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dsh-acp

dsh plugin to run DeepSeek Harness (dsh) agents in Zed’s Agent Panel.

Stars
2
Language
JavaScript
Created
Sep 3, 2026
Updated
Oct 1, 2026
GitHub repo

Introduction

dsh-acp-v1

dsh-acp-v1 is, at heart, a dsh plugin: it supplies the ACP capabilities missing from dsh's built-in ACP, and serves the DeepSeek Harness to the Zed editor as a custom ACP agent-server extension (an interactive ACP v1 server).

Run DeepSeek Harness agents inside Zed's Agent Panel over the Agent Client Protocol (v1): create/close threads, stream text + reasoning, live tool cards, plan updates, slash commands and installed agent skills, session history, permissions, model/thought-level/preset selects, elicitation forms — while every tool runs inside the dsh sandbox with dsh's own model route.

Requirements

  • dsh CLI (tested on 0.2.0-rc.2) — install globally first:

    npm install -g @deepseek-ai/dsh@0.2.0-rc.2
    dsh --version   # → 0.2.0-rc.2
    
  • pnpm (the dsh plugin command delegates to pnpm)

  • Zed with the Agent Panel (ACP v1)

  • A DeepSeek API key: DEEPSEEK_API_KEY env var, or configured once in dsh Web (Models settings → writes ~/.dsh/.credentials.yaml)

Install

The plugin is installed as a profile bundle. Pick a profile name (the examples use acp); the boot command is then dsh --profile acp.

Option A — remote (from this GitHub repository)

# HTTPS (public repository; use a credentialed URL for a private one)
dsh plugin --profile acp add https://github.com/dangpangch/dsh-acp.git

The repository ships its prebuilt bundle (lib/), so the install is a plain fetch — no build scripts, no extra allowlist. Repeat add (or remove + add) after pulling new commits to upgrade the installed copy.

Option B — local (development / offline)

dsh plugin --profile acp add /path/to/dsh-acp

This installs a pnpm link to the local checkout. After changing the source code, rebuild and the running profile picks it up on next boot:

pnpm build   # tsdown -> lib/

After installing: check the bundle list

dsh plugin --profile acp add seeds a fresh profile with the CLI's template, which also bundles the official automation-only @deepseek-ai/dsh-acp-app. In that composition the official bridge answers the client (agentInfo.name = deepseek-harness-acp, no session/close, no live deltas) and this plugin never gets the connection.

Remove it from the profile's own package.json so the bundle list is exactly base + this plugin, then restart the profile:

// ~/.dsh/profiles/acp/package.json
"dsh": {
  "profile": {
    "bundles": ["@deepseek-ai/dsh-base", "dsh-acp-v1"]
  }
}

Verify the running bridge with dsh --profile acp + initialize: agentInfo.name must be dsh-acp-v1.

Configure Zed

Add a Custom Agent to Zed's settings.json (~/.config/zed/settings.json on Linux; Cmd+, → "Open Zed Settings" from the agent panel otherwise):

{
  "agent_servers": {
    "DeepSeek Harness (acp)": {
      "type": "custom",
      "command": "dsh",
      "args": ["--profile", "acp"]
    }
  }
}

Notes:

  • command: "dsh" assumes dsh is on PATH (npm global install). If a GUI-launched Zed cannot find it, start Zed from a terminal that has dsh on PATH, or set command to the absolute path of the dsh binary.
  • Then start a new thread from the Agent Panel and pick DeepSeek Harness (acp). The thread toolbar offers Preset (while the session is still blank), plus the Model / Thought Level / Write permission selects.
  • DEEPSEEK_API_KEY is optional in agent_servers[].env — without it dsh uses the credentials already stored by dsh Web.

Smoke test (no model key needed)

stdout must contain only JSON-RPC; EOF must exit 0:

printf '%s\n%s\n' \
  '{"jsonrpc":"2.0","id":1,"method":"initialize","params":{"protocolVersion":1,"clientCapabilities":{}}}' \
  '{"jsonrpc":"2.0","id":2,"method":"session/new","params":{"cwd":"/tmp","mcpServers":[]}}' |
  dsh --profile acp

Expect two result frames (initialize → protocolVersion 1, session/new → sessionId), then exit 0.

