2026年8月18日 技术热点总结

项目简介：dsh-routing-suite — injector + router-standard kit: install the runtime injector first, then the task-aware reasoning-mode router preset (measured P1-P23).

技术栈：PowerShell

核心介绍：一个仓库装齐「运行时手术台 + 思维模式路由预设」：先装注入器（免重启运行时管理层）， 再用它装配 router-standard 预设（任务感知思维模式路由，P1-P23 实测）。 中文 | English

关键特性：三行为带 + weak 内路由：spec（计划-集体）/ react（执行者）/ mixed（陷阱，回避）/ weak（模型自分类）；按模型选 persona：Pro=spec 句+few-shot（区分度 +5.0）；Flash=neutral+classify（+5.7）；近距离引导：每轮用户消息后注入固定引导（缓存 92-94% 命中），路由 96% + 收敛 100% + 反稀释；单任务三锚（persona 静态）：回顾 + 收敛 + 反跑题 —— 开放任务完成率 0% → 100%；plan-mode 保留：只替换 p…

项目简介：Two-phase DeepSeek Harness preset: Minimal-aligned bootstrap, then full Standard tools (Project2 98/99)

技术栈：JavaScript、deepseek、deepseek-harness、dsh-plugin、llm-agent

核心介绍：中文说明 Experimental DeepSeek Harness agent presets — a base mode, two live-anchor variants, and one seeded prefab mode — that anchor a session’s model trajectory on the Minimal condition (real Minimal tool schema, no auto-injected context), then promote to a small resident catalog once the session is durable, unlocking heavier Standard tools This is a community project. It is not an official DeepSeek prese…

项目简介：Opinionated Oxlint rules for rejecting low-evidence TypeScript and JavaScript patterns

技术栈：TypeScript、agent-skills、linting、oxlint、typescript

核心介绍：Opinionated Oxlint rules that reject low-evidence and low-signal TypeScript and JavaScript patterns. This project is meant to be vendored, not treated as a fixed npm dependency. Copy the rules into your repository, read them, and change them to match your team’s standards. The bundled agent skill handles the initial copy and configuration; after that, the vendored files are yours to maintain and make your own.

项目数据：⭐ 2,358 …

项目简介：DSH Web 鲸鱼娘皮肤系列(深海女仆工坊 maid-atelier)——CC BY-NC-SA 4.0

技术栈：TypeScript、dsh、dsh-plugin

核心介绍：DeepSeek Harness Web GUI 的鲸鱼娘主题皮肤系列(独立分发仓库)。 点击图片可查看完整尺寸。 *反馈问题尽可能在 issue 中发起，而不是跑去联系上面两位老师。但是，看鲸鱼娘二创可以去关注一下，谢谢喵

项目数据：⭐ 1,250 Stars，🍴 41 Forks

项目简介：简历包装

技术栈：HTML

核心介绍：中文求职工作流插件 用五个独立入口完成开源贡献、经历酥化、简历制作、同款简历复刻和秋招进度管理。 现在输入“我想要阿酥同款简历”就能制作属于你的简历！支持 AI 编辑和手动编辑。 ASu 正在建设一套面向求职场景的 Harness 工程，欢迎通过 Issue 和 PR 一起补充真实求职案例、技能和终端体验。 前往 GitHub 查看 ASu Harness 工程 ASu-skills 现在是一个插件包。安装后会提供五个可单独调用的入口：

项目数据：⭐ 1,138 Stars，🍴 90 Forks

In 2023, a New York judge sanctioned two attorneys in Mata v. Avianca for filing a brief with hallucinated citations generated by ChatGPT. Such failures are largely caught by database lookups; the harder problem is detecting citations that point to real cases but do not support the propositions for which they are offered — a failure mode that existing evaluations of LLMs for legal use cases largely overlook. In this paper, we study proposition-level citation support verification through controlled perturbations of real legal citations obtained from two legal corpora, either replacing the c…

Nanbeige4.2-3B is a 3B-parameter agentic model built around a Looped Transformer (LT) that reuses one stack of layers for a second forward pass, adding effective depth without additional parameters. Evaluated on Apple Silicon (MPS), we identify five independent bugs which prevent the released checkpoint from running via Hugging Face transformers out of the box (including a silently-zeroed RoPE buffer and calls to removed transformers cache APIs). Furthermore, we show that fixing these bugs is still not sufficient for agentic tasks, due to the LT's layer-reuse strategy (which effectively dou…

Which reasoning behaviors are associated with correct answers in reasoning models, and does reasoning-oriented training amplify those behaviors? This distinction is important because reasoning-oriented training can make traces look more deliberative without amplifying the behaviors most tied to model correctness. We quantify this mismatch with Behavioral Lift, a metric that measures how much correctness changes when a behavior is present versus absent in a model's reasoning trace. Across 15 models and 6 benchmarks spanning text-only and vision-language reasoning, we annotate 15,282 traces w…

The human brain exhibits a striking degree of functional specialization, with distinct networks supporting language, formal reasoning, reasoning about other minds, and reasoning about the physical world. Is this modular organization a fundamental principle of how intelligent systems must be built, or an evolutionary accident specific to biological brains? Here, we test whether a similar organization emerges in Large Language Models–another class of intelligent systems created through a very different optimization process. Using circuit analyses across N=46 tasks spanning four cognitive dom…

Apollo did not reach the Moon merely because its engineers could solve difficult equations. It succeeded by turning a distant ambition into a mission architecture of explicit objectives, simulation, verification, and repeated correction. AI now faces a similar transition: frontier models can solve difficult tasks once the problem, tools, and success criteria are specified, yet consequential real-world challenges rarely arrive in an executable or verifiable form.
We introduce Apodex Discovery, a framework for building and evaluating discoverative AI through the heavy-duty solver, a system …

Parliamentary proceedings are a primary record of democratic deliberation, yet their volume and fragmentation make multi-perspective access difficult for citizens, journalists, and researchers. Applying Retrieval-Augmented Generation (RAG) to parliamentary transcripts introduces three specific risks: dominance of the most frequent speakers, inability to weight speakers according to topical expertise, and citation misattribution in politically sensitive text. We present ParliamentRAG, a RAG system for the Italian Chamber of Deputies that addresses these risks jointly. Its core contribution i…