Nous Research Updates Hermes Agent With a Blank Slate Mode That Pins Toolsets via platform_toolsets.cli and disabled_toolsets
重點摘要
Nous Research has added a Blank Slate setup mode to its open-source Hermes Agent. It inverts the usual onboarding. Instead of a fully loaded default, you start with almost nothing. Hermes Agent is the self-improving agent framework from Nous Research. It runs on your own machine. The team announced the new mode on X. Blank Slate now joins two existing options: Quick Setup and Full Setup. TL;DR Blank Slate boots an agent with everything off except provider & model, File Operations, and Terminal. Web, browser, code execution, vision, memory, delegation, cron, skills, plugins, and MCP stay disabled. It writes an explicit platform_toolsets.cli list plus agent.disabled_toolsets to pin the surface. Nothing you skipped loads later — not even after hermes update. Re-enable anything with hermes too
Nous Research has added a Blank Slate setup mode to its open-source Hermes Agent. It inverts the usual onboarding. Instead of a fully loaded default, you start with almost nothing. Hermes Agent is the self-improving agent framework from Nous Research. It runs on your own machine. The team announced the new mode on X. Blank Slate now joins two existing options: Quick Setup and Full Setup. TL;DR Blank Slate boots an agent with everything off except provider & model, File Operations, and Terminal. Web, browser, code execution, vision, memory, delegation, cron, skills, plugins, and MCP stay disabled. It writes an explicit platform_toolsets.cli list plus agent.disabled_toolsets to pin the surface. Nothing you skipped loads later — not even after hermes update. Re-enable anything with hermes tools, hermes skills opt-in --sync, or hermes setup agent. What is Blank Slate On a fresh install, hermes setup now offers three modes. The choice sets your starting surface area. Quick Setup uses the Nous Portal. It needs no API keys and uses a free OAuth login. It sets up a model plus the Tool Gateway tools. The docs call it the recommended fast path. Full Setup is the opposite. You walk through every provider, tool, and option yourself. You bring your own keys. Blank Slate is the minimal third path. It is for building an agent from the ground up. Everything starts off except the bare minimum needed to run an agent. That minimum is three pieces: provider & model, the File Operations toolset, and the Terminal toolset. The disabled list is explicit. Off by default: web, browser, code execution, vision, memory, delegation, cron, skills, plugins, and MCP servers. Compression, checkpoints, smart routing, and memory capture are also disabled. Hermes Agent has a new Blank Slate setup mode.The default Quick/Full setup modes work great for most, but if you would rather build your agent from the ground up you can now start with just a provider, model, file operations, and terminal, then manually add in anything else. pic.twitter.com/EiFm7tW3Ws— Nous Research (@NousResearch) June 20, 2026 The Two Paths After the Baseline Blank Slate does not stop at the baseline. After the minimal baseline is applied, you choose one of two paths. The first path keeps everything disabled. You finish now with the minimal agent. You get file and terminal access, and nothing else. The second path walks through all configurations. You opt in to tools, skills, plugins, MCP, and messaging. You enable only what each workflow needs. Pick Blank Slate when you want a minimal, fully-controlled agent. The point is to enable exactly what you need and no more. Why the Config Format Matters Blank Slate does not just toggle features at runtime. It writes the decision to disk. The mode writes an explicit platform_toolsets.cli list. It also writes agent.disabled_toolsets. Together, these two keys pin your agent’s surface. The effect is durable. Nothing you did not choose ever loads. That holds even after hermes update. An update cannot silently re-enable a toolset you left off. Hermes also separates secrets from settings. Tokens live in ~/.hermes/.env. Non-secret settings live in ~/.hermes/config.yaml. The CLI routes each value to the correct file. Setup Modes Compared ModeEnabled by defaultKeys / authBest forQuick Setup (Nous Portal)Model + Tool Gateway toolsFree OAuth, no API keysFastest first runFull SetupEvery tool and option you pickBring your own keysHand-tuned, full controlBlank SlateProvider & model, File Operations, TerminalProvider auth onlyMinimal, fully-controlled setups Use Cases With Examples Three situations fit Blank Slate well: A security-sensitive deployment is the first. You want an agent with no web and no browser. Blank Slate ships file and terminal access only. Nothing reaches the network unless you add it. A reproducible team setup is the second. You pin one known toolset across every machine. Updates will not drift the configuration. New tools never appear without an explicit opt-in. A teaching or audit environment is the third. You start minimal and add one toolset at a time. Each capability becomes a deliberate choice. Here is a minimal flow. Install, run setup, choose Blank Slate, then finish now. Copy CodeCopiedUse a different Browsercurl -fsSL https://hermes-agent.nousresearch.com/install.sh | bash source ~/.bashrc # or source ~/.zshrc hermes setup # choose Blank Slate, then "finish now" hermes # file + terminal only Later, add one capability when a task needs it. Copy CodeCopiedUse a different Browserhermes tools # re-enable a toolset, e.g. web hermes skills opt-in --sync # seed skills on demand hermes setup agent # tune compression, routing, memory A Note for Local Setups Hermes Agent requires a model with at least 64,000 tokens of context. Smaller windows are rejected at startup. Most hosted models meet this easily. Local models need an explicit context size of 64K. For example, use --ctx-size 65536 for llama.cpp. A minimal Blank Slate agent on a local model still has to clear this floor. Interactive Explainer (function(){ var f = document.getElementById('hbs-embed-frame'); window.addEventListener('message', function(e){ if(e && e.data && e.data.hbsHeight){ f.style.height = e.data.hbsHeight + 'px'; } }); })(); Check out the Technical details. Also, feel free to follow us on Twitter and don’t forget to join our 150k+ML SubReddit and Subscribe to our Newsletter. Wait! are you on telegram? now you can join us on telegram as well. Need to partner with us for promoting your GitHub Repo OR Hugging Face Page OR Product Release OR Webinar etc.? Connect with us The post Nous Research Updates Hermes Agent With a Blank Slate Mode That Pins Toolsets via platform_toolsets.cli and disabled_toolsets appeared first on MarkTechPost.
Related
相關文章
Crawlee for Python:打造具備機器人處理、連結圖譜與RAG分塊匯出的網頁爬取管道
在本教學中,我們建置了一套完整的 Crawlee for Python 工作流程,涵蓋環境設定、本機網站生成、靜態爬取、動態爬取、結構化擷取及下游資料處理。首先,我們配置相容的 Crawlee 執行環境,包含固定版本的 Pydantic 支援、Playwright 瀏覽器安裝、持久化儲存目錄,以及 Colab 安全執行處理。接著,我們產生一個擬真的本機示範網站,包含產品頁面、文件頁面、部落格內容、內部連結、robots.txt 規則、JSON-LD 元資料,以及 JavaScript 渲染的商品目錄。透過 BeautifulSoupCrawler,我們執行快速的遞迴 HTML 爬取,並擷取頁面標題、元資料、文字預覽、對外連結、產品屬性、文件標題、程式碼區塊與部落格標籤。

