek Harness on Twitter for project updates.

Development

Start with the development guide and read the architecture before changing packages.

For agents, follow AGENTS.md.

DeepSeek Harness is currently in internal testing.

License

BSD 3-Clause

Third-party dependencies and their licenses are disclosed in THIRD_PARTY_NOTICES.md.

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