TGINSIGHT SIMILAR POSTS
Source channel @olddriverGDstudy · Post #98 · Sep 12
#舔逼三步 第一步（初舔B） 亲阴唇时要把女性的明唇尽量吸吮到嘴里，用舌头轻扫轻舔，女性会觉得阴唇部位特别有点痒，她很想你亲更多位置，亲得更广些，别理她们，你亲你的就行了，你可以趁着她们正享受着的时候，轻轻的咬一下她的阴唇她肯定会“啊”的一下惊叫，身子抽动一下，在她还没来得及说话时，你快速把嘴唇整个贴在她的阴道口，这种做法可以让女性一下子感觉到整个阴部很温暖很舒服， 刚才的那声“啊”还没叫完就变成“噢”的一轻呼了。这时开始应该动手了，你应该用大拇指轻轻的将她的阴唇向两边分开蛋出女性的阴道口，用舌头在阴道口周围打转绕圈，时轻时重，时而整个嘴唇贴上。 这时候你可以稍为停下不亲阴道口，而是用湿润的舌尖轻轻撩几下她的阴蒂，把她的感觉从明蒂里撩拨起来，女性会轻叫几下，然后你再回去亲她的明道口和阴唇。 第二步（挑逗期） 不要在这时候再亲她的阴蒂，要让女性半吊在那种感觉里，而且男性要开始从女性的会阴处向阴蒂方向往上轻舔，慢点，舌头到达阴道口时左右拨动，把阴唇一边拨开一边向上继续舔，一点点向阴蒂部位接近。就是偏不要亲到阴蒂那，差不多到的时候你用舌尖轻轻的，越轻越好，只是在她的阴蒂上轻扫轻点一下（舌头要含点口水) ，随即反方向按上述亲法朝阴道口部位舔去。这样会把女性给急死的，她一急，自然就兴奋了。亲阴道口时，舌头长的男性可以尝试把舌头插入女性的明道内搅动。舌头宽厚的男性可以把舌头由阴道口自下往上扫动。 第三步（猛攻） 现在开始可以集中精力夺取“珍珠”了，清把舌头上移至女性的阴蒂处集中精力。女性的阴蒂是非常敏感的，如果你太大力舔动，她的痛感多过快感，就没意思了。亲吻阴蒂要注意几点，舌头一定要湿、轻、尖，一定要保持舌头湿润，亲舔阴蒂时一定要轻，要用舌尖来舔。进攻明蒂要用“点、挑、拨、压、搅”五字诀。点，是指用舌尖轻点轻触女性的阴蒂顶端;挑，是指舌头从阴蒂下面向上挑动；拔，是用舌头左右拨动女性的阴蒂；压，是时不时用舌头压女性的阴蒂，把它稍为压下即可；搅，是当你含住女性的阴蒂时用舌头在明蒂四周搅动。进攻明蒂要用“点、挑、拨、压、视员五字决，点，是指用舌尖轻点控用女性的阴蒂顶端;挑，是指舌头从阴蒂下面向上挑动; 拔，是用舌头左右拨动女性的阴蒂;压，是时不时用活头压女性的阴蒂，把它稍为压下即可， 搅，是当你含住女性的阴蒂时用舌头在阴蒂四周搅动。你可以感觉到她们的阴蒂下似乎有点筋会在跳动，这在你含着女性的阴蒂时感觉非常明显。不要随便中断女性的感觉，动作要平均，因为你突然而快节奏的动作很容易让女性到达高潮。觉得可以给对方高潮时，应该用整个嘴唇含住女性的阴蒂部位， 上嘴唇压在阴蒂上方的阴毛根部，下嘴唇左石分开女性的阴唇，尽量贴近阴道口,用口含住女性的阴蒂(留点空间)，让女性觉得她的阴蒂是飘浮在你的嘴里的，用五字决发动进攻。让对方猛的一阵抽搐，看着她快到时，轻轻一放，然后马上又含上去。 (评论区附图解) 标签：#知识，#技巧
Search: #graph
@Isaiahsystem · Post #1203 · 06/30/2024, 07:23 AM
Related Subreddits丨Reddit 探索神器 https://anvaka.github.io/sayit/?query=Nietzsche 最近发现的爆炸网站，Reddit 相关论坛探索，Reddit 关键词图谱。它能根据你给出的任意论坛名字或关键词，编织出整个论坛与之相关的子板图谱，与之关联。点击图谱按钮，再点击弹出的侧边栏子板名字，即可跳转。 网站提到这种图谱关系生成由「发布到此 Subreddit 的用户也发布过的其它板块」决定，并通过 Jaccard Similarity（衡量两个集合相似度的指标）来最终确定板块相似度。 Reddit 作为我 RSS 常驻网站之一，挖掘得比较少，这个网站可以好好用用。它类似前面用过的 music map 以及各种论文网站图谱，详情见下面 refs. 相关链接 1 可视化图谱 2 搜索引擎终极索引 #search#graph#tools
@githubtrending · Post #14632 · 04/25/2025, 12:00 PM
#python#agents#graph#llms#rag Graphiti helps AI systems handle constantly changing information by building real-time knowledge graphs that track relationships and historical data, allowing them to integrate user interactions, business data, and external sources seamlessly. Unlike traditional methods, it updates information instantly without needing full recomputations, enabling precise historical queries and efficient hybrid searches. This helps AI applications stay context-aware, automate tasks effectively, and manage complex, evolving data with minimal delay. https://github.com/getzep/graphiti
@thedevs · Post #1384 · 02/01/2019, 08:02 PM
Data structures 101: graphs, a visual introduction for beginners. #article#tutorial#data#ds#graph @thedevs https://kutt.it/4S6HBr
@tsukassadrive · Post #3010 · 01/08/2026, 02:55 AM
#twitter#animals#dogs#science#physics#graph#mongolia
@cosplayuploadtest2 · Post #102714 · 03/23/2025, 03:36 AM
