Technical Analyst
tradermonty/claude-trading-skills
This skill should be used when analyzing weekly price charts for stocks, stock indices, cryptocurrencies, or forex pairs.
Chinese-language method for sharpening judgment on direction-setting decisions, drawn from Naval Ravikant's ideas: rebuild reasoning from basics and apply mental models.
SKILL.md written in Chinese; this summary is our English description.
Install Judgment Training
$ npx skills add kangarooking/cangjie-skill --skill judgment-training -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install kangarooking/cangjie-skill judgment-training --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/kangarooking/cangjie-skill.git skills-src && mkdir -p .claude/skills && cp -r skills-src/books/naval-almanack-skill/judgment-training .claude/skills/judgment-training && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "judgment-training" agent skill from https://github.com/kangarooking/cangjie-skill/tree/main/books/naval-almanack-skill/judgment-training into .claude/skills/judgment-training/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "judgment-training", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/kangarooking/cangjie-skill/tree/main/books/naval-almanack-skill/judgment-trainingType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add kangarooking/cangjie-skill --skill judgment-training -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install kangarooking/cangjie-skill judgment-training --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/kangarooking/cangjie-skill.git skills-src && mkdir -p .agents/skills && cp -r skills-src/books/naval-almanack-skill/judgment-training .agents/skills/judgment-training && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "judgment-training" agent skill from https://github.com/kangarooking/cangjie-skill/tree/main/books/naval-almanack-skill/judgment-training into .agents/skills/judgment-training/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "judgment-training", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add kangarooking/cangjie-skill --skill judgment-training -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install kangarooking/cangjie-skill judgment-training --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/kangarooking/cangjie-skill.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/books/naval-almanack-skill/judgment-training .cursor/skills/judgment-training && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "judgment-training" agent skill from https://github.com/kangarooking/cangjie-skill/tree/main/books/naval-almanack-skill/judgment-training into .cursor/skills/judgment-training/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "judgment-training", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/kangarooking/cangjie-skill.git --path books/naval-almanack-skill/judgment-training--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add kangarooking/cangjie-skill --skill judgment-training -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install kangarooking/cangjie-skill judgment-training --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/kangarooking/cangjie-skill.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/books/naval-almanack-skill/judgment-training .gemini/skills/judgment-training && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "judgment-training" agent skill from https://github.com/kangarooking/cangjie-skill/tree/main/books/naval-almanack-skill/judgment-training into .gemini/skills/judgment-training/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "judgment-training", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install kangarooking/cangjie-skill judgment-trainingInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add kangarooking/cangjie-skill --skill judgment-training -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/kangarooking/cangjie-skill.git skills-src && mkdir -p .github/skills && cp -r skills-src/books/naval-almanack-skill/judgment-training .github/skills/judgment-training && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "judgment-training" agent skill from https://github.com/kangarooking/cangjie-skill/tree/main/books/naval-almanack-skill/judgment-training into .github/skills/judgment-training/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "judgment-training", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add kangarooking/cangjie-skill --skill judgment-training -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install kangarooking/cangjie-skill judgment-training --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/kangarooking/cangjie-skill.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/books/naval-almanack-skill/judgment-training .opencode/skills/judgment-training && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "judgment-training" agent skill from https://github.com/kangarooking/cangjie-skill/tree/main/books/naval-almanack-skill/judgment-training into .opencode/skills/judgment-training/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "judgment-training", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
Facts
- Skill name
judgment-training- GitHub stars
- 11k
- Token cost
- ~686 tokens
- SKILL.md length
- 154 words
- Files
- 3
- Skills in repo
- 22
- Repo updated
- First seen
- Licence
- MIT
At a glance
Chinese-language method for sharpening judgment on direction-setting decisions, drawn from Naval Ravikant's ideas: rebuild reasoning from basics and apply mental models.
- Works in 4 steps: 方向选择：「这件事该不该做/往哪走」 → 评估言论：「这个专家的说法靠谱吗/是真懂还是包装」 → 学习新领域：「怎么快速建立对陌生领域的判断力」 → …
- Deciding whether a project or direction is worth pursuing
- SKILL.md covers R — 原文 (Reading), I — 方法论骨架 (Interpretation), A1 — 书中的应用 (Past Application) and A2 — 触发场景 (Future Trigger) ★, plus 4 more sections
- Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
What it does
The skill treats judgment, the ability to foresee the long-term consequences of actions, as worth more than hard work. It offers training paths: rebuild ideas from fundamentals, since real understanding means being able to derive a concept; learn foundational disciplines such as math and microeconomics; collect mental models like compounding, principal-agent problems and falsifiability; and leave a regular blank space for thinking.
Execution has four steps: decide whether the question is a high-stakes direction call or a low-stakes execution choice, reduce the core assumptions to what you can explain from scratch and mark the rest unknown, test the conclusion against one or two mental models, and reserve at least one meeting-free day each week. It is not for tasks needing immediate steps or simple lookups, and it notes the author's blind spots, including little room for emotion and intuition. Test prompts and results ship in the folder.