Capabilities (declared only when implemented)

  • Sessions: session/new · list · load · resume · close · delete with durable history (session-query/persistence); load replays committed content per ACP semantics.
  • Streaming/rendering: agent_message_chunk, streamed reasoning, tool cards (execute cards carry the concrete command line in their title), plan/todo updates, usage_update, available_commands_update slash catalog = dsh command plane + user-invocable skills (~/.agents/skills, <project>/.agents/skills, .dsh/skills). Skills follow the pi-acp naming convention: announced as skill:<name> (/skill:find-skills in the / popup), commands keep plain names; picking one loads the skill body through dsh's tool-skill pre-step.
  • Command output display (Zed 1.18): Zed renders execute-kind cards as terminal-style cards whose text content hides behind a hover-only chevron (an external agent cannot force them open), so every bash/pwsh result is delivered as a read-style card: the title carries the model-written command description (the raw command line stays in rawInput) and the captured output rides as fenced text content in the tool_call_update, folding with the card. Commands run under dsh's own sandbox/approval; nothing is ever executed inside the client.
  • Session options: Preset (while the session is still blank), Model, Thought Level, Write permission.
  • Permissions: one-shot session/request_permission (allow-once / reject-once). A pending escalation is announced in the conversation stream before the request, so the wait is visible even when you are not looking at that session.
  • Auth: authenticate via DEEPSEEK_API_KEY or dsh Web credentials; AUTH_REQUIRED with a sign-in method when missing.
  • Elicitation: ask_user_question → ACP form (when the client declares elicitation.form).

Honestly not implemented (never advertised): session fork, delegated terminal/fs execution (commands run only in the dsh sandbox — the client renders captured output as card content, it never executes the agent's command), additionalDirectories, audio/embeddedContext, MCP mounting (non-empty mcpServers is accepted and ignored — no MCP tools are mounted, noted on stderr), fine-grained diff cards, Windows.

Presets & model route (deployment fields)

The agent preset and the default model route are deployment fields, read from the environment once at boot (changing them means restarting the agent):

  • DSH_ACP_PRESET — the preset every ACP session is composed from (default standard; the roster this bundle ships: standard, ptc, minimal, cordis). A value no installed preset supplies fails session/new with a readable error listing the available presets. This bundle ships the host rows the non-standard presets need (cordis-host-runner + cordis-inspect-providers for creator mode; the terminal / tool-presentation packages are devDependencies), so a base-only profile — and the standalone dev boot — mounts all four.
  • DSH_ACP_PROVIDER / DSH_ACP_MODEL — the shipped default route (deepseek-official / deepseek-v4-flash); the per-session Model config option still overrides.

Presets are a deployment default and a blank-session session option. A new thread advertises a Preset selector: while the session has produced no turn, picking another preset recomposes the agent — tool set, prompt sections, skills — the same switch dsh Web performs. dsh fixes the composition at the first turn (agent-preset/locked), so the bridge drops the selector at turn/start: after that the preset is a property of the session and only a new thread can change it. A reloaded session re-mounts the preset its log last selected, not the one DSH_ACP_PRESET names now.

On dsh 0.2.0 the preset roster is declarative: the registry scans no directories, so this bundle ships the four compositions as presets/<id>.patch.yml (@deepseek-ai/dsh-agent-preset rows, listed in package.json dsh.bundle.patch) and disables dsh-base's agent-plane rows so each session's preset owns its tool surface. Add a preset the same way a deployment does: insert a @deepseek-ai/dsh-agent-preset row from your profile's own cordis.patch.yml. A preset whose composition cannot mount is not offered (and a direct pick fails with a readable error).

Develop

pnpm install
pnpm typecheck   # tsc --noEmit
pnpm build       # tsdown -> lib/
pnpm test        # vitest (175 tests incl. spawned frame-purity + history probes)
node scripts/conformance.mjs     # ACP v1 wire conformance + mount audit
node scripts/preset-smoke.mjs    # deployment env fields (preset/provider/model)
node scripts/history-probe.mjs   # session history end-to-end (isolated DSH_HOME)

The dev/probe boot composes @deepseek-ai/dsh-base + every dsh.bundle.patch layer of this package (cordis.patch.yml then presets/*.patch.yml). Set DSH_ACP_DEV_PATCH=<patch.yml> to append one more layer — the way the probes author a preset, since the 0.2.0 registry scans no directories.

Layout: src/bridge/index.ts (plugin entry), catalog.ts (slash catalog), replay.ts (history → ACP frames), tool-cards.ts (card titles/kinds), {codec,updates,content,config-options,session-store}.ts (wire builders / decision tables), src/dev-bin.ts (isolated dev/test boot), cordis.patch.yml + presets/*.patch.yml (bundle patch).

Docs & license

  • Technical design document (Chinese): docs/design.zh.md
  • English design summary: docs/design-summary.en.md
  • MIT