Plugins

Follow list above the sidebar conversation list: a status dot per conversation (unread, waiting for you, running, failed), newest reply first, running ones last, and a follow toggle beside the model selector. Marking a row unread lifts it to the top, opening one expands and scrolls to its row in the Workspace list below, a finished turn always counts as unread until the conversation is opened, and a conversation whose delegated subagents are still working keeps counting as running until the last child reports back.

Multi-agent agent team of employee AI subagents for DeepSeek Harness — dsh-company: employee management, CEO bidding, n8n workflow orchestration, drag and drop canvas. DeepSeek Harness plugin with seven built-in roles (project director, product manager, tech lead, engineer, data analyst, QA, reviewer), each with its own persona, model and tool whitelist. Broadcast a mission and the employees bid for it themselves — the first line of their answer must be 【accept】 or 【decline】 — so accepted work runs in parallel instead of down a pipeline. The workflow canvas wires employee nodes with the start node, references each upstream result with {{input}}, and runs the graph in topological layers: parallel across employees, serial per employee, downstream skipped when upstream fails. Ships a web panel for the employee management tab, the mission board and each employee's transcript, the /dsh-company slash command, a live mirror into the built-in agent-team panel, deletable missions, and a private memory directory per employee.

Picks each subagent model from the local catalog by task category, unless the caller already named one. Free and quota tiers are ranked together by per-model capability tags; a pricier model is used only when no cheap model is tagged as good at that kind of work. Only providers whose remaining balance is readable, or that are account-backed, enter the candidate pool; the rest stay listed but are not routed. A panel adds per-model manual priority above the automatic order plus allow/revoke controls.

Layered system-prompt profiles — global, per-workspace and per-session entries injected in order — where individual builtin sections and runtime contexts can be disabled or overridden, with a line-level diff of what an override changed; each entry carries a subagent scope that targets the main agent only, subagents only, or both; assembly snapshots record what each turn actually received, subagents included. Managed from a Web panel and a `prompt_manager` tool.

Registers a wrapper provider that gives delegated subagents their own LLM route — one-off spawns through provider.start, Agent Teams members through a hook on startActivation — while the main agent keeps its model. Ships a Settings section for picking that route, a per-expert override file, a capability flag reporting which seams the hook caught, and a readiness record written at mount.

Superpowers skills for the DeepSeek Harness (dsh): a full engineering methodology served through dsh's own filesystem skill provider, with an always-on bootstrap.

Set the provider, model and reasoning effort delegated subagents run with, from one chip beside the composer: a per-conversation override and a profile-wide default share the same two controls, and the chip always shows the effective route. Applied when each in-process child is created (agent/created + agent.model.select()); no settings page, no preset edits, no model-facing tool parameters.

Stop or permanently delete DeepSeek Harness sessions from the sidebar session menu: cancels running turns, subagents, background jobs and reminders, then removes the log, subagent session logs, projection cache and workspace record, with an optional clean

DeepSeek-led background orchestration of Codex and DSH subagents, with existing conversation handoff, Markdown history, quota pauses, and bounded decision retries.

Token usage dashboard and per-session tree statistics: provides time-range filtering, 6 summary metric cards, GitHub-style activity heatmap, model stacked-bar charts with cache hit rate curves, and Top-5 model/provider rankings; enhances the native session status bar to display aggregated token usage across main agents and all subagents with detailed breakdowns.

Agent preset: one session runs a three-phase auto-development pipeline — interactive design with parallel research subagents, goal-driven development with reviewer/developer subagents and per-package budget ledgers, then an acceptance fix loop.

Memory-assembly team for DeepSeek Harness: every message triggers a five-step cognition loop (judge, retrieve, assemble, feedback, calibrate) carried by role-playing subagents (judge, retriever, archivist, advocate, editor, scribe), using BM25 retrieval, time-ordered material, and LLM assembly to build useful material packs injected into linghun. Works with dsh-linghun.

Closes ai-memory's consolidation loop for DSH: when a DSH session ends it calls ai-memory finalize-session, so the observations DSH captured become wiki pages the other harnesses ai-memory serves can read. Skips subagents, queues concurrent session ends, and sweeps sessions abandoned by a forced restart.

Task monitor plus remote chat for DeepSeek Harness. Read sessions, background jobs, subagents, goal rounds, workflows and pending approvals from a phone-friendly page, and talk to any session from it: streamed replies, tool-call progress, stop at any time, switch sessions and models. Also ships a GUI sidebar panel.

Team cost captain: meters every model call (subagents included), attributes each call to a member by workspace rules, prices it with the built-in DeepSeek 2026-09 catalog (peak/off-peak, CNY/USD) or user overrides, and appends it to a local JSONL ledger. Adds hot-reloadable member budgets, 80%/100% webhook alerts, optional over-budget enforcement, a team_cost_report tool with CSV export, and a settings-page team dashboard served over a Typert RPC service.

Answers hard questions by staging a formal debate: two adversarial subagents argue opposite sides with research, then the main agent rules on the transcript through the debate_open, debate_round, and debate_verdict tools.

Adds a Graph tab that renders one session's execution as an interactive DAG of turns, LLM steps, tools, skills, subagents, code changes and tests, with live status, retry aggregation, critical path and trajectory linkage.

Registers a /code-review slash command with five parallel review lenses and per-finding confidence scoring, for both pull requests and local code.

Configure default model routes for DeepSeek Harness subagents, with single-model, round-robin, random, and per-route reasoning-effort options.

Reusable subagent definitions managed from a Settings page and dispatched through a single delegate_agent tool; ships with a built-in read-only Explorer preset and a nested-delegation policy toggle.

Minimal prompt x Web PTC capabilities: one-line persona, run_code SDK, subagents, Ralph, web search/fetch, and Windows Git Bash; the general-purpose workflow tool stays hidden.

Extends dsh-subagent-tools with a per-call cwd for subagents, shipped with the two in-process provider patches it requires.

Cross-session task queue with handoff notes: sessions and subagents push, claim, complete and cancel tasks on a shared file-backed queue, and leave a handoff summary for whoever picks up next.

QQ Bot channel and D&D 5e Dungeon Master plugin for DeepSeek Harness (fork of @tencent-connect/dsh-qqbot; do not enable alongside upstream): /dnd runs turn-based campaigns with 19 `dnd_*` tools for dice, checks, grid positioning, fog and battle maps, story chronicles, snapshot rollbacks and an optional dedicated combat subagent, plus /persona per-chat switching with handoffs, shared Markdown notes, sticker collection, read-only Bilibili tools and per-chat tool-access gating. Direct and group chats default to open in cordis.patch.yml while non-allowlisted QQ chats are blocked from shell and subagents; requires QQBOT_APPID/QQBOT_SECRET or in-app QR binding, with optional sharp for rendered maps and ffmpeg for audio/video. Shared notes are visible to every session, so private-chat content may be recalled in groups.