Plugins

Desktop pet for the DSH Web UI with 25 transparent animations, screen wandering, click reactions and drag, plus a reproducible asset-generation pipeline.

White-box AGI architecture exploration: metacognition (self-cognition loop), continual learning (knowledge flywheel), world model (condition space, spatiotemporal memory graph), self-improvement (bootstrap discipline), zero-LLM white-box pipeline, and auditable trust guardrails.

Multi-device remote access for DeepSeek Harness: continue an active session from your phone, tablet, browser, or another computer over an end-to-end encrypted channel (Noise IK + adaptive relay/WebRTC transport), with device authorization, ApiProxy-only remote capabilities, and read-only file preview via dsh-file-viewer — no shell, remote desktop, or write access.

Multi-device remote access for DeepSeek Harness: continue an active session from your phone, tablet, browser, or another computer over an end-to-end encrypted channel (Noise IK + adaptive relay/WebRTC transport), with device authorization, ApiProxy-only remote capabilities, and read-only file preview via dsh-file-viewer — no shell, remote desktop, or write access.

Causal memory for dsh: a zero-dependency MCP stdio bridge that mounts the 17 tools of the causal-memory server under clean names (no mcp__ prefix) — decision → outcome edges with typed relations (caused / enabled / prevented) in a local SQLite store that survives compaction — plus a pinned system-prompt section. Requires the causal-memory server binary on PATH (pip install causal-memory, or a prebuilt release).

Ports all 38 opencode themes (33 TUI + 4 desktop 2.0 + system) into DeepSeek Harness: data-driven pipeline (JSON → color resolve → DSH override), per-browser persistence, monospace/proportional choice, five code fonts, and a system fallback that keeps typography only.

Data quality checking for DeepSeek Harness — profiling, cleaning, and verification pipelines with structured reports.

Quantitative R&D toolkit for DeepSeek Harness — 59 tools across six domains covering market data, indicators, factor evaluation, walk-forward ML validation, risk (VaR/CVaR/drawdown/Beta with Kupiec POF), options, bonds, FICC and fund simulation, with an end-to-end PDAT→PET research pipeline.

QA pipeline as 10 agent skills: requirement analysis, test strategy, case writing and review, E2E (Playwright) and API automation, exploratory, regression scope and bug analysis, backed by a shared knowledge base with format rules, risk model and schema validators.

lowtide: human-adjudicated off-peak batch task pipeline for dsh (peak/valley pricing aware)

Thinking-language control for DeepSeek Harness: two presets — Default English, which only makes replies follow the language of the question, and Simplified Chinese, which also pins thinking to Chinese — injected as a system-prompt section rendered first via a minimal order plus an assemble-pipeline reorder guard against plugins joining earlier or with smaller orders, with an optional per-turn user-message prepend carrying an idempotency marker; switched from the Settings → General page and applies live on hosts with schemastery >= 3.18.3.

Installs four multi-agent math-research presets for DSH: v2 (probability-driven pipeline with multi-verifier debate), v3 (paper-style Markdown knowledge base with a planner agent and a reusable method library), v4 (persistent self-organizing residents that message and meet), and v5 (a research institute with an academician who decomposes and assigns work, voting researchers, temp workers, group chat and a compare-and-set task board); all four support checkpoint resume, human intervention, and an optional Lean formal-verification switch (off/encourage/require) whose passing proof turns the vote into a fidelity check of the Lean statements.

Deep reading & summarization for DSH: books/papers/videos/web into structured Obsidian notes via plugin parsers, MapReduce parallel deep-read subagents, JSON Schema outputs and an idempotent cache.

AI image and video generation for the DSH Web GUI: text-to-image and image-to-image over per-channel model catalogs with per-family request shaping (gpt-image, Grok Imagine, Nano Banana, Seedream, GLM-Image, Qwen-Image, MiniMax image-01, DALL-E 3), a sidebar generation studio, an infinite canvas with node workflows, files preview and canvas skills, and a prompt template library; the video side adds text-to-video, image-to-video, first/last-keyframe and multi-reference modes on an async submit/poll/download pipeline, host-side video tools, video nodes on the canvas, and clip stitching of two or more video nodes into one MP4 with the local ffmpeg.

