Plugins

Normify · DSH 插件：把项目架构写成归一化的分形模块树，三层校验（写时 / 校验 / 冻结回执）、30 个 normify_* 工具 + normify-gen 技能，一键渲染单文件交互式架构图；支持伴随式开发（change_open → brief → check → 实施 → refresh → change_close）。

Complete chinese-traditional-wisdom (玄枢 / XuanShu) skill pack as a DeepSeek Harness Cordis plugin: bazi, ziwei-doushu, liuyao, meihua, qimen, daliuren, taiyi, wuyun-liuqi, constitution and fengshui calculation, with a local deterministic engine and a visualization dashboard.

Quantitative R&D toolkit for DeepSeek Harness — 59 tools across six domains covering market data, indicators, factor evaluation, walk-forward ML validation, risk (VaR/CVaR/drawdown/Beta with Kupiec POF), options, bonds, FICC and fund simulation, with an end-to-end PDAT→PET research pipeline.

DSH Web 输入框接管（v0.3.0-beta.4 · 复杂任务能力包：3D/法向量/交互/数据/并发/性能细节逐项过关 + 可自动化验收 + 中英双语 · 适用于 dsh-0.1.6-alpha.1）：发送前用独立 AI（传话者）把提示词优化成可直接发给工作 AI 的命令（四档强度、按难度定流程长度、按会话隔离、极简迷你窗）

Local Obsidian vault as the agent knowledge store, with read-only DSH tools that route status, preference, correction, memory, project, search, and suggest to the matching page.

lowtide: human-adjudicated off-peak batch task pipeline for dsh (peak/valley pricing aware)

Off-peak batch runner for DeepSeek Harness: users define tasks during busy hours — prompt, strategy, priority, workspace, locked files — and release them by hand; the plugin then runs the batch automatically inside user-defined off-peak windows. Each run passes five preflight checks (workspace, git HEAD, locked-file sha256, window fit, daily budget), supports four execution strategies (single / iterative / sampling / review) and three autonomy levels (L1 per-task, L2 batch, L3 full-auto), and closes the loop with a morning report containing diffs, actual spend and savings from a daily ledger aligned with official peak/valley pricing.

SkillRoute by JEStats: skill routing for DeepSeek Harness agents.

A persistent agent team for long-running collaboration in DeepSeek Harness: durable agent identities, per-project Workspaces, responsibility-bearing Channels, and Task Threads chaining session agents.

Feishu/Lark bridge for DeepSeek Harness: scan-to-connect PersonalAgent binding, streaming cards, git-worktree project workspaces, parallel per-scope tasks, multi-role agents, cross-session notify, in-chat model/key management, and a safety-net guardian that still answers in Feishu after dsh crashes.

Local-first A-share research workbench for DeepSeek Harness: market dashboards, watchlists, valuation, four investor agents, versioned reports, and continuous post-report chat.

Local Obsidian vault as the agent knowledge store, with read-only DSH tools that route status, preference, correction, memory, project, search, and suggest to the matching page.

Cross-platform Computer Use for DeepSeek Harness: virtual-mouse human-like operation (screen_observe + computer_click + type + key + scroll + drag, 11 tools), AX-tree zero-vision-cost mode with free GLM-4V-Flash vision fallback, safety guards (snapshot TTL / app whitelist / dangerous-action approval / password-box protection).

DeepSeek Harness (dsh) bundle wiring SkillRoute's skill router into your agents.

DeepSeek Harness (dsh) bundle wiring SkillRoute's skill router into your agents.

给 HR / 猎头的 AI 招聘工作流：岗位标准梳理、Boss直聘 + 猎聘双通道寻源初筛、市场人才盘点、简历评估、约面试、候选人台账与日报。可装成 Claude Code 插件或 DeepSeek Harness (dsh) 插件——后者自带可直接上手操作的「招聘浏览器」面板；也能配合任意读 AGENTS.md 的 AI 编程助手使用。

Web access for DSH agents: fetch JS-rendered or protected pages as clean markdown, aggregated search across 14 engines, and stateful interactive sessions (click, type, scroll, eval, screenshot) against a hosted or self-hosted Rust browser engine. Every session returns a live view URL so a human can watch the agent browse and take over with the mouse.

QA pipeline as 10 agent skills: requirement analysis, test strategy, case writing and review, E2E (Playwright) and API automation, exploratory, regression scope and bug analysis, backed by a shared knowledge base with format rules, risk model and schema validators.

Lists the Markdown documents, images and video that already exist anywhere in the session workspace in the DSH sidebar, ranked by relevance to the current conversation: recent messages are matched locally against document title, summary and body with IDF weighting, with no model calls and no network. Because the list is scanned from the workspace instead of remembered, restarting DSH or starting a new session does not empty it. Images and video preview in place, with relative-path images resolved and video streamed over HTTP Range. A references bar under the preview header shows which documents cite the one being previewed and which it cites, with one click to jump between them. The same ranking is exposed to the agent as a knit_docs tool, which returns the most relevant documents along with the passage that matched in each, where one is found.

The marketing OS for AI agents — think like a marketer first, get tactics as the output.

Unified multi-provider web search and fetch: BYOK key pools, health monitoring, and deterministic fallback.

Local-only project memory with zero bundled runtime dependencies or external services: JSON as the source of truth plus generated PROJECT_MEMORY.md, token-bounded session-frozen Hot Memory for prompt-prefix cache stability, cached cross-project BM25 recall, trusted session/turn provenance, explainable pre-write duplicate/conflict governance, editable importance/pin/tags/supersede/archive lifecycle, configurable top-level turn-end distillation, and a bilingual Web GUI for search, inspection, diagnostics, and live settings.

OpenCues for DeepSeek Harness — LLM word alternatives and `_`-gated blank fill-ins in the dsh composer.

Installs four multi-agent math-research presets for DSH: v2 (probability-driven pipeline with multi-verifier debate), v3 (paper-style Markdown knowledge base with a planner agent and a reusable method library), v4 (persistent self-organizing residents that message and meet), and v5 (a research institute with an academician who decomposes and assigns work, voting researchers, temp workers, group chat and a compare-and-set task board); all four support checkpoint resume, human intervention, and an optional Lean formal-verification switch (off/encourage/require) whose passing proof turns the vote into a fidelity check of the Lean statements.