Create, manage, and automatically receive AgentRQ tasks without leaving the harness. The bundle ships two rows: the workspace's tools bridged to the model, and the harness-side behavior a tool bridge cannot provide on its own — a supervised workspace session that delivers AgentRQ's pushes into the live agent, and the AgentRQ working agreement as a system-prompt section.
Install
One profile per workspace. A profile serves one AgentRQ workspace and carries its own endpoint, so name it after the workspace rather than using default — that is what makes several workspaces work. Your workspace's Settings → Setup → DeepSeek Harness page prints every command and config block below already filled in.
Then pin this workspace's endpoint in the profile's own patch layer, ~/.dsh/profiles/agentrq-/cordis.patch.yml. Copy the URL from the Settings page — it already carries the ?token= credential that authenticates a headless client:
One row, one URL: the plugin mounts @deepseek-ai/dsh-mcp-client itself as a child fiber, so the endpoint is configured in exactly one place and the bridge shares this row's lifetime — disposal and HMR take it along.
dsh --profile agentrq- --dump-config # shows the bundle layer and your override
dsh --profile agentrq-
The profile's patch is applied after every bundle layer, so those two rows win. dsh watches both cordis.patch.yml layers and reapplies valid edits transactionally, so changing the URL takes effect without a restart.
Configuring without a file edit
The bundle's own patch defaults both rows to !!js process.env.AGENTRQ_WORKSPACE_MCP_URL, so a container or CI job can export the endpoint instead of writing a profile patch:
Prefer the profile patch for an interactive install: an environment variable is process-global, so with one profile per workspace you have to remember the right export before each start, and the wrong one connects the wrong workspace without complaint. Supply neither and the row fails to load with the url field named — it is a required field, not a silent default.
Installing from a git checkout instead of the registry fetches sources rather than built artifacts, so pnpm must be allowed to run this package's prepare build. Add the allowance to your profile's pnpm-workspace.yaml and re-run the add:
allowBuilds:
'@agentrq/dsh-plugin-agentrq': true
That allowance is permission to execute this package's code on your machine at install time. Pin a commit (github:agentrq/agentrq#) if you take that route. Publishing to npm or shipping a pnpm pack tarball avoids the allowance entirely.
What the model gets
Seven AgentRQ tools, bridged by @deepseek-ai/dsh-mcp-client under the agentrq namespace:
Tool
Purpose
mcp__agentrq__getTask
Fetch a task, or dequeue the next one assigned to this agent
mcp__agentrq__createTask
Assign work to the human or to another agent
mcp__agentrq__updateTaskStatus
Move a task to ongoing, completed, blocked, …
mcp__agentrq__reply
Send a message into a task thread — the only thing the remote human sees
mcp__agentrq__getWorkspace
Read the workspace title and mission
mcp__agentrq__downloadAttachment
Fetch an attachment's content
mcp__agentrq__publishEvent
Fire a named event so subscriber workspaces spawn their trigger tasks
Plus one tool this package owns:
Tool
Purpose
agentrq_autopull
status, pause, resume, or pull_now for this session's AgentRQ delivery
pull_now returns the dequeued task as its own tool result rather than queuing a turn, because a tool body runs mid-turn by definition.
How work arrives
The plugin does not poll. AgentRQ already decides when there is work and pushes it over notifications/claude/channel:
creating a task assigned to the agent pushes it immediately (backend/internal/handler/api/task.go), provided nothing else is ongoing;
WorkspaceServer.StartPoller re-pushes the next unclaimed task — or a status check for the ongoing one — every 60 seconds.
The plugin's own workspace session subscribes to that channel, exactly as acp-gateway does for Gemini and other ACP agents. Polling the queue from the client would duplicate the server's own ticker and deliver every task twice.
Each push is forwarded as written. A new task, the periodic reminder, a status check, and a human's reply all arrive on the same channel; the plugin adds a framing line naming the chat_id and the tools to answer with, then hands over the content. It does not try to classify what kind of push it is, because that would only add a way to be wrong. The content is JSON-escaped into the framing, so pushed content cannot forge a framing field.
Delivery route depends on the agent's state: inject() while a turn is running, so it lands at the next step boundary, and followup() while idle, since nothing else would wake it. Neither interrupts a turn in flight.
SendChannelNotification puts the task id in meta.chat_id on every push, so the id never has to be recovered from the content.
Repeats are dropped. The workspace re-pushes an unclaimed task verbatim every minute; the runtime remembers recent (task, content) pairs, so the agent is handed it once and not woken every sixty seconds for work it already has. A genuinely new message on the same task still gets through.
Staying connected is the load-bearing part. No session, no pushes — so a closed transport or an unrecoverable transport error triggers a reconnect with exponential backoff (reconnect.initialDelayMs doubling to reconnect.maxDelayMs), on top of the SDK's own SSE resumption. Because the server re-pushes on its own schedule, a recovered session catches up on the next tick without any client-side replay.
catchUpOnStart dequeues one task when the session opens, so work that predates the connection does not wait for the server's next tick. A failed startup check costs latency, not work.
agentrq_autopull pause stops pushes from reaching the session; the session itself stays open.
One AgentRQ queue serves one worker, the harness Web UI creates a root agent per chat session, and pushes are broadcast to every connected session. Under the default scope: single-agent, exactly one live root agent holds the workspace session, so a second chat session does not get every task delivered a second time; a later session inherits the connection only after the owning agent is gone. Set every-agent when your agents work disjoint queues or you want deliberate fan-out.
Multiple workspaces
AgentRQ users normally have several workspaces, each with its own queue, mission, and agent identity. Run one profile per workspace.
Install once per profile, and let each profile's cordis.patch.yml carry its own endpoint:
Because the endpoint lives in the profile rather than the environment, switching workspaces is switching profiles — nothing to re-export, and no way to start one workspace's profile pointed at another's queue.
