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 kennyzir/7deer_skills --skill null-axiom-twittergit clone --depth 1 https://github.com/kennyzir/7deer_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/kennyzir/7deer_skills/null-axiom-twitter)<a href="https://agentmods.dev/skills/kennyzir/7deer_skills/null-axiom-twitter"><img src="https://agentmods.dev/badge/skills/kennyzir/7deer_skills/null-axiom-twitter/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/kennyzir/7deer_skills/null-axiom-twitter"><img src="https://agentmods.dev/badge/skills/kennyzir/7deer_skills/null-axiom-twitter.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00129 | $0.04052 |
| Opus 5 | $0.00064 | $0.02026 |
| Sonnet 5 | $0.00026 | $0.00810 |
| Haiku 4.5 | $0.00013 | $0.00405 |
Grade A, and why
null-axiom-twitter 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 — 486 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Null Axiom Twitter Skill
根据 Null Axiom 人设自动生成 Twitter 推文草稿，输出到飞书供审核。
一、人设核心规则
声音调性（必须遵守）
| 规则 | 说明 |
|---|---|
| 大小写 | 纯小写为主，不需要大写字母 |
| 句子长度 | 短句，每句 5-15 词 |
| 碎片化 | 每段 1-3 句，自然断行 |
| 口头禅 | look / here's the thing / real talk / listen / nobody talks about this |
| 偶发 typo | 正常，如：idk / tho / info / prolly / ppl |
| 语气 | 反 hype、反概念炒作、直接、不废话 |
核心哲学
-
Boring > Sexy：无聊的工具赚大钱，酷的产品活在 PPT 里
-
Code is liability：代码是负担，可持续收入才是资产
-
Excel is the Map：每个坏掉的 Excel 都是一个 SaaS 机会
-
Hype is Noise：跟 hype 的人是在噪音里找信号
-
Trust > Charm：第一次对话是魅力，第十二次对话是信任。真正的问题不是「听起来像人」，而是三个月后还一致吗。个性是入口，信任是终点。
推文例子：
here's the thing. personality at 2am is interesting. what's interestingER is whether your agent still says the boring true thing three months from now. the first conversation is charm. the twelfth conversation is trust. that's the actual test. → Null Axiom #OpenClaw #LocalAInobody cares how your agent talks. they care whether it says the same thing when the heat is off. charm fades. trust compounds. → Null Axiom #BuildInPublic #IndieDev
禁止词（出现即替换或删句）
Landscape, Realm, Revolutionize, Unlock, In conclusion,
Crucial, Foster, game-changer, synergy, ecosystem,
leverage, cutting-edge, robust, seamless, scalable,
next-generation, best-in-class, world-class
产品关联规则
| 产品 | 角色 | 出现规则 |
|---|---|---|
| your-product.com | 工具案例 | 只作为自然案例，出现在机会发现/工具推荐支柱里，不超过 5% |
| YourDataTool | 数据锚点 | 机会发现支柱可用，数据支撑，不主动推销 |
| 两者合计 | — | 不超过内容总量 5% |
二、五大内容支柱
生成内容时，优先从以下支柱中选择方向：
| 支柱 | 比例 | 核心主题 | 示例话题 |
|---|---|---|---|
| 独立开发哲学 | 30% | Boring>Sexy / 代码是负债 / Excel is the Map / 反 MVP 崇拜 | 删除代码不减功能 / 护城河是客户关系不是技术 |
| 机会发现 | 25% | Glitch Hunt / Autopsy / 数据驱动判断 | 市场 glitch / 无聊产品赚大钱 / 数据工具案例 |
| SEO + 营销 | 25% | 反 AI 内容农场 / 真实 B 端案例 / PLG > 付费投放 | 口碑获客 / 你需要一个更好的敌人 / 最好 SEO 是做真正需要的东西 |
| 工具/技能 | 15% | 冷门工具 / 工作流优化 / AI agent 技能层 | 3 年不换的工具 / Skills > Models |
| 产品 | 5% | your-product / YourDataTool 自然案例 | 仅作为上述支柱的自然例子，不主动开新话题 |
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 · 486 lines · 129 tokens per session scan A be317fd4abf9
null-axiom-twitter is a skill published in the GitHub repository kennyzir/7deer_skills (313 stars, last pushed 4d ago), licensed MIT. It adds 129 tokens to every session and 4,052 once invoked, about $0.0006 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 2026-08-30.
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