Plugins

Standalone Skills page for dsh: lists every skill with an enable switch at global, project or session scope, keeps unchecked skills out of the model catalog, and sorts them into named categories.

Sales workflow for individual insurance agents: P1-P5 product class matched against the client risk rating, a policy ledger that counts grace periods from the receipt date, and five-section dual-recording checks. 10 tools and 5 skills.

Run Blender headless from DeepSeek Harness: execute bpy scripts, render scenes and export glTF assets, with modeling cookbook, 5.x pitfall list and asset-pipeline playbooks bundled as skills so the agent self-checks geometry before handing assets back.

Memory that outlives the session, kept as plain daily log files: one markdown file per day plus a generated index the agent greps instead of re-reading. Registers the annals skill, injects the write-it-down rules into the system prompt, and exposes three tools — annals_init builds the log directory, the index generator and a separate Git repository in one call; annals_query full-text searches past entries and returns them with file and line anchors; annals_links resolves which entry cites which. Reminds the agent once per turn when it changed files but wrote no log that day, and once more when the log was updated but the index was not. Adds a settings page for the six switches.

Quantify what switching projects costs. Measures each workspace's cold-start overhead (AGENTS.md + skill catalog + tool schemas + runtime context), its steady state, and how many turns it takes to reach it — then compares workspaces and attributes the difference. Attribution requires at least three workspaces and says so instead of inventing a correlation from two points; a factor with no spread across workspaces is reported as a property of the profile, not of the project. Recommends which workspaces to keep warm, which to archive, by entry cost times visit frequency. Deterministic.

Delegate DSH tasks to a paired LAN worker and drive it like a subagent (ACP over WebSocket).

Expert center: browse and import WorkBuddy experts, create experts with AI, edit role.md and skills, and switch experts per session.

DeepSeek Harness (DSH) 官方与开源生态「插件与 Skill 双生态市场」一键安装与资产管理中心 (Plugins & Skills Market)

Floating toolbar on selected text in the DSH conversation: copy / follow up / collect to Feishu / deliver to the inbox Base / rewrite.

General Agentics distribution bundle for DeepSeek Harness (DSH): one install brings the General Agentics white-label brand, curated plugins, bundled skills, and MCP pre-configuration. Built on DeepSeek Harness (DSH).

DeepSeek Harness 插件：在 Boss 直聘求职者侧浏览岗位，为每条 JD 生成只属于它的自我介绍并发给 HR（可见浏览器 + CDP 状态机 + 文案护栏）

把 agent-skills 的 git-kit Git 工作流、handoff 跨会话交接与 disk-cleanup 磁盘清理以 dsh 原生斜杠命令接入（薄意图表，委托对应 skill 执行）

Install Desert Ant Labs on-device models as DSH tools and skills, with per-platform capability gating

Configuration vault for DeepSeek Harness: snapshot, diff and safely roll back profile patches, plugin manifests, skills and workspace lists, with credentials excluded by default.

Move an entire dsh installation to another machine and check it item by item. Three layers go across: the declaration layer (settings, credentials, plugin declarations and vendored link: sources), the state layer (sessions, storages, skills, attachments) and, optionally, the workspace project code. Sessions are rewritten at the zstd header frame only, workspace paths are remapped through an explicit path mapping, and at the end 14 checks (I1–I13 plus I6b) report PASS / FAIL / WARN. A LAN route pairs two machines and pulls the bundle over directly; merge mode diffs a bundle against a machine that has already been in use and stops before writing anything while conflicts are undecided.

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.

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.

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.

Skill-creation console for the Web UI: fetches the official creator skills, hands the requirements to the Huawei Cloud, generic, or REST API creator, then scores the generated skill against a 10-point rubric and returns the itemised deductions to the creator until it reaches 8.5/10.

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.