Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/WhiteGiverMa/meme-skillsnpx agentmods add skills/whitegiverma/meme-skills/meme-skill-creatorWrote 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-skill-creator)<a href="https://agentmods.dev/skills/whitegiverma/meme-skills/meme-skill-creator"><img src="https://agentmods.dev/badge/skills/whitegiverma/meme-skills/meme-skill-creator/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-skill-creator"><img src="https://agentmods.dev/badge/skills/whitegiverma/meme-skills/meme-skill-creator.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 | $0.00161 | $0.02242 |
| Opus 5 | $0.00081 | $0.01121 |
| Sonnet 5 | $0.00032 | $0.00448 |
| Haiku 4.5 | $0.00016 | $0.00224 |
Grade A, and why
meme-skill-creator 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 — 169 lines — stays where its author put it; the contents beside it link to each section on GitHub.
梗技能创建器
此 skill 用于在 meme-skills 知识库中创建新的热梗 skill，实现梗知识的持久化记忆与复用。
触发判断
明确触发（用户主动要求）
用户说出以下类型的表述时，立即进入创建流程：
- 「做个 skill」「创建 skill」「收录这个梗」
- 「记一下这个梗」「保存一下」「存个档」
- 「这个梗也加进去吧」
主动提议（Agent 判断）
以下条件全部满足时，Agent 应主动提议创建 skill：
- 当前讨论的梗不在已有
meme-*skill 覆盖范围内 - 该梗已有足够的网络传播量（可搜到多个独立来源）
- 用户在对话中对此梗表现出反复提及或深入讨论
提议话术示例：
「这个梗资料挺丰富的，要不要我收录到 meme-skills 里？下次再聊到就能直接调用了。」
不要频繁提议（同一会话中最多提议 2 次）。
创建流程
触发 → 命名 → 搜索 → 验证 → 起草(incoming/) → 复核 → 移入(skills/) → 索引 → 提交
步骤 1：命名
确定 skill 名称 meme-<拼音>：
- 拼音全小写，连字符分隔，不带声调
- 如果梗有多个名称，选最通用的一个
- 示例：奶龙 →
meme-nailong，你已急哭 →meme-niyijiku
向用户确认名称后再继续。
步骤 2：搜索（跨来源交叉验证）
对梗的以下维度分别搜索，每个维度至少命中 2 个独立来源：
| 维度 | 搜索目标 | 问题示例 |
|---|---|---|
| 起源 | 创作者、最初平台、最早出现时间 | "XX梗 起源 最早" |
| 传播 | 出圈节点、关键传播事件 | "XX梗 为什么火了" |
| 含义 | 字面义、引申义、使用场景 | "XX梗 是什么意思" |
| 演变 | 变体、衍生、语义漂移 | "XX梗 演变 新含义" |
推荐搜索来源：
- 百度百科、萌娘百科（基础事实）
- 腾讯新闻、虎嗅、澎湃新闻（传播分析）
- 单词乎、游侠手游（梗百科类网站）
- B站/抖音相关视频标题与简介（当前热度）
步骤 3：验证
创建 skill 前，必须确认：
- 梗的起源人物/账号有至少 2 个独立来源交叉确认
- 时间线关键节点有来源支撑
- 衍生概念有实际案例引用
- 没有将「网友玩梗编造」的内容当作事实写入
如果某个关键事实只有一个来源，标注为「待验证」或降低确信度表述。
步骤 4：起草 SKILL.md
先在
incoming/meme-<name>/SKILL.md创建草稿，待复核通过后再移入skills/。
参考 references/meme-template.md 模板，按以下结构编写：
- 概述（2-3 句话，给出梗的快照）
- 起源（创作者、时间、平台、原始内容、出圈过程）
- 核心特征/含义（形式、含义、使用场景）
- 发展经过/传播时间线（表格形式，关键时间节点）
- 衍生概念（变体、二次创作、相关梗）
- 文化分析（社会心理、时代情绪）
- Agent 使用指南（如何识别与回应、注意事项）
- 参考资料（每条带可访问 URL）
编写原则：
- LLM 训练数据已知的基础信息从简，重点覆盖训练截止后的新演变
- Agent 使用指南必须具体——给出「当用户说 X，TA 想表达 Y，你应该回应 Z」的模式
- 语言：正文用中文，引用 URL 保持原始格式
如果梗的信息极少（搜不到 2 个独立来源），不要直接拒绝——先看用户意图：是要贡献到仓库，还是自己留着用？见下方「仓库标准 vs 本地自用」。
步骤 5：复核、移入正式目录并更新索引
- 复核：按步骤 3 的 checklist 逐项确认无误
- 移入：将
incoming/meme-<name>/整个目录移动到skills/下 - 更新索引：移入完成后，更新以下文件：
README.md：在「已收录梗」表格中新增一行：
| [meme-xxx](./skills/meme-xxx/SKILL.md) | 梗中文名 | 分类 | 关键词1、关键词2、关键词3 |
AGENTS.md：在 skills/ 目录结构中新增条目：
│ ├── meme-xxx/ # 梗中文名
│ │ └── SKILL.md
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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 · 169 lines · 161 tokens per session scan A 6e701c327e9d
meme-skill-creator is a skill published in the GitHub repository WhiteGiverMa/meme-skills (7 stars, last pushed 3mo ago), licensed MIT. It adds 161 tokens to every session and 2,242 once invoked, about $0.0008 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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