Плагины

A desktop companion for DeepSeek Harness (dsh): she lives on your real desktop (on top of your windows or inside the wallpaper), talks with you by voice and remembers you. · DSH 桌面女友：住在你真正的桌面上，能语音聊天、记得你。

Reference links panel for DeepSeek Harness: collects every URL of a conversation into the right sidebar with pins, turn counts, metadata and favicon caching. DSH 右栏「参考链接」面板。

A model-driven desktop pet, derived from PC2005-cloud/dsh-pet (MIT): an always-on-top companion that follows your agent sessions, races the Web UI to answer approvals and questions, keeps a per-pet affection ledger, speaks through pet_say/pet_do tools or an autonomous inner voice, and can read those lines aloud through BreezeBlue TTS with your own BreezeBlue API key. It uses its own /whale598 route and ~/.dsh/whale598 data directory, so it is a separate pet from dsh-pet rather than a replacement for it.

Loopback HTTP/SSE service that lets an Obsidian plugin drive DSH sessions and inject vault notes into the system prompt (path-based, re-read every turn, so edits show up next turn); needs the companion plugin running inside Obsidian.

File-based environment registry for DSH: manage environments, services, deployments and operation-to-Skill bindings through a panel and model-facing tools.

Adds an UpdateNotify tool and a live progress panel docked above the composer in the DSH Web UI, so the model can narrate what it just did, found, or is waiting on while a turn runs.

macOS notch panel for DeepSeek Harness: running sessions and pending approvals sit above every window, approvals are decided in place, and clicking a row opens that conversation in the desktop app. Requires macOS 14+ and Xcode Command Line Tools.

GitLab panel in the DSH right sidebar: commit graph, branches, changes, merge requests (inline diffs, review submission, pipelines), issues, and agent tools with an approval queue for triage and batch actions. GitLab data needs a personal access token or a logged-in `glab`; local git data works without either.

Read-only workflow panel for DSH: overview, six gates, milestones, org template, task flow and roster - project data from a project.json file, roster from the live DSH state, ledger presence from the ledger directory. Ships as a Cordis bundle with two GET-only routes and writes nothing to the project or the DSH state file.

Measures one university department's research output: matches author affiliation strings against a college's known name variants (detecting same-named departments at other universities), backfills papers that only name the university by faculty author IDs, classifies each paper by journal tier (CAS partition with Top flag, JCR quartile, CCF, Chinese core via a CNKI export merger), splits staff from student first authors, and writes a workbook with a dashboard sheet, a filterable paper list, a teacher-by-direction matrix and per-teacher statistics. Student authorship is inferred from affiliation and staff lists, not verified against enrolment records. Requires Python 3.9+ with pandas and openpyxl (pip install -r requirements.txt); papers come from the OpenAlex API, whose free per-IP quota is limited, and Chinese-journal coverage needs a manual CNKI export.

DeepSeek Harness sidebar panel for TeamAI skills, MCP, and prompts.

Relay that bridges DSH and the browser: tasks started from a browser extension run in DSH sessions, while page operations are driven back through browser_* tools, with an in-page assistant panel and a local wizard for one-click setup.

Keeps the DSH browser from accumulating tabs: once a configurable limit is exceeded it closes blank, error, duplicate and oldest pages, while leaving the page in use, newly opened tabs and keep-pattern URLs alone. Includes a settings panel with preview and manual cleanup.

Connects the Google Stitch MCP endpoint as 16 native `mcp__stitch__*` tools for projects, screens and design systems, plus an in-panel card for an API key or OAuth access token.

Look up Chinese companies inside the conversation: name a company and get its business registration, shareholders, executives, outbound investments and registration changes, plus judicial and operating-risk records such as enforcement, dishonest judgment debtor, consumption restriction, abnormal operation, serious illegality and administrative penalties (11 dimension groups). Results render as conversation cards with fields and the raw payload on expand, and the API key is saved from the plugin page into the Harness credential store.

Indexes public AI-company job boards (Greenhouse, Ashby, Lever, Workable, SmartRecruiters), scores postings for AI relevance, extracts the requirements from each job description, and produces a scheduled daily Markdown digest.

Bilibili companion for DSH (MIT fork of Alterssss/dsh-bili-whale; do not install alongside the upstream — both register the same `/dsh-bili/` settings routes and share `~/.dsh/bili-whale.config.json`): wakes on a schedule, reads videos through subtitles, danmaku, hot comments and covers, writes two diaries, and shares at most one pick per wake by commenting on the video and @-mentioning the owner (daily quota 3; DM when `share.via=dm`). Inbound DMs, commenter names, summary requests and live danmaku are normalized and scanned for injected instructions before they reach the model; only the owner DM channel can carry an authorization prefix.

Local-first, file-native long-term memory for DSH with per-turn preflight, compact context injection, citations, human-approved writes, manual consolidation, nightly report-only maintenance, and a Web panel that is read-only for knowledge while allowing workspace-config edits.

Layered global and workspace memory for DeepSeek Harness, with a web panel to browse entries and tune distillation and consolidation, an index kept in context with records loaded on demand, and a per-session choice of layer.

Unified long-term memory hub: captures turns into L0 evidence, distills in the background into L1 facts / L2 scenes / L3 profile (depth configurable), recalls via hybrid BM25+fuzzy search, ships 13 memory_* tools, traceable lineage back to source turns, optional Hindsight backend, and a built-in memory panel with three entry points.

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.

Diary and narrative memory for companion agents: daily first-person entries scoped per group or private chat, refs that can be checked against that day's messages, and a read-only journal page where hand-drawn doodles and photos follow the sentences they belong to.

Stores the agent's long-term memory as plain Markdown in an Obsidian vault — every memory is a .md file with YAML frontmatter that Obsidian indexes natively, so you can read, edit, link and back up it with tools you already use. Nothing is locked in a database. Ships a sidebar panel (tag filter, sort by recency or importance, edit in place), 7 agent tools, three-tier token-budgeted recall, BM25 ranking (no embeddings, no API key, works offline, CJK bigram tokenization), importance decay with archiving (moved to .archive/, never deleted), and optional GitHub Contents API sync. A note containing a secret is refused rather than redacted, because a redacted memory reads as complete while the important part is gone. Zero runtime dependencies; everything comes from the DSH host.

Session and image management for DSH: a sidebar panel deletes selected sessions together with their on-disk files after DSH has archived them, with multi-select, sub-agent / team-member / whole-family cascade and per-session size; a right-sidebar tab counts a session images and offloads or deletes the selected ones, optionally removing source files and attachment objects from disk.