Mobile web shell for the DSH Web GUI: overlay drawers, draggable FAB, mobile composer fixes, and a floating image-upload button pinned above the composer (native gallery/camera, integrated with the validated add-images pipeline), zero desktop regression. Published on npm as dsh-webui-mobile.

Token-cost pipeline for DeepSeek Harness: pressure-aware layered compaction (lossless projection below 40% context pressure, LLM summarization above), per-agent tool allowlisting, long-text-to-image with vision summarization, and a /token-status command tracking pressure, tiers, and saved tokens.

Ported from the ARS Claude Code plugin (44k+ stars on GitHub): academic research skills for DeepSeek Harness — a deep-research agent team, a paper-writing pipeline, a multi-perspective peer-review panel, and an end-to-end orchestrator, plus sixteen /ars-* commands.

DeepSeek Harness bundle registering one skill that turns long-form production (academic papers, industry analysis, business commentary) into a 9-role pipeline: T1 literature / T2 data / T3 case scouts running in parallel, T4 analyst, T5 writer, T6 critical companion, T7 auditor, T8 finalizer run by the coordinator, T9 peer reviewer — across 6 phases with triangular evidence verification, a 23-check M-gate, a G0-G14 audit including a Chinese AI-trace gate, peer-review scoring with journal matching, and 4 human checkpoints. Installs with `dsh plugin add lunheng-article-pipeline` (package.json#dsh.bundle.patch plus a lib/index.js entry that registers the skill); ships role cards for T1-T9, templates and 11 zero-dependency verification scripts, with five-language READMEs.

Multi-platform research and deep search pipeline: harvest_scout for parallel discovery across GitHub, Web, Twitter, Reddit, Xiaohongshu, Bilibili, and YouTube, harvest_deep_research for automated comprehensive research reports, plus extract, cross-source verification, and credibility auditing.

Expert-mode agent preset for DeepSeek Harness (v0.9.2, npm dsh-expert-mode, bilingual EN/ZH): a chief coordinator plus 17 domain-expert subagents with automatic task delegation. Features: taskboard scheduler (file-system task state machine pending/ready/running/done/failed, dependency DAG, atomic claim, retry, crash recovery), quality gates (5-stage pipeline for high-risk tasks: requirement clarity, implementation, verification, independent review, integration, with 2-round rework limit), Five-Anchor constraint (review/convergence/anti-drift/collaboration-check/resource-awareness per turn), Near-distance Guidance (identity/task/output template per expert), progressive disclosure (~28% token savings), expert persistence, inter-expert file message bus (direct P2P comm, zero coordinator relay), cross review, experience pool, fast-track for simple tasks, fault recovery with auto-retry. Experts: data analyst, copywriter, legal review, product manager, frontend, UI/UX, architect, social media ops, growth hacker, quant finance, finance, backend, DevOps, database, QA, security.

Role-based multi-agent team for DeepSeek Harness — your digital workforce. One goal assembles a team of product, architect, frontend, backend, reviewer and QA roles that deliver through a nine-phase gated pipeline, plus a persistent team you can keep directing across sessions. Zero runtime dependencies, no build step.

Turn a one-line requirement into verified delivery. TeamFlow runs a multi-stage pipeline — triage, PRD, design, technical plan, parallel development, QA with defect rework, acceptance — and gives the model 12 `teamflow_*` tools plus a workbench with a live pipeline graph and a backlog kanban. Each requirement gets its own folder holding the PRD, design, technical plan, QA report and acceptance record.

"Single-Core Writing" plugin for DeepSeek Harness: Thoroughly tool-streamlined and output-hardened for quantized small models, suitable for running long-novel pipelines locally with on-device models.