NVIDIA AI 推出 SpatialClaw:無需訓練的代理程式,將程式碼視為空間推理的動作介面
NVIDIA Research 發布了 SpatialClaw,這是一個無需訓練的空間推理框架。該框架針對視覺語言模型(VLM)持續存在的弱點——難以判斷物體的位置、相對關係及在三維空間中的移動方式。SpatialClaw 不重新訓練模型,而是改變代理程式用來呼叫感知工具的動作介面。研究團隊指出,介面才是瓶頸所在。他們的解決方案是將程式碼作為動作介面。在 20 項基準測試中,SpatialClaw 達到平均 59.9% 的準確率,比近期發布的空間代理 SpaceTools 高出 11.2 個百分點。
網易有道全面向AI轉型 全場景Agent矩陣亮相圖博會
{"id":"39ef5947-b77a-4904-bf03-ff6264f08dc4","object":"response","model":"deepseek-v4-flash","output":[],"stop_reason":"max_output_tokens","usage":{"input_tokens":154,"output_tokens":200,"total_tokens":354}}
MosaicLeaks: Can your research agent keep a secret?
Back to Articles MosaicLeaks: Can your research agent keep a secret? Enterprise Article Published June 18, 2026 Upvote - Alexander Gurung agurung Follow ServiceNow Rafael Pardinas rafapi-snow Follow ServiceNow TL;DR Deep research agents increasingly combine private local documents with external tools like web retrieval, creating a privacy risk: an agent's external queries may leak sensitive information. MosaicLeaks proposes a new deep-research task with multi-hop questions that interleave public and private information. Across the models we tested, agents frequently leaked private information, and training only for task performance made it worse. We propose a mosaic-leakage-aware RL training method, Privacy-Aware Deep Research (PA-DR), which raises strict chain success (the share of chains

騰訊老兵+大廠00後新銳,碼上飛想做的不只是AI Coding
這篇消息聚焦「騰訊老兵+大廠00後新銳,碼上飛想做的不只是AI Coding」。原始導語提到:已接入華為鴻蒙生態 從 AI 情報角度來看,這類內容值得關注其背後的技術進展、產品落地、產業競爭與後續市場影響。

Agent引爆網盤大戰,騰訊、百度、阿里齊聚,這次爭的不再是下載速度
這篇消息聚焦「Agent引爆網盤大戰,騰訊、百度、阿里齊聚,這次爭的不再是下載速度」。原始導語提到:網盤成了Agent新基建。 從 AI 情報角度來看,這類內容值得關注其背後的技術進展、產品落地、產業競爭與後續市場影響。