When your agent uses it
- Deciding whether a project or direction is worth pursuing
- Judging whether an expert's claim is credible or just packaged
- Building judgment quickly in an unfamiliar field
Example prompts
- “Help me judge whether moving our team to a new product direction is a sound bet.”
- “How can I tell if this advisor really understands the topic or is repeating jargon?”
Workflow steps
4 steps, taken from the first numbered list in SKILL.md.
- 方向选择：「这件事该不该做/往哪走」
- 评估言论：「这个专家的说法靠谱吗/是真懂还是包装」
- 学习新领域：「怎么快速建立对陌生领域的判断力」
- 决策前检查：「我的依据能不能从头推导」
What it can do on your machine
Read from SKILL.md and the folder at commit a28de55. It shows what the files ask for, not the result of running them.
Tool permissions
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Runs code
No scripts in the folder and no shell commands in SKILL.md.
From the folder's file list and the shell code blocks in SKILL.md.
Network
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Context cost
Judgment Training loads about 686 tokens when it runs. Until then it costs about 57 tokens; SKILL.md has 154 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
Safety
Auto-check passed
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.
SKILL.md
The full file from kangarooking/cangjie-skill at commit a28de55, republished under its MIT licence (© kangarooking). 154 words, ~686 tokens.
Download SKILL.mdSave it as
.claude/skills/judgment-training/SKILL.md (or your agent's skills folder). This skill also uses 2 other files; get the full folder from GitHub.- name
- judgment-training
- description
- 当用户需要做方向性判断、评估「该往哪走/这事靠谱吗」、或想提升决策能力时调用。 核心理念: 判断力(知道行为长期后果)比努力重要; 清晰思考=从基础学科重建推理; 收集心智模型(复利/委托代理/可证伪性/基础数学)。 不适用于: 需要立即执行的具体任务步骤。 Triggers: 判断力/方向/第一性原理/心智模型/思维模型/判断靠不靠谱/judgment/mental model/first principles
- source_book
- 《纳瓦尔宝典：财富与幸福指南》 纳瓦尔·拉维坎特
- source_chapter
- 第一章·财富 / 第二节 培养判断力 / 判断力与如何清晰地思考
- tags
- judgment, thinking, mental-models, learning
判断力训练
R — 原文 (Reading)
努力工作的价值真的被高估了。在现代经济中，努力工作不是那么重要。那什么被低估了？判断力。……真正聪明的思考者是思维清晰的思考者。他们理解非常非常基本的基础知识。……如果你不能根据需要从基础知识重新推导出概念，你会迷惑不解。你只是熟记而已。
— 纳瓦尔·拉维坎特, 《纳瓦尔宝典》 第一章·财富
I — 方法论骨架 (Interpretation)
判断力=知道行为长期后果并据此决策的能力，它是杠杆时代最重要的生产力—— 一个正确的决定可以赢过大量低效努力，而错误方向上的努力只会放大损失。 训练判断力有三个路径： ① 从基础重建——真正理解=能从头推导；高级概念无法推导就只是熟记；最聪明的人能把事情向小孩讲明白； ② 打牢基础学科——数学、微观经济学、可证伪性等是「严肃知识」，比背诵复杂概念更值钱； ③ 收集心智模型——复利、委托代理、黑天鹅、进化论等模型库，遇到新问题先找合适的模型套用； ④ 留出思考空白——每周至少一天不安排会议，伟大的想法只在你无聊之后出现。
A1 — 书中的应用 (Past Application)
案例 1: 费曼三页纸讲数学
- 问题: 如何判断一个人是否真的懂
- 方法论的使用: 费曼从数字→计算→初级微积分，用不打破的逻辑链串起来，不靠定义
- 结论: 能重建逻辑链才是真懂
- 结果: 「如果你无法向小孩子讲明白，那么你并不是真的知道」
案例 2: 每周留白思考
- 问题: 忙碌挤掉了思考时间
- 方法论的使用: 每周留一两天不安排会议
- 结论: 「只会在你感到无聊之后，才会有伟大的想法」
- 结果: 判断力和好想法随之而来
A2 — 触发场景 (Future Trigger) ★
用户会在什么情境下需要这个 skill?
