Plugins

Daily AI digest by email: fetches ten sources (OpenAI, Anthropic, Google DeepMind, Hugging Face, arXiv, Hacker News and others), clusters near-duplicate stories, scores them in code and with an LLM, then emails the top three on a daily schedule with a four-part reading (facts, why it matters, impact, open questions). Adds four conversation tools and a sidebar panel for previewing the digest, sending it now and changing the schedule.

Quiet break, water, long-session and late-night reminders delivered by three bundled chibi companions, with cloud bubbles and a light bounce. Works in-page without extra downloads; the optional macOS desktop window uses a separately downloaded Electron helper.

Bidirectional GitHub repository sync for DSH: git sync with conflict rollback and pre-push checks, Actions/CI monitoring with per-step run detail, repository add/remove/rename, a web panel with local and remote file browsers, scheduled automation, and six agent tools.

Shows the repository, branch, working-tree change count and short commit SHA on the composer row, with a searchable branch switcher and a per-file diff pane in the right sidebar.

Branch panel for the composer: creates rule-checked branches from production6, validates commit messages against a type(scope) convention, and commits, pushes, or merges into stage in one click.

Generic monitor plugin for DSH Desktop: an HTTP polling rule engine. Poll any endpoint on schedule (multi-step, variable extraction, JS condition expressions); when conditions hit, wake a visible agent session to act — zero model calls otherwise. Configure everything in a sidebar GUI panel: create/edit/pause/test/fire-now/run history, same UX as the built-in scheduler plugin.

Keeps a repository's task ledger as a resident prompt section with eleven native tools, plus a sidebar panel and a floating window for browsing the queue and signing off review tasks.

A machine-checked reasoning ledger: every fact must resolve to a real file:line and be quoted verbatim from it, every assumption must state what would falsify it, and a conclusion may not rest on an assumption that never comes back for review. The ledger can carry a review date, a confidence and a kill condition. Ships the checker tool, an /fp command family, an optional gate that asks before irreversible shell commands, and a web panel listing the error codes each round fixed.

Read-only orchd panel for the DSH right sidebar: task board, ideas board, dependency graph, review timeline and an install entry for the project of the current session.

Investment research bundle: 10 tools (search, page fetch, source audit, claim verification, numeric rigor, channel health, workflow loader, chart engine, PDF renderer, PDF gate) and 23 skills adapted from ai-berkshire. Runs a six-phase workflow where four parallel agents (Duan Yongping, Buffett, Munger, Li Lu) research a company, cross-examine each other, and ship a chart-rich PDF with cover, tables, captions and page numbers. Requires Python 3.10+; the chart and PDF tools also need python-docx and matplotlib.

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.

Skill panel for the DSH Web GUI: lists every installed skill with Chinese annotations and eight category filters, runs pinyin and fuzzy search, ranks by pin and recency, and manages each skill in place (pin, disable, reveal, uninstall with undo). Ships its own maintenance skill.

Shows which skills each turn invoked and installs, updates or removes skills inside the app.

Manage a GitHub Pages blog from a DSH panel — browse the Markdown articles grouped by tag, edit them in a split editor with a front-matter form, and publish the changes as one commit over the GitHub REST API.

Meeting notes for dsh: one meeting per conversation, transcribed and speaker-separated on the machine itself, with points, assignments, handwritten notes, reviews and monthly scores in the same panel. Exports SRT/Markdown/Word and packs a meeting into a portable zip another dsh can import; confirmed assignments go to DingTalk/WeCom in one click, following your robot settings. Recognition models are swappable (a stronger local model can be imported from a file), and cloud recognition is off by default with no request made before consent. Word export needs Python and python-docx; the first run downloads a recognition model (28 or 77 MB).

Requires macOS and AirPods with head tracking. Answer DSH permission prompts and questions with AirPods head gestures — nod to allow or confirm, shake to reject or shift the selected option — and install the companion macOS menu-bar app from a card inside the session.

Per-workspace closet for temporary scripts and their run logs, kept in a .dsh-fix directory inside each project. Registers a script with its language and purpose, scans a project for leftover scratch scripts, backups and log files, runs registered scripts with a timeout and writes each run to a timestamped log, and sweeps chosen files into a reversible trash with per-batch restore. Scanning only lists and never deletes; cleanup moves files instead of deleting them; files already tracked by git are refused unless forced. Ships 7 agent tools and a settings panel.

Author custom tools in Python from a web page, in chat, or from the dsh-go app's native panels, and register them as DSH tools without a restart; dangerous tools need built-in approval on every run, tools can be grouped into packs, and an optional unlock mode exposes them per conversation. Needs Python 3 on PATH.

Runs a Claude Code project's .claude/ slash commands and permissions.deny rules inside DeepSeek Harness. Command bodies expand $ARGUMENTS, positional arguments and @file references into the agent's next turn; matching tool calls are denied before they run. Every host service is probed, so a host without a command registry, working-directory service or TUI status line degrades one feature instead of failing the boot.

Cross-session artifact center: agent tools that register deliverable files (PDF, Excel, PPT, code, JSON) into one shared directory, plus a sidebar panel that filters them by category, extension or keyword.

Model-driven tool-result archiving for DeepSeek Harness. Results above a configurable size carry a short inline id (\[#a1b2c3d4]); the model archives the ones it no longer needs into the session's own archives/ folder and the context keeps a small recoverable stub with the file path. Originals stay in the append-only session log, so nothing is lost. Ships a settings panel with per-size-bucket recovery stats, thresholds that apply without restart, and a conditional reminder when results are waiting to be archived. Requires dsh-better-sidebar for the statistics panel.

Turn English audiobooks (MP3) and documents into listening lessons: transcribe every sentence locally with the speech model DSH voice input already downloaded (about 241 MB, fetched on first use if missing; ffmpeg required), proofread and explain each sentence with your DSH model, then drill with blind listening, intensive listening and spaced repetition, with Chinese-dubbing export and offline Kokoro voices; ships a sidebar panel and four AI tools.

Release gate for AI answer quality. Two channels: replay an existing VeriScope archive through the original Python quality gate, or run a threshold gate over a Ragas per-row export with Node only — no VeriScope, Python or pandas. Returns PASS, FAIL or REVIEW with source evidence and a re-checkable receipt; supports per-row thresholds and exact decimal comparison. It never re-evaluates and never calls a model, and REVIEW never becomes PASS.

Local BM25 auto-recall, a fail-closed write guard, a static doctor and a memory panel for an Engramory markdown store. No network, no daemon and no model calls unless you opt in; recall quality is measured by a reproducible benchmark in the repository.