Title: Iori_Sagara_相楽伊織,_GIRLS_graph._デジタル写真集_「泡沫の宵夢」_Set.02 Authors: #None Tags: #None#Iori_Sagara_相楽伊織#Nogizaka46_乃木坂46#デジタル写真集#Iori#Sagara#相楽伊織#GIRLS#graph#デジタル写真集 #「泡沫の宵夢」 #Set #02 recommendation: None TelegraphLinks:page-0-32
@cosplayuploadtest2 · Post #102682 · 03/23/2025, 03:34 AM
Title: Iori_Sagara_相楽伊織,_GIRLS_graph._デジタル写真集_「泡沫の宵夢」_Set.01 Authors: #None Tags: #None#Iori_Sagara_相楽伊織#Nogizaka46_乃木坂46#デジタル写真集#Iori#Sagara#相楽伊織#GIRLS#graph#デジタル写真集 #「泡沫の宵夢」 #Set #01 recommendation: None TelegraphLinks:page-0-28
@githubtrending · Post #14649 · 04/30/2025, 01:00 PM
#typescript#csv#diagrams#graph#json#nextjs#react#tool#visualization#yaml JSON Crack is a free, open-source tool that instantly turns complex JSON, YAML, CSV, XML, or TOML data into clear, interactive graphs, making it easier to explore and understand your information. It lets you convert between formats, validate data, generate code (like TypeScript interfaces), run queries, and export visuals as images—all while keeping your data private since everything processes locally on your device[1][2][5]. https://github.com/AykutSarac/jsoncrack.com
@githubtrending · Post #14878 · 06/28/2025, 02:00 PM
#cplusplus#arduino#cansat#csv#embedded#graph#ground_station#iot#microcontroller#network#projects#qt#serial#serial_studio Serial Studio is a free, easy-to-use tool that lets you visualize real-time data from devices like microcontrollers via serial ports, Bluetooth, or network connections. It works on Windows, macOS, and Linux, and offers customizable dashboards with various widgets to monitor sensor data, debug info, or telemetry. You can quickly plot data, export it as CSV for analysis, and even use advanced features like checksum validation and JavaScript data processing. It supports hobbyists, educators, and professionals by simplifying data monitoring and debugging, saving you time and effort in understanding your device’s output. Pro versions add commercial use and extra features[1][4][5]. https://github.com/Serial-Studio/Serial-Studio
@githubtrending · Post #15518 · 02/24/2026, 11:30 AM
#rust#ai#ai_ocr#attention_mechanism#gnn#gnn_model#gnns#graph#graph_neural_networks#llm_inference#low_latency#mincut#neo4j#ocr#onnx#rust#vector#wasm RuVector is a free, open-source vector database that gets smarter with every query. Unlike static databases, it learns from usage via GNN layers, runs LLMs locally with no cloud costs, supports graph queries like Neo4j, scales freely across nodes, and deploys as a single self-booting file (125ms startup). Run with `npx ruvector`. You benefit from faster, more accurate AI search that improves automatically, zero operating costs, full offline/privacy control, and easy scaling—perfect for RAG, agents, or edge apps without vendor lock-in. https://github.com/ruvnet/ruvector