Workflow & Automation

AI news sidebar plugin for DeepSeek Harness (DSH): scores RSS/Atom feeds on five axes, surfaces top items, and imports them into chat for follow-up.

Document-driven workflow plugin for DeepSeek Harness: verified index, clarification gates, notes & plan, live sidebar panel.

鲸翼：专家团队、个人知识与持续技能沉淀

DSH 网站运维工作台：一句话建站（自动配 nginx + 申请证书），查 SEO/GEO/安全与真实流量，部署前看影响分析、出问题一键回滚；新增流量分析、HTTP 探测、读文件、服务管理、只读诊断命令。

Share selected theme settings, installed plugins and skills by QR code, then review and install them together from an image or screenshot. The QR code carries the install manifest only; larger skill and plugin files are downloaded from the sources it names, so a code from someone else makes your Harness fetch and install from their source.

Guides RTL design and verification in DeepSeek Harness, with project scaffolding, evidence checks, and OpenROAD/ORFS setup.

Kaipu Workstation — a cross-cloud, cross-platform console where agents collaborate on one workspace. Any agent runtime that speaks plain HTTP can take a seat, each with its own device credentials: project context is shared, files are kept per seat, and tasks rotate between seats with a trace of who did what. Workstation data lives on the server — this plugin is only the interface, so uninstalling loses no data and reinstalling restores it. The panel renders the persisted workstation state (no live stream yet). Workstation data is stored on the author's hosted server (agent.ak2029.com/kai-pu) unless you override baseUrl in the profile config.

An audit workspace for DeepSeek Harness: a multi-agent consultation venue where each review seat is filled by an agent, every judgment is routed to a named review face, and the whole run is kept as a traceable record. Works out of the box: the service endpoint is built in, a workspace is provisioned automatically on first launch, and review scenes come with their seats and agents listed. The built-in service endpoint is the author's hosted server (agent.ak2029.com/kai-pu): scenes, runs and review records are stored there unless you override baseUrl in the profile config.

ZenTao workbench for DSH: load a ZenTao browse-page URL into a panel, multi-select bugs, tasks and stories, and hand them to the current or a new session with description, recent comments, screenshots as real image attachments and other files saved locally; when the agent is done it writes comments and status transitions (resolve, close, activate, start, finish and so on) back into ZenTao, one item or a batch, from the panel or through five registered agent tools (bug write-back verified end to end, task and story forms share the same code path).

Right-sidebar novel studio that treats a chapter as a pipeline with checkable artefacts instead of one long prompt: scaffold a project, inspect the exact context pack a chapter gets, generate 2-6 parallel candidates and keep the one you pick, then run chapters in sequence with per-chapter progress on disk so it survives an engine restart. Length band, cross-chapter Jaccard and drift ratio are enforced in code rather than by model self-grading; rejections come back as repair evidence for up to two rewrites. AI-fingerprint metrics are reported against a 3956-chapter human baseline but never block, because the distributions overlap. Ships 7 agent tools. The writing engine is a separate Python package that the plugin installs on first use. Needs Python 3.10+ on PATH (or a path set in the plugin settings).

Runs allowlisted Python hook scripts on session events and injects the text they return into the next turn, so standing rules live in editable .py files instead of the prompt. Needs Python on PATH; it only runs scripts whose names are on its built-in allowlist.

Project board in the sidebar: a self-contained HTML Kanban and Gantt page served over a same-origin route, drag-and-drop columns, due-date timeline, JSON import/export, data kept in local storage.

Syncs DSH skills, profile settings and AGENTS.md with a private git repository: status chip, six-section health check, pull, secret redaction, and a snapshot-then-push flow. Dry-run by default, never rebases or force-pushes.

A multi-project todo board inside DSH: capture notes in a global capsule overlay, group them into projects and mind maps, and export a todo into the composer as a task for the agent. Notes and todos are read and written on the author's hosted service (todo.memorymap.cn) after you sign in; set config.apiBase to point it at your own backend. Its HTTP routes have no DSH access check.

A Windows Harness adaptation of [Media Review Skill](https://github.com/Ww-Cooooo/media-review) for AI video feedback: annotate frame regions or time ranges and jump to recognized speech or imported subtitle cues; other Agents with local file and command access can use the original Skill. Windows only and built for DSH 0.2.2-rc.1 (a 0.1.0 release candidate). Waveforms use an existing FFmpeg/ffprobe and transcripts an existing Whisper; without them, manual annotation and subtitle import still work.

Long-form fiction workflow for DSH: seven queryable bibles, edit-impact tracking, living relationship and plot maps, and a first-chapter tryout that picks your writer. Its /novel-panel routes, including save, archive and reconcile, are mounted with webServer.register and carry no DSH Host/Origin admission check, so a web page open in your browser can write to the novel project through them.

Track source lineage for web excerpts and structured Agent reports, fold repeated text with recorded provenance, and export auditable evidence through DSH tools.

Adds one system-prompt section that limits delegation to subagents and teammates to two cases: adversarial review of freshly produced output, and one-shot context reading that returns a summary.

Research-style problem solving in four gated stages: record sources by retrieval tier with local before web, turn each shortfall of existing tools into a gap that needs evidence, score candidates against weighted metrics with a deterministic engine, fuse or improve the weak ones, then iterate on measured deltas. Also organizes a directory into human-facing and machine-facing trees.

Run Google Antigravity CLI (agy) as DeepSeek Harness subagents, with Gemini web Deep Research and parallel/team modes.

Deep research for DeepSeek Harness: multi-query search, source fetching, evidence extraction and a cited evidence report, through the host ctx.web service. · DSH 深度研究插件：多查询检索、正文取证、交叉印证，产出可引用的证据报告。

Track, branch, compare and reproduce local CSV classification and regression experiments through DSH tools backed by MLflow; requires a separately installed Python backend. By default training runs as detached local worker processes that keep running after DSH exits (executionMode dsh stops them with DSH); running your own Python preprocessing or estimator code needs allowCustomCode, which is off by default; the plugin makes no network requests.

Manage iterative text annotation through DSH tools with rule versions, stale-result isolation, human review preservation and traceable exports; requires a separately installed Python backend.

Local CLI bridge for Codex or terminals to create and continue conversations in the running Harness desktop/Web Host, query progress, wait for output, and cancel tasks. Needs Harness 0.2.2-rc.1 and Node.js 24.9+. Requests travel through a per-user file queue in the Harness home (no network port), and approvals and questions stay in the Harness UI.