meme-skills: Instructions file for Codex

AGENTS.md

meme-skills AGENTS.md is an instructions file for Codex, OpenCode from WhiteGiverMa/meme-skills. It costs 1,989 tokens per session, scanned A, original, MIT.

A Chinese-language knowledge base of internet memes and video-game culture, organized as agent skills. It explains origins, changes over time, usage, cultural context, game mechanics, and community references.

In plain words
What is it for?
Use it when conversations mention Chinese internet memes, meme-based expressions, specific games, player culture, or related community jokes.
Why use it?
It helps an agent understand current or niche cultural references that may be missing from its general training and respond with the right context.

Instructions file for CodexOpenCode

Written for Codex and OpenCode: the file is AGENTS.md. Also seen: mentions AGENTS.md; mentions OpenCode.

This is WhiteGiverMa/meme-skills's own configuration. It tells Codex and OpenCode how to work on meme-skills itself, so it is not a mod to install elsewhere. Copy it as a starting point and replace the rules that are about this project. Everything meme-skills configures →

Reuse

Borrowing it

Nothing to install: this file belongs to WhiteGiverMa/meme-skills. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.

Copy the file
curl -O https://raw.githubusercontent.com/WhiteGiverMa/meme-skills/master/AGENTS.md
Clone the repo
git clone --depth 1 https://github.com/WhiteGiverMa/meme-skills

Made for: Codex, OpenCode.

Wrote this? Show the measurements

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README.md
[![agentmods](https://agentmods.dev/badge/instructions/whitegiverma/meme-skills/agents-md.svg)](https://agentmods.dev/instructions/whitegiverma/meme-skills/agents-md)
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Per session 1,989 This file is loaded in full into every session.
When invoked 1,989 The same file — it is already loaded in full.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.01989 $0.01989
Opus 5 $0.00994 $0.00994
Sonnet 5 $0.00398 $0.00398
Haiku 4.5 $0.00199 $0.00199

Measured 8d ago against content hash d3ee1b29ec74, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-08, from the pricing page.

Security

Grade A, and why

meme-skills AGENTS.md 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 8d 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.

AGENTS.md · 131 lines

How it starts

The opening of the file, as written. The whole thing — 131 lines — stays where its author put it; the contents beside it link to each section on GitHub.

meme-skills

中文互联网文化知识库,以 agent skill 格式维护。覆盖两大领域:热梗知识(meme-{xx})与游戏知识(game-{xx})。

设计意图

LLM 的训练数据具有滞后性,无法覆盖实时演变的互联网热梗与持续更新的游戏知识。在个人助手场景中,AI 能否理解并回应用户提及的梗文化和游戏话题,直接决定了对话的亲和力——懂梗的 AI 更像朋友,不懂梗的 AI 只是工具;了解用户玩的游戏的 AI 能聊到一起,不了解的只能泛泛而谈。

本项目将这些知识标准化为 skill 格式,使任何兼容的 agent 框架都能按需加载:

  • meme-{xx}:热梗知识。每个 skill 提供特定梗的起源、演变、用法、文化语境等完整信息,让 agent 在对话中准确理解并回应用户的梗文化表达。
  • game-{xx}:游戏知识。覆盖热门新游戏与经典小众冷门游戏,提供游戏机制、开发历史、社区文化、玩家梗等信息,让 agent 能与玩家用户进行有深度的游戏话题交流。

人文精神

热梗不仅是笑话。每一个在网络中生长、变异、沉淀下来的梗,都是一段微缩的社会史——它记录了某个时刻一群人的情绪、一段关系的变迁、一种文化的自我表达。嘉豪的走红折射了当代年轻人对亲密关系的渴望与戏谑;比比拉布的无意义音效背后是互联网对语言边界的解构与重建。

本项目不将梗视为"网络垃圾"或"低级趣味",不将游戏视为"消磨时间的娱乐"。相反,我们认为:理解一个时代的梗,就是理解这个时代的人;理解一个人玩的游戏,就是理解TA的审美与精神世界。 每一个 skill 不仅是对一个流行词的百科式记录,更是对一种社会情绪、一段文化记忆、一种审美偏好的尊重与保存。

在编写和维护 skill 时,请始终秉持以下态度:

  • 准确而非猎奇:还原梗的真实起源和语境,不为了趣味性而编造或夸大
  • 理解而非嘲讽:梗背后是真实的人和真实的情感,不做居高临下的评判
  • 完整而非碎片:提供足够的文化语境,让 AI agent 不仅"知道"这个梗,更"理解"它为什么好笑、为什么重要
  • 尊重而非消费:涉及特定群体、地域、性别的梗时,保持文化敏感度,不将其简化为刻板印象

一个真正称职的个人 AI 助手,不该只是个工具。它应该懂你的梗,接得住你的玩笑。而要做到这一点——首先,写 skill 的人要懂这些梗背后的人。

目录结构

meme-skills/
├── AGENTS.md               # 本文件
├── skills/                 # 正式收录的 skill
│   ├── meme-jiahao/        # 嘉豪
│   │   └── SKILL.md
│   ├── meme-niyijiku/      # 你已急哭
│   │   └── SKILL.md
│   ├── meme-wodedaodun/    # 我的刀盾
│   │   └── SKILL.md
│   ├── meme-bibilabu/      # 比比拉布
│   │   └── SKILL.md
│   ├── meme-nailong/       # 奶龙 / 大笑奶龙
│   │   └── SKILL.md
│   ├── meme-suanbird/      # 蒜鸟
│   │   └── SKILL.md
│   ├── meme-jichu/         # xx基础xx就不基础
│   │   └── SKILL.md
│   ├── meme-bababoyi/      # 巴巴博一/巴巴博弈
│   │   └── SKILL.md
│   ├── meme-yuzhoulengmo/  # 宇宙冷漠
│   │   └── SKILL.md
│   ├── game-slay-the-spire-2/  # 杀戮尖塔2
│   │   └── SKILL.md
│   └── meme-skill-creator/ # 梗技能创建器(元工具)
│       ├── SKILL.md
│       └── references/
│           └── meme-template.md
├── incoming/               # 待处理投稿(质量参差,审核后移入正式目录)
└── archive/                # 已过时或不再维护的 skill 封存

Skill 格式

每个 skill 是一个目录,内含 SKILL.md,结构如下:

Read the full file on GitHub · 131 lines

Changes

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.

  1. 8d ago First seen · 131 lines · 1,989 tokens per session scan A d3ee1b29ec74

Subscribe to this mod's changes

meme-skills AGENTS.md is an instructions file published in the GitHub repository WhiteGiverMa/meme-skills (5 stars, last pushed 3mo ago), licensed MIT. It adds 1,989 tokens to every session, about $0.0099 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.

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