Plugins

Turns what a design, plan or document claims into a model and decides it: UML diagrams rendered, read and reviewed; state machines, protocols and data models checked as models; migrations tested for coverage and rollback symmetry; concurrency claims mined and routed to the checker that can decide them; dependency graphs audited; reports diffed.

Command resolution forensics: which file a command actually runs, which PATH entry won, what it shadows, how many entries are duplicates or dead, and whether the copies behind one name report the same version.

Reports DeepSeek Harness session state (working, done, error) to the agent-pet macOS desktop overlay and lets it open sessions or start a chat.

Redundant branch cleaner: finds branches whose work already landed in the mainline — merged, squash-merged, patch-equivalent after rebase or cherry-pick, upstream-gone, or PR-merged — and deletes them when asked. It only reports by default, never switches branches or rebases, and backs every deleted local branch up under refs/backup/branch-cleaner/ (deleting remote branches has no backup).

Bidirectional dispatch for DSH: opens visible desktop sessions for tasks dispatched in by Grok Bot / Yobiru, adds /dispatch-grok and /dispatch-zcode slash commands to send tasks out, and reports the session result back to the dispatching peer on completion (peers are user-configured; nothing is sent until configured).

Test work framework for DSH that scaffolds a product, module and version directory tree, registers seven test_framework_* tools and four runtime skills, and adds a prompt-level gate that reports which requirement-document splits, versions, related documents and environment credentials are still unrecorded before testing starts. Requires the playwright MCP server (no fallback).

Shows what each installed skill costs in the model context and hides a skill from the catalog without deleting it. Lists every skill found on disk with the exact catalog line the model receives (description normalized and truncated at the catalog cap), its body size and token estimate; previews the catalog message byte-for-byte as the agent will receive it, compares that with the copy already published in the current session, and reports skills on disk that never reach the catalog (invalid frontmatter, or shadowed by a higher-priority root). Hiding writes disable-model-invocation into frontmatter and keeps the file, so the skill still works via /name. Also imports skills from ClawHub, Skills.sh and GitHub URLs and uninstalls user-owned ones.

Publish size check skill: verifies a deliverable's geometric specs against a target platform before publishing - pixel dimensions, aspect ratio, dpi, file size, format, physical print width and colour mode. Geometry only: it does not review content compliance (QR codes, text-to-image ratio, copyright and prohibited content are out of scope). Pure Python standard library, no third-party packages, and inputs are never modified. Python 3.8+. Covers 10 platforms and 20 slots with per-platform confidence labels - WeChat MP, Xiaohongshu, Bilibili, Zhihu, Weibo, Douyin, WeChat Channels, journal submission, print and client delivery - and resolves a platform by id, Chinese name or alias with fuzzy matching. Two trigger modes: asked directly, or as a parasitic self-check that runs by itself once an image, poster, chart or export workflow has written a file and the user mentioned a publishing target, reporting in one line when everything passes and only expanding when something is wrong. For journal submission and print it judges by physical width (pixels / dpi), which catches files whose dpi metadata passes but whose actual printed size is too small; for multi-image posts it checks whether the whole set is consistent and names the odd one out rather than listing every file.

Evidence-first reuse skill for DeepSeek Harness: before implementing, porting, choosing dependencies, or troubleshooting a tool, it searches the local project and machine for existing solutions in layers, judges reuse on checkable evidence, refuses reuse when essential requirements or risks are unmet, and reports what could not be verified. Ships as a DSH bundle that registers the skill on ctx.skills.

Skill that reviews your coding-agent session transcripts (Claude Code and Codex only; DSH's own transcripts are not supported) over the last two weeks and reports which skills, hooks and rules work, need attention or go unused. Requires Python 3.

OCR for scanned, image-only PDFs into Markdown, built around the fact that a book takes about an hour: every page is checkpointed so an interrupted run resumes, a progress log reports live status, and a quality report names empty pages and low-confidence lines. Requires Python 3.10+ and pip install -r requirements; the first run downloads the OCR model.

