A 267-skill research graph in pure markdown — 51 research operations built from 216 single-purpose steps, composed in any order with explicit backtracking. One npx install, no runtime, no MCP bindings. The AI is the researcher; you set the direction.

Local document knowledge base for DeepSeek Harness: library_add/remove/list, hybrid semantic+keyword library_search with diversity re-ranking, relevance filtering and lost-in-the-middle avoidance, citation-aware injection, library_cite_check and library_d

AI4Scholar for DeepSeek Harness (dsh): 38 native academic tools — Semantic Scholar, PubMed, Google Scholar, arXiv, bioRxiv/medRxiv, DOI resolution, PDF full text, auto-cite, scientific figures, credit balance — with an API-key card in the Web UI settings.

公文全流程处理工具——基于 GB/T 9704《党政机关公文格式》 国家标准，面向公文写作、企事业单位材料编制场景，支持 格式检查与修复、内容优化（Word 原生修订+批注/差异对比版）、模板生成、Markdown 转公文、版头版记页码注入、事实核验、风格增强 等完整能力。原生支持 DeepSeek Harness (DSH) 技能系统，打包为可被 AI Agent 直接调用的 Skill，完全自包含，克隆即用。

A portable memory protocol for AI agents — load it as standing rules; a curation discipline + reference spec + optional cap hook.

The dsh-plugin-guide knowledge base plus the dsh-plugin-dev CLI toolchain: official docs, Cordis primer, community deep-dives, and battle-tested pitfalls registered as an on-demand agent skill, with a scaffolder, static checker, and pack verifier for buil

Third-party provider reasoning-effort AND input-modality settings for DeepSeek Harness: thinking levels and image-input support declared per model, auto-adapted from a model knowledge base + wire-protocol inference, edited right inside the official Models

DeepSeek Harness (dsh) 从 0 到 1 深度手册：安装/插件开发/性能调优/实测案例/同模型多 Agent 实测对比（中文 + 英文 PDF）