Plugins

Lingshu (灵枢) is a brain-inspired persistent memory, persona and growth system for AI coding agents: pure Python standard library, zero dependencies, local-first, requires Python 3.9+. Hippocampus/cortex layered memory with forgetting curves, dream consolidation, fuzzy associative recall, emotion system, persona drift protection, knowledge base, self-authored skills, and a local web panel. Ships as a DSH bundled skill; the separately installable cordis startup-injector plugin auto-injects sessions only when Lingshu is installed at ~/.dsh/skills/lingshu (or brainPy is configured) and Python 3 is available; the optional update check contacts GitHub/Gitee.

DSH plugin to read AutoCAD DWG/DXF, PDF and images without installing AutoCAD or Tesseract; DXF requires Python 3 and ezdxf on the machine.

Pipeline for scanned textbooks: OCR at roughly 5x the ONNXRuntime speed (requires Python 3.10+ with pymupdf, rapidocr, openvino and numpy), then a structure report and a per-chapter reading plan before you open the PDF.

A 股分红账本 DSH 插件 —— 薄 TypeScript 适配层，业务逻辑全部委托给 dividend_ledger Python 核心

Local development facts for Harness: environment and runtime-health probes, git status/diff/log/commit, write-time snapshots with version-by-version restore, and project checks for Node, Python and Go.

Bundled Pixiv skill backed by a Python CLI: search illustrations, manga and novels, browse daily/weekly/monthly/rookie/original/AI/R-18 rankings, look up works, novel series and artists, and download originals, with multi-page works merged into PDF, ugoira converted to GIF and novel series merged into TXT; requires Python 3.9+ with requests, img2pdf and Pillow installed (pip install -r requirements.txt), and R-18 content needs your own Pixiv cookie.

Bundles a deep-read paper library and the paper-deepread-html skill: a sidebar panel to browse interactive reading reports, upload PDFs into a managed library, deep-read them with an agent (or through an optional site auto-read worker), and manage or rebuild the library; ships the paper_deepread, paper_deepread_uploads and paper_deepread_reports model tools. Deep-read/ingest and report builds require Python 3 (the bundled skill prepares a PyMuPDF venv on first use; index rebuild falls back to plain python3).

Scientific figures as code: agents create a versioned figure IR, patch it incrementally (one node at a time — untouched objects never move), and export publication-ready, true-vector SVG / PDF / PPTX. Seven papercanvas_* tools (create, get, patch, layout, lint, render, inspect) over a deterministic engine with FC001-FC008 quality lint and CJK-aware font resolution. Verified on DSH 0.1.5-rc.3 through 0.2.2-alpha.2. By the author of dsh-sessionflow. Requires the PaperCanvas engine installed separately: Python 3.11+ and the papercanvas CLI (not yet on PyPI — install it from this repository, put it on PATH or set papercanvasBin); the plugin is a thin adapter and ships no engine.

Project-scoped SQLite memory with progressive retrieval, bounded context, a composer button and visual review. Install the repository-root DSH bundle, then run /learning-init with an absolute project path using local Python 3.10+.

Let a pet whale girl browse Bilibili on her own: she picks videos, reads subtitles, posts comments and moments once you allow it, and writes daily digests with optional local video production. Maintained fork of c1overzz/dsh-bili-scroll (MIT) with per-action permissions, memories, stickers and local video production added; it registers the same bili_* tool names as the upstream, so the two cannot be installed together. Video production needs Python 3.11-3.13 (or uv); the media dependencies are installed on first use.

Hands-free voice for DSH on Windows: local wake word, local Chinese speech-to-text inserted and sent into the composer, and spoken replies that can be interrupted and resumed. Requires a one-time run of the bundled install.ps1 (Python speech dependencies plus microphone pick) and a SenseVoice model already downloaded by the DSH voice input (or placed under models/sensevoice-onnx).

Long-term memory kept as plain Markdown plus git: each session opens with a generated memory-context block assembled from a global store and per-project books (role card, user profile, current focus, routing table, recent logs), the plugin records which memory files the agent read and reminds it to extract conclusions while the day's log is unextracted, personas live in roles/<role>/SOUL.md role cards, and it ships a seven-tab settings page in the sidebar plus four skills. Requires Python 3.10+.

Static-context audit for a DSH home: a six-layer baseline (rules, memory, skills, tool surface, sessions, KB), broken-path checks for a markdown capability map, memory duplicate/stale/over-limit reports, SKILL.md description compression, and tool-surface plus cold-start static-context estimates recovered from session logs. Four read-only DSH tools; writes require --apply and are backed up first. Requires Python 3.10+ on the host (stdlib only; all four tools shell out to the bundled CLI).