Extract Bilibili platform/AI subtitles or external/embedded/ASR/OCR fallback and render Markdown, Word, PDF, TXT, SRT or JSON with timestamps, bilingual alignment and a quality report. Requires Python 3.10+; platform/AI subtitles need a Bilibili SESSDATA cookie; OCR/ASR/PDF need ffmpeg, faster-whisper and LibreOffice or reportlab.

Previews a workspace OpenWiki in the DSH Web right Sidebar: detects the wiki directory, serves it with the official `openwiki visualize` reader on a loopback port, and embeds it in its own tab, reporting the installed openwiki and DSH versions against configurable floors and checking the registry for its own updates.

Local offline prosody analysis for DeepSeek Harness: reports how something was said — speed, pitch, pauses, energy — alongside the transcript.

Registers two tools for DeepSeek Harness. `doc_ocr` turns scanned PDFs and images into structured text (per-page text, financial tables with a balance-sheet tie-out check, contract-clause hits) through a local RapidOCR engine or a Zhipu GLM-OCR cloud engine, and `doc_preprocess` turns a directory of raw files into an Obsidian-ready knowledge base through a seven-stage pipeline with backend routing and sha256-based incremental skipping. Numbers that fail the tie-out are reported, not invented. The local engine needs Python 3 with rapidocr-onnxruntime, pypdfium2 and Pillow (pip install -r requirements.txt); the GLM engine needs ZHIPU_API_KEY.

Lets the model actually see a video: local ffmpeg samples timestamped stills and faster-whisper transcribes the audio track, so the agent reads real pixels frame by frame instead of trusting a text summary. Fully local, nothing uploaded; reports honestly when the audio has no speech. Windows only; needs Python 3.10+ and ffmpeg installed, and the first video_eyes_setup run downloads about 700 MB (faster-whisper and its model).

Registers one `context_extract` tool for DeepSeek Harness: it compresses a long raw document (financial report, contract, ledger) into dense structured Markdown plus JSON — key metrics, tables, numbered clauses, entities and cross-check alerts — so a downstream pipeline can work from the compressed form instead of re-reading the raw document. Financial statements, legal contracts and business ledgers are detected and handled differently; balance-sheet and cash tie-outs are run and mismatches are flagged as alerts rather than silently fixed. Read-only; never modifies the source file. Requires Python with openpyxl and python-docx.

Deliverables registry for DeepSeek Harness: agents register the final artifacts of a task (reports, pages, documents, sheets, images, datasets) into one settings section and manager page that store paths only, never copies, and remove recoverably; a standalone CLI (add, list, stats, check, remove, restore) reads and audits the same registry outside the app.

Requires JDK 11+, the DM JDBC driver and SSH access to the target instance. Inspect Dameng database instances, assess security and recovery conditions, and generate filterable reports with shared evidence.

Requires Claude Code installed and signed in on this machine. Delegates coding tasks to the local Claude Code agent through the Claude Agent SDK, reports which files changed, supports one-command revert, and adds a Claude Mode toggle to the composer.

Gowin (高云) 1.9 FPGA toolchain control for dsh: 15 tools covering environment and license probe, .gprj/.cst project and constraint auditing against a real GW1N board pinout, gw_sh batch synthesis and place-and-route, pnr resource and timing report parsing, programmer_cli JTAG scan and flash, arbitrary gw_sh Tcl, and the GAO on-line logic analyzer capture chain — plus a bundled gowin-fpga skill and three field-note references. Pure JS, zero runtime dependencies.

AI research toolkit for DSH: a model release radar, a per-model benchmark and community report from 13 structured leaderboards plus Chinese and English community discussion, and an AI news radar over 46 feeds and 22 official X accounts; registers four tools and three skills and renders every report to Markdown with a generated table of contents.

Windows-only game crash diagnosis from Event Log, WER reports and crash dumps, with a diagnose_game_crash tool and an optional background notifier.

Reads the installed plugins, MCP servers and skills, groups them by capability, and reports which preset each belongs in; can register one preset per category on request.