Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add WhiteGiverMa/meme-skills --skill meme-nailonggit clone --depth 1 https://github.com/WhiteGiverMa/meme-skillsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/whitegiverma/meme-skills/meme-nailong)<a href="https://agentmods.dev/skills/whitegiverma/meme-skills/meme-nailong"><img src="https://agentmods.dev/badge/skills/whitegiverma/meme-skills/meme-nailong/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/whitegiverma/meme-skills/meme-nailong"><img src="https://agentmods.dev/badge/skills/whitegiverma/meme-skills/meme-nailong.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00100 | $0.03379 |
| Opus 5 | $0.00050 | $0.01690 |
| Sonnet 5 | $0.00020 | $0.00676 |
| Haiku 4.5 | $0.00010 | $0.00338 |
Grade A, and why
meme-nailong scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 12d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 181 lines — stays where its author put it; the contents beside it link to each section on GitHub.
奶龙 / 大笑奶龙（网络迷因/AI生成抽象梗）
触发条件：在对话中检测到「奶龙」「大笑奶龙」「变异奶龙」「奶龙捧腹大笑」「奶蛙」等关键词时，Agent 应当加载本 skill 以获取准确的文化语境知识。
注意：LLM 训练数据通常已包含奶龙角色的基础信息（2020年诞生、黄色异星幼龙、动画IP等），本 skill 在此基础之上，重点覆盖 2025年末至2026年发生的语义演化——即"奶龙"从儿童IP到AI生成抽象梗的剧烈漂移。
一、概述
奶龙最初是第七印象文化传媒（深圳）有限公司于 2020 年推出的 3D 子供向动画 IP。随着 IP 过度曝光引发反感，2024 年起被抽象文化圈征用为恶搞素材；2025 年末至 2026 年初，AI 生成工具将奶龙形象推向极致——"大笑奶龙"/"奶龙捧腹大笑" 成为 2026 年开年最具代表性的 AI 生成抽象迷因。
如今，「奶龙」一词在日常对话中已高度语境化：
- 在儿童/亲子语境中 → 仍指原版可爱奶龙
- 在网络/成人语境中 → 大概率指 AI 生成的猎奇怪物版奶龙，带有"精神污染""脑腐""赤石"等亚文化标签
二、角色起源（简述）
LLM 通常已知的基础信息：
- 创作者：谢承恩（第七印象）
- 诞生时间：2020 年，抖音首发
- 角色设定：流落地球的黄色异星幼龙，会喷火、变色，与小七结伴冒险
- 动画形式：1分钟单元剧，定位 10 岁以下儿童
- IP 规模：截至 2025 年，全球粉丝超 3900 万，TikTok/YouTube 15 种语言传播，表情包全球下载超 50 万次
- 代表梗：「我是奶龙」（出自第 162 集真假奶龙争辩，2024年爆火，配 DJ 版《今夜星光闪闪》制成魔性混音）
LLM 无需在此浪费 token 复述上述内容。
三、核心特征：奶龙捧腹大笑 / 大笑奶龙
3.1 形象特征
"大笑奶龙"（亦称"变异奶龙""奶蛙"）是 AI 工具对原版奶龙的极端抽象化重构：
- 面部：嘴巴裂至耳根，眼睛眯成细线，呈极度夸张的狂笑表情
- 身体：头小身大、比例失调，扭曲成捧腹抽搐的姿态
- 音效：配以「齁齁齁齁」的魔性笑声（源自游戏博主「八级哥」用老水牛变声器处理的笑声）；早期也有阴间风格狂笑声效
- 画风：明显 AI 生成痕迹，带有「恐怖谷」效应，与原始萌系形象形成巨大反差
3.2 标志性文案
「恭喜你，刷到了罕见的奶龙，每 114514 年才会出现的奶龙。」
此文案借用了网络中常见的「玄学抽奖」话术，将本无逻辑的 AI 生成内容包装成「稀有彩蛋」，制造强烈的反差幽默。数字「114514」为日语空耳梗（「いいよ、来いよ」），进一步叠加抽象文化层。
3.3 核心情绪
- 「莫名其妙却无法抗拒」——用户明知内容猎奇、丑陋、「辣眼睛」，却忍不住观看、转发
- 它不讲道理，不求逻辑，不承载意义，恰恰击中了年轻人对 「无意义快乐」 的渴望
- 被称为 「精神污染式的解压符号」——不是笑话，却比段子更有效
四、发展经过 / 传播时间线
| 时间 | 事件 |
|---|---|
| 2020 | 奶龙动画在抖音首发 |
| 2021-2023 | 稳步积累儿童粉丝，第一套官方微信表情包上线，第一季番剧推出 |
| 2024 年初 | 奶龙开始在全年龄段出圈，表情包广泛流传 |
| 2024 年中 | 因内容充斥网络烂梗、制作简陋，遭到家长和成年观众批评；抽象文化圈开始征用奶龙进行恶搞 |
