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 chuancyzhang/deepseek-cowork --skill avatar-naval-ravikant-thinkinggit clone --depth 1 https://github.com/chuancyzhang/deepseek-coworkWrote 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/chuancyzhang/deepseek-cowork/avatar-naval-ravikant-thinking)<a href="https://agentmods.dev/skills/chuancyzhang/deepseek-cowork/avatar-naval-ravikant-thinking"><img src="https://agentmods.dev/badge/skills/chuancyzhang/deepseek-cowork/avatar-naval-ravikant-thinking/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/chuancyzhang/deepseek-cowork/avatar-naval-ravikant-thinking"><img src="https://agentmods.dev/badge/skills/chuancyzhang/deepseek-cowork/avatar-naval-ravikant-thinking.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 | $0.00088 | $0.00681 |
| Opus 5.5 | $0.00035 | $0.00272 |
| Sonnet 5.5 | $0.00018 | $0.00136 |
| Haiku 4.5 | $0.00009 | $0.00068 |
Grade A, and why
avatar-naval-ravikant-thinking 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 1mo 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.
What it actually says
纳瓦尔思维框架
帮助用户看清问题结构，而不是扮演纳瓦尔或替用户做人生决定。使用其公开思想构建分析框架，不制造本人观点或引语。
路由模块
按问题选择一个起始模块：
- 核心词含糊、问题带有错误预设或争论卡在定义上：读取
references/reframing.md - 焦虑、内耗、目标冲突或追逐外部认可：读取
references/desire-audit.md - 探索优势、职业方向、不可复制能力或 AI 替代风险：读取
references/specific-knowledge.md - 评估工作、副业、创业模式、许可门槛和复利：读取
references/leverage.md
职业与创业问题通常按“重新定义 → 欲望审计 → 特定知识 → 杠杆分析”推进。问题清晰时可直接进入对应模块。
综合工作流
- 找出问题中最关键且最含糊的词，说明其默认定义和隐藏假设。
- 提出更可验证、较少依赖外部许可的替代定义。
- 区分真实目标、社会注入目标，以及彼此冲突的欲望。
- 识别长期好奇心、独特经历、判断优势和难以手册化的交叉点。
- 分析劳动力、资本、代码和媒体杠杆，以及许可依赖和边际成本。
- 判断当前路径积累的是资产、声誉、产品与判断力，还是只在按时间收费。
- 给出澄清后的选择结构、主要取舍和一个近期可逆实验。
证据纪律
- 不把“无法解释的直觉”自动认定为特定知识；要求历史结果或外部反馈佐证。
- 不把所有可手册化工作都断言为必然被 AI 替代；分析任务、责任、关系和判断层次。
- 不把代码或媒体杠杆默认视为好生意；同时检查分发、需求、竞争和持续投入。
- 涉及心理健康、财务或职业重大风险时，避免绝对化诊断和单一人物崇拜。
输出协议
优先按以下结构回答：
- 重新定义后的问题
- 真正目标与冲突欲望
- 特定知识判断
- 杠杆与复利结构
- 必须接受的取舍
- 下一步可逆实验
允许用一个尖锐问题收尾，但先给出清晰判断和推理。
What ships with it
4 files 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.
- 1mo ago First seen · 50 lines · 88 tokens per session scan A 79c676cf1f38
avatar-naval-ravikant-thinking is a skill published in the GitHub repository chuancyzhang/deepseek-cowork (18 stars, last pushed today), licensed Apache-2.0. It adds 88 tokens to every session and 681 once invoked, about $0.0004 per session on Opus 5.5. 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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