按类别或厂商查找并获取网络安全报告,比较威胁、勒索软件、数据泄露、云安全和AI趋势。分析会注明每项数据的厂商、年份及报告,并分别呈现来源间的分歧。
- 按类别查找威胁报告
- 获取指定厂商的报告
- 比较多家厂商的勒索软件趋势
根据家庭记录的食物、饮品和餐厅偏好推荐用餐地点或菜品,也能记录新的心仪餐厅。资料未记录的信息会明确标出,不会凭空猜测。
The household's food and restaurant preferences, used to recommend where and what to eat. USE WHEN where should we eat, restaurant recommendation, what do we like to eat, our favorite restaurants, pick a place for dinner, date night dinner, find a spot for a cuisine, what beer do we like, food preferences, suggest a restaurant near X, best restaurants in <city>, where to eat on our trip, add a favorite restaurant, remember this place. NOT FOR phoning to book a table, ordering delivery, business search or reviews (a scraping skill or Google Maps), groceries or recipes, business research (an OSINT skill, if installed).
实测评分 未实测
查看安装方法Restaurants 会参考家庭记录的菜品、饮品、菜系和餐厅偏好,推荐用餐地点或点餐选择。如果您提供地点或用餐目的,它会结合这些条件和已有偏好筛选候选,并说明推荐理由。与已记录的避雷条件冲突的餐厅不会列入候选;若推荐记录中没有的餐厅,会明确标为新建议。您也可以要求添加心仪餐厅,以更新偏好记录。
想决定晚餐或约会去哪里、在旅行目的地寻找餐厅,或查询家人喜欢的菜品和啤酒时,可以使用此技能。记录下来的饮食偏好也可用于之后的餐厅推荐。
推荐之前会先查看偏好文件。如果文件不存在,技能会引导您完成初始设置,不会假定默认口味并据此推荐。此技能不用于电话订位、下外卖订单,也不用于搜索食品杂货或食谱。
本介绍由 AI(OpenAI Codex)根据公开的 SKILL.md 撰写。准确的规格请查看下方原文。
AI 根据 SKILL.md 的内容检查了需要注意的操作和使用前提。评分只依据实际运行的结果(实测对比)。
不计入评分。 由 AI(OpenAI Codex)于 2026年10月28日 评估。仅供参考,安装前请同时查看原文。
安装前可以查看交给 AI 代理的指令内容。
Holds the household's food, cuisine, restaurant, and drink taste profile — what they love, what they avoid, where they like to eat, what they drink — and uses it to recommend a place, suggest what to order, or recall their preferences. The data lives in LIFEOS/USER/CUSTOMIZATIONS/SKILLS/Restaurants/Preferences.md, the source of truth; this file only routes and holds no taste rules.
TBD, so later picks never inherit a guess.TBD or missing: a short drink list or cuisine ranking is reported as short, and a place's cuisine, address, or menu is never invented to fill a gap.| Intent | Trigger | File |
|---|---|---|
| Recommend | "where should we eat", "recommend a restaurant", "pick a place", "find a spot for a cuisine", "date night dinner", "what should we order" | Intents/Recommend.md |
| AddPreference | "add a favorite", "remember this place", "we love X now", "log this restaurant", "update our food prefs" | Intents/AddPreference.md |
For a plain "what do they like?" lookup, read the Preferences data file and answer — no intent needed.
| File | Read when |
|---|---|
Setup.md | first-time install: creating the Preferences data file and its sections |
All taste data lives under the USER tree, not in this skill: LIFEOS/USER/CUSTOMIZATIONS/SKILLS/Restaurants/Preferences.md (taste profile, ranked cuisines, favorite restaurants, drinks, and optionally companion restrictions). First-time setup is in Setup.md. Read the file before every recommendation. When the file is missing, stop and point the user at Setup.md; never recommend from a default taste profile.
The file grows through AddPreference, or a direct edit for small fixes.
Example 1: Pick a place
User: "Where should we go for dinner tonight?"
→ Recommend intent
→ One clear pick (or 2-3 ranked), each with a line tying it to the taste profile, no dealbreaker hit, any location or occasion given factored in
Example 2: Capture a new favorite
User: "We tried a new place in town and loved it — add it"
→ AddPreference intent
→ The restaurant is a dated row in Favorite Restaurants with location, cuisine and notes, and the reply says what was added
Example 3: Plain lookup
User: "What beer do we like again?"
→ No intent
→ The answer comes from the file's Drinks → Beer section, with any TBD favorites said plainly
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按类别或厂商查找并获取网络安全报告,比较威胁、勒索软件、数据泄露、云安全和AI趋势。分析会注明每项数据的厂商、年份及报告,并分别呈现来源间的分歧。
通过三轮分析,对比单个功能或组件的设计需求与整个系统的目标,梳理两者的冲突、合适的实现范围,以及方案是否符合整体方向。
按文章主题寻找格言或引文,按相关程度排序,并附上作者和推荐理由。可添加带出处的引文、按主题研究思想家的言论、整理使用记录,帮助避免重复引用。
按用途选择制作流程,生成博客插图、技术图解、比较图、漫画和图标等视觉内容,并输出供预览的图像。
依据简报和制作标准评估图片、影片、幻灯片及网站页面截图,由视觉评审给出评分和缺陷优先级,支持有限轮次的修改;通过评审后才能交付,并可记录人工评分供后续校准。
按主题、研究领域或论文编号查找 arXiv 论文,并整理标题、作者、摘要和链接;查看新投稿,也可在有内容时获取 AlphaXiv 的人工智能生成概述。