Plugins

Focus-aware notifications for DeepSeek Harness: approvals, questions, plan reviews and finished replies appear as one alert only when the conversation window loses focus; background conversations alert at any time and subagent sessions never do.

Move45clock: a health clock for DeepSeek Harness. A 45-minute work timer (5–120 minutes), 12 guided 12–15 minute seated/standing break plans, a visual plan editor, reminder cards scalable to 200%, night reminders at 21:30/22:00/22:30, and optional action-name voice coaching. Window wake is Windows-only.

Toasts from DeepSeek Harness when a turn finishes, and when it stops for approval, a question or a plan exit. Native on Windows, text and timing configurable.

In-conversation workflow run timeline for DSH Web: a horizontal rail with phase stations, agent pills, loop arcs and parallel bands replaces the stock workflow tool card and workflow-run chat node. Planned stations render before the run starts via client-side script scanning; status dots and icons follow DSH official primitives.

Registers native doubao_generate_image and doubao_image_status Agent tools to automate Doubao Web (doubao.com) via Tabbit Browser, automatically extracting watermark-free 2.7K wm0 original images into local files and multimodal chat attachments.

Dual-brain agent presets for DSH: one model plans the framework and delegates execution to a subagent pinned to a second model. Ships brain-ds (DeepSeek-V4.1-Flash plans, MiMo-V2.6-Flash executes) and brain-mimo (the reverse), switchable per session. Needs two providers configured (Xiaomi MiMo and a DeepSeek account), and the main brain must be selected manually.

Agent preset for DeepSeek Harness: the standard tool stack plus four working rules written into the persona prompt — a project keeps at most four documents (intro, decisions, change log, current state and next steps), those documents describe only the current state with no AI edit history or superseded decisions, no git commit or push or pull request until the user explicitly asks, and a careful-coding workflow (restate the goal and done-criteria first, surgical diffs, evidence before claiming success) with plain-language reports.

Multi-agent meeting negotiation over the LAN: each person runs their own assistant, and assistants find each other via mDNS and negotiate meetings, weekend outings and bubble tea votes through A2A messages. They share only availability (never the reasons) and ask the owner before giving up protected time. Ships a phone-style page in the DSH sidebar and a 13-person sample company. No authentication; trusted LANs only.

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).

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.

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.

Skill manager page for dsh: set each skill to on, manual only, model only, or off per agent mode; count how often each skill is loaded per mode from the session history; search skills.sh and install from GitHub; import from Codex, Claude Code, or a folder; create, edit, and version skills, with a trash for deleted ones; modes keep working after an uninstall.

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.

Competitive-informatics senior plugin for DeepSeek Harness: companion practice, three-version C++14 reference solutions, problem explanations, real g++ compile-and-judge (g++ required), and optional solution-record archiving to the ima notebook "信奥学长-题解复盘", for GESP / CSP-J/S / NOIP / NOI.

Competitive-informatics coach plugin for DeepSeek Harness: coaching-rule prompts, learning roadmap, knowledge points, problem setting, real C++ judging with g++, and ima knowledge-base retrieval with four-notebook archiving, for GESP / CSP-J/S / NOIP / NOI teaching. Needs g++, and an ima account with ima-skill and the four notebooks configured; replies carry a WeChat-account promo and QR code by default.

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.

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.

Interior and exterior ballistics paper reproduction and code generation skill. Requires LibreOffice Kit for PDF rendering and a vision API key (e.g. Qwen-VL) for formula OCR.

DocChain knowledge base and document conversion toolkit — filename, content and metadata search, topic listing, bulk document upload, document-to-Markdown conversion, image-similarity search, and a deep-research workflow. The configuration page keeps several docchain environments (each with its own address and credential), switches between them in one click, and pre-selects topics per environment. Needs a docchain service URL and API key (except doc2markdown).

Windows x64 translator with a dedicated sidebar entry and Workbench / Chat interface, side-by-side text and document translation, screen-region translation, recent history, and host model selection, voice input and preview. CUDA document OCR with CPU fallback; screen OCR uses CPU. Do not enable the CPU and CUDA packages at the same time.

Windows x64 translator with a dedicated sidebar entry and Workbench / Chat interface, side-by-side text and document translation, screen-region translation, recent history, and host model selection, voice input and preview. CPU OCR without NVIDIA dependencies. Do not enable the CPU and CUDA packages at the same time.