- 方向选择：「这件事该不该做/往哪走」
- 评估言论：「这个专家的说法靠谱吗/是真懂还是包装」
- 学习新领域：「怎么快速建立对陌生领域的判断力」
- 决策前检查：「我的依据能不能从头推导」
语言信号
- "帮我判断一下/评估一下"
- "他怎么知道自己在说什么"
- "我想提升自己的判断力/思维模型"
- "how to think clearly / build judgment / is this credible"
与相邻 skill 的区分
- 与
decision-heuristics的区别: 本 skill 是底层能力训练；决策启发式是即用规则 - 与
rational-buddhism的区别: 本 skill 讲如何想清楚；理性佛教是验证一切主张的总标准
E — 可执行步骤 (Execution)
识别决策类型与后果尺度
- 完成标准: 明确这是方向判断（长期后果大）还是执行选择（后果小）；判断力优先投入前者
从基础重建核心假设
- 完成标准: 把问题拆到「我能从头解释」的公理层；解释不了的部分标为未知
- 判停条件: 若发现对方/自己满口大词但无法推导，标记为「不可信」，停止采信
套用已知心智模型
- 完成标准: 至少匹配 1–2 个模型（复利/委托代理/可证伪性/黑天鹅…）交叉检验结论
预留思考留白
- 完成标准: 每周安排 ≥1 天无会议/无任务，把最难的问题放进留白时段
B — 边界 (Boundary) ★
不要在以下情况使用此 skill
- 用户只需要快速执行步骤（先执行，再复盘判断）
- 信息查询类问题（查资料不需要完整推导）
作者在书中警告的失败模式
- 熟记≠理解: 「如果你不能根据需要从基础知识重新推导出概念，你会迷惑不解」
- 读错次序的博学: 虚假基础会过滤一切新想法
作者的盲点 / 时代局限
- 「基础学科优先」隐含理性人假设，未覆盖情绪/直觉在决策中的作用
- 判断力训练无法替代经验；作者自己也说判断力需要经验打底
容易混淆的邻近方法论
reading-metaskill: 阅读是判断力的供给管线
相关 skills (阶段 3 定稿)
- depends-on:
reading-metaskill（基础来自阅读） - composes-with:
decision-heuristics、principal-agent、rational-buddhism
审计信息
- 验证通过: V1 ✓ / V2 ✓ / V3 ✓ (v06)
- 测试通过率: 见 test-results.md
- 蒸馏时间: 2026-08-01
© kangarooking, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Files
SKILL.md and 2 other files in books/naval-almanack-skill/judgment-training of kangarooking/cangjie-skill.
- SKILL.md
- test-prompts.json
- test-results.md
Open the folder on GitHubat commit a28de55
Compare with similar skills
Judgment Training next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Judgment Training this skillkangarooking/cangjie-skill | 11k | — | ~686 | Automated safety check: Pass | MIT | |
| Technical Analysttradermonty/claude-trading-skills | 3k | 5 repos | ~4.6k | Automated safety check: Pass | MIT | |
| Creating Financial ModelsChen-zexi/open-ptc-agent | 730 | 4 repos | ~1.3k | Automated safety check: Pass | MIT | |
| Theme Detectortradermonty/claude-trading-skills | 3k | 2 repos | ~4.9k | Automated safety check: Pass | MIT | |
| Stock APIzhangxiangliang/stock-api | 2k | — | ~507 | Automated safety check: Pass | MIT | |
| Itr Walakaranb192/itr-wala | 871 | — | ~3.6k | Automated safety check: Pass | MIT |
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Categories
Questions about Judgment Training
What does Judgment Training do?
Chinese-language method for sharpening judgment on direction-setting decisions, drawn from Naval Ravikant's ideas: rebuild reasoning from basics and apply mental models. The skill treats judgment, the ability to foresee the long-term consequences of actions, as worth more than hard work. It offers training paths: rebuild ideas from fundamentals, since real understanding means being able to derive a concept; learn foundational disciplines such as math and microeconomics; collect mental models like compounding, principal-agent problems and falsifiability; and leave a regular blank space for thinking.
When should I use Judgment Training?
Judgment Training fits situations like: deciding whether a project or direction is worth pursuing; judging whether an expert's claim is credible or just packaged; building judgment quickly in an unfamiliar field.
How do I install Judgment Training in Claude Code?
Run `npx skills add kangarooking/cangjie-skill --skill judgment-training -a claude-code`. Or copy the skill folder (books/naval-almanack-skill/judgment-training in kangarooking/cangjie-skill) into .claude/skills/judgment-training in your project. Claude Code loads it when a task matches its description.
How do I install Judgment Training in Codex?
Run `npx skills add kangarooking/cangjie-skill --skill judgment-training -a codex`. Or copy the skill folder (books/naval-almanack-skill/judgment-training in kangarooking/cangjie-skill) into .agents/skills/judgment-training in your project. Codex loads it when a task matches its description.
Can I use Judgment Training in Cursor, Gemini CLI or GitHub Copilot?
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add kangarooking/cangjie-skill --skill judgment-training -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/judgment-training, .gemini/skills/judgment-training, .github/skills/judgment-training and .opencode/skills/judgment-training in your project.
What does Judgment Training need to run?
SKILL.md names no scripts, command-line tools or credentials: Judgment Training is instructions for the agent only.
Does Judgment Training access the network?
SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.
Is Judgment Training safe to install?
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.
What licence does Judgment Training use?
Judgment Training is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
How many tokens does Judgment Training use?
About 686 tokens (SKILL.md is roughly 2.7k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
What are the alternatives to Judgment Training?
Skills that share tags, products or a category with Judgment Training: Technical Analyst (tradermonty/claude-trading-skills, 3k stars), Creating Financial Models (Chen-zexi/open-ptc-agent, 730 stars), Theme Detector (tradermonty/claude-trading-skills, 3k stars) and Stock API (zhangxiangliang/stock-api, 2k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Judgment Training?
kangarooking (a GitHub user) maintains it in kangarooking/cangjie-skill, which has 10,988 GitHub stars. The repository holds 22 skills in this directory. The repository was last updated on October 2, 2026.
Source: kangarooking/cangjie-skill on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.