Each profile gets its own process, sessions, working directory, and workspace connection, which matches how AgentRQ already models a workspace: one workspace, one agent, one mission. It also matches the usual case where workspaces track different repositories.
Two consequences worth knowing:
A single profile cannot serve two workspaces. Mounting the bundle twice in one profile registers the agentrq:protocol prompt section and the agentrq_autopull tool twice in the same layer, and both registrations throw on a duplicate name. Namespacing them per instance is deferred until someone needs it.
No cross-workspace view. AgentRQ's CoreMCP supervisor (https://mcp.agentrq.com/mcp) does expose listWorkspaces and listAllTasks, so a deployment that wants "what is outstanding everywhere" can mount it as an extra @deepseek-ai/dsh-mcp-client row. It sends no channel notifications, so it complements per-workspace delivery rather than replacing it.
serverName is safe to change: the guidance section and every framing derive their tool names from it, so the namespace the model sees and the namespace the prose describes cannot drift apart.
Config
Key
Default
Meaning
url
— (required)
Workspace MCP endpoint, including its ?token= credential
token
''
Bearer token, for deployments that prefer an Authorization header over ?token=
mountBridge
true
Mount the @deepseek-ai/dsh-mcp-client child that gives the model AgentRQ's tools
serverName
agentrq
Namespace for the bridged tools; the guidance section and framings follow it
deliverPushes
true
Deliver the workspace's tasks and messages into the live session
catchUpOnStart
true
Dequeue one task when the session opens
scope
single-agent
Whether one root agent or every root agent holds a workspace session
reconnect.initialDelayMs
1000
Delay before the first reconnect attempt
reconnect.maxDelayMs
900000
Ceiling for the reconnect backoff
guidance
true
Contribute the AgentRQ working-agreement system-prompt section
requestTimeoutMs
30000
Timeout for one AgentRQ tool call
Set any of these in the same profile patch. A patch replaces a row's whole config rather than merging into it, but every key except url has a schema default, so a row only restates what it changes:
AgentRQ's MCP server ships its collaboration rules as server Instructions, and the harness does not surface an MCP server's instructions to the model. Without them the model has the tools but not the contract — that the human is remote, sees only what reply sends, and needs the task claimed before work starts. This package contributes those rules as the agentrq:protocol section in the tool-guidance band (order 150), so behavior in dsh matches behavior in the Claude Code and Gemini extensions. Turn it off with guidance: false when a deployment states the same protocol in its own persona.
Development
npm install --legacy-peer-deps # harness packages declare peers pnpm resolves from the profile
npm run typecheck
npm test
npm run build
make plugin-deepseek from the repository root runs all four.
Releasing
.github/workflows/plugin-deepseek-harness.yml typechecks, tests, and builds this package on every pull request that touches plugins/deepseek-harness/**, and publishes it to npm when such a change lands on main.
Bumping version in package.json is what releases. npm refuses to republish an existing version, so the workflow checks first and skips the publish when the current version is already on the registry — an ordinary fix that touches this path does not need a version bump to merge.
Authentication is npm trusted publishing: the package names agentrq/agentrq and this workflow file as its trusted publisher, the job requests an OIDC token with id-token: write, and npm exchanges it for a short-lived publish credential. There is no NPM_TOKEN secret to store, rotate, or leak, and npm attaches build provenance automatically.
Two things that break it, both non-obvious:
Renaming the workflow file. The trusted-publisher record names plugin-deepseek-harness.yml exactly; a rename must be made on npm's side too or every publish is rejected.
npm older than 11.5.1.setup-node with Node 22 installs npm 10.x, which has no OIDC support and silently falls back to looking for a token. The workflow upgrades npm explicitly for this reason — do not remove that step.
Known limitations and deferred work
One workspace per profile — each row carries one url, and mounting the bundle twice in one profile collides on the prompt-section and tool names. Several workspaces means several profiles.
The endpoint is configured, not discovered — there is no in-harness command to switch workspaces; the profile's cordis.patch.yml (watched, so no restart needed) or AGENTRQ_WORKSPACE_MCP_URL is the switch. A ctx.settings namespace would give a schema-driven editor with role('secret') redaction for the token, but its document is $DSH_HOME-global by default and so does not carry per-profile values without extra plumbing.
The bridge is mounted, not injectable — the plugin mounts one @deepseek-ai/dsh-mcp-client child with the settings it derives from its own config. A deployment that needs the bridge's other knobs sets mountBridge: false and mounts its own row, and is then responsible for keeping serverName aligned.
Load-order boundary — the plugin attaches only to root agents published after it loads; an agent that was already live when the plugin loaded gets no workspace session and no agentrq_autopull tool.
Ownership does not migrate to a live agent — under single-agent, when the owning agent is disposed the connection stops until the next root agent is created; an already-open second session does not adopt it.
Session-lifetime repeat memory — the delivered-set is process-local and bounded, so a restarted harness may be handed a task it saw before if that task is still unclaimed. Claiming a task with updateTaskStatus is what stops the workspace re-pushing it.
Auth is the URL's credential — the plugin does not run the AgentRQ OAuth authorization-code flow; it uses the long-lived token from Workspace Settings, as a bearer header or a ?token= query parameter.
Attachments travel through the model — the plugin's own session only receives pushes and dequeues on request; downloadAttachment remains a model-facing tool call on the bridged server.
Permission verdicts are not bridged — acp-gateway also consumes notifications/claude/channel/permission to answer AgentRQ's allow/deny prompts. The harness has its own tools/pre-execute approval axis, and wiring the two together is deferred.
License
Apache-2.0, matching the rest of the AgentRQ repository.