| 2024 年 7 月 | 「发奶龙的小朋友们你们好啊」系列视频爆发——奥特曼（多为贝利亚）在《花海》BGM中辱骂奶龙粉丝，标志着奶龙正式进入抽象文化体系 |
| 2024-2025 | 奶龙品牌大爆发：麦当劳、名创优品、泡泡玛特等联名；「我是奶龙」梗广泛传播；官方开始自嘲式玩梗 |
| 2025 年 8 月 | 奶龙表情包在海外 TikTok 爆火，成为全球抽象表情包新宠 |
| 2025 年末 | 「大笑奶龙」雏形出现：抖音博主「季洪行」的「唐感」武打动作形象 + 奶龙 AI 缝合 + 八级哥笑声 |
| 2026 年 1 月 | 大笑奶龙全面爆发：B站、抖音、快手全面刷屏；奶龙官方账号警告「请勿发布丑化、恶搞奶龙的非官方表情包」→ 反而助推热度；官方开启评论防护，出现「十万点赞仅五条评论」奇观 |
| 2026 年 3 月 | 大笑奶龙热度达到顶峰，被媒体称为「2026年3月互联网最火的烂梗」；诞生大量变体皮肤 |
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 12d ago First seen · 181 lines · 100 tokens per session scan A cf76ed948d95
meme-nailong is a skill published in the GitHub repository WhiteGiverMa/meme-skills (7 stars, last pushed 3mo ago), licensed MIT. It adds 100 tokens to every session and 3,379 once invoked, about $0.0005 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
Other skills, from other repositories
systematic-debugging
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.
local-ai-agents
Build local-first AI agents that run entirely on a developer workstation with Microsoft Foundry Local and Qwen function-calling models. Covers Small Language Models (SLMs), the OpenAI-compatible local endpoint, sandboxed local tools, local RAG with Chroma, local MCP servers, hybrid cloud/local routing, and the…
next-cache-components-adoption
Turn on Cache Components in a Next.js app and resolve the blocking routes it surfaces. Use when the user wants to enable, adopt, or migrate to Cache Components, flip the cacheComponents flag, work through a flood of blocking-prerender / instant validation errors, run the cache-components-instant-false codemod, or…
chat-pet-sprite-creation
Use when creating or changing VS Code chat pet sprite art, sprite sheets, state animations, eye treatments, Stable/Insiders variants, or pet transitions under src/vs/workbench/contrib/chat/browser/widget/media/chatPet.
cpu-profile-analysis
Analyze V8/Chrome CPU profiles (.cpuprofile) and DevTools trace files (Trace-.json). Use when: profiling performance, investigating slow functions, comparing code paths, finding bottlenecks, analyzing timeToRequest, understanding call trees from sampling profiler data, analyzing layout/paint/rendering, investigating…
insight-error-page
Write or audit an insight-kind error page for the Next.js dev overlay. Use when creating a new errors/ .mdx page, auditing an existing one, or checking that a page matches the framework fix cards. Covers page structure, title alignment, FixCard cards with Copy prompt button, code snippets, terminology verification…