Read, message and live-follow local DeepSeek Harness sessions from inside an agent: four tools (session_list, session_read, session_send, session_chat) plus a matching Python CLI, over the desktop app local RPC; transcripts also read offline. Requires Python 3.10+; offline transcript reads also need the zstd CLI.

A transparent always-on-top desktop pet for DSH on Linux (X11 / XWayland), driven by the session state. The pet lives outside the browser as its own window, follows the pointer with a distance and per-display limit, shows a live session-status bubble that lists each session task and state, and auto-starts with your session. Linux only (X11/XWayland); needs Python 3 with PyGObject, GTK3, GdkPixbuf and xdotool. Its sprite sheets come from @michengai/dsh-codex-pet (MichengAI/dsh-codex-pet in this list).

DeepSeek Harness skill bundle for Hearts of Iron IV 1.19.3 modding: registers 15 skills and mounts 20 local MCP tools (a Python stdio server) to scaffold, statically verify, install and debug mods - focus trees, events, decisions, ideas, characters, technologies, MIO, special projects, scripted GUI and topbar buttons, localisation, DDS icons, 18-slot tank designer layouts, 3D tank models, CJK font auditing and error.log triage - plus a 23-workshop-mod technique survey and a multi-agent playbook. Requires DSH >=0.2.0 <0.3.0 and Python 3.9+ on PATH (standard library only, no third-party packages); no game assets are shipped.

Auditable mathematical proving for DeepSeek Harness: a local stdio MCP server with 23 machine-checking tools, a bundled workflow skill, and the /prove and /audit-proof commands. proven, refuted and inconclusive are never conflated, and unproven steps are reported instead of hidden. Needs Python 3.10+ with pip install -r requirements.txt on first run; the 23 tools are unavailable until then.

给小朋友的编程学习启蒙插件：一个包 = 一张 🐵「小教室·跑代码」卡片（真跑 Python/海龟画图）+ 五个模型工具（kid_run / kid_explain / kid_practice / kid_review / kid_steps），零第三方依赖、无构建步骤。

A 护航 panel in the session header that switches the local dsh-guard watchdog on or off and shows whether scanning is enabled, whether the guard is alive and when it last scanned; the Python watchdog that does the watching is deployed separately and found through the DSH_GUARD_ROOT environment variable. The watchdog defaults to a Windows checkout (D:\AI\Projects\dsh-guard); set DSH_GUARD_ROOT to point at another directory.

Study companion for your materials with guided practice, evidence-grounded feedback, Leitner spaced review, 18 teacher tools, and a Chinese/English student panel using the current DSH session model; requires DSH >=0.2.1-rc.2 <0.3.0-0, Python 3.11+, and Python runtime dependencies.

Bilibili autopilot run by a local Ollama model: it picks videos within per-topic quota, reads subtitles, hot comments and keyframes, decides whether a reply is warranted, then writes and posts one comment through a five-level safety gate. Triggered by dsh-schedule; write tools are not registered while commenting is disabled. v1.1 hardens the write path: revoking write access is a runtime state checked before every send, publishing is atomic, risk-control errors persist as a pause, and the final post re-checks persona style. Needs Python 3.10+ with the repo's requirements.txt installed.

Audits the skills and plugins you already installed: routes a task description to the tool it needs, flags version drift against the npm registry and runtime faults from host logs, and reports which of a plugin's tools you never call. Registers 9 tools: can, find, status, recommend, check, scan, probe, run and suggest. Runs on Python 3.8+ with no third-party dependencies. Registered tool ids all carry the skill_audit_ prefix, for example skill_audit_can and skill_audit_find.

Native Anki workspace backed by one real headless Anki collection: browse, edit, add and review notes, suspend cards, import and export APKG, and sync with AnkiWeb, with the same collection exposed to the anki AI tool. No Anki desktop app, AnkiConnect or Qt is started. Supports Windows x64 and macOS 12 or later (Apple Silicon and Intel). The matching headless Anki core, CPython and all Python runtime dependencies are bundled, so no separate Anki or Python installation is required.

Two DeepSeek Harness tools for the local tempguard watchdog: read temperatures and alertd health, and send alerts through alertd; it does not start or stop the watchdog. Needs the separate tempguard Python watchdog and its alertd service running locally, with projectDir and alertdToken set in the profile patch; there is no npm package, so install from a local clone of the repository subfolder.