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 agentmods add commands/xu-xiang/everything-claude-code-zh/learngit clone --depth 1 https://github.com/xu-xiang/everything-claude-code-zhWrote 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/commands/xu-xiang/everything-claude-code-zh/learn)<a href="https://agentmods.dev/commands/xu-xiang/everything-claude-code-zh/learn"><img src="https://agentmods.dev/badge/commands/xu-xiang/everything-claude-code-zh/learn.svg" alt="Measured on agentmods" 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 | $0.00011 | $0.00437 |
| Opus 5 | $0.00005 | $0.00218 |
| Sonnet 5 | $0.00002 | $0.00087 |
| Haiku 4.5 | $0.00001 | $0.00044 |
Grade A, and why
learn scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 4d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
What it actually says
学习命令 (Learn Command)
从当前会话（Session）中提取模式（Patterns）、学习心得（Learnings）和可复用的见解：$ARGUMENTS
你的任务
分析对话和代码变更以提取：
- 发现的模式 (Patterns discovered) - 重复出现的解决方案或方法
- 应用的最佳实践 (Best practices applied) - 效果良好的技术
- 应避免的错误 (Mistakes to avoid) - 遇到的问题及其解决方案
- 可复用代码段 (Reusable snippets) - 值得保存的代码模式
输出格式
发现的模式 (Patterns Discovered)
模式：[名称]
- 上下文（Context）：何时使用此模式
- 实现（Implementation）：如何应用它
- 示例（Example）：代码片段
应用的最佳实践 (Best Practices Applied)
- [实践名称]
- 为什么有效
- 何时应用
应避免的错误 (Mistakes to Avoid)
- [错误描述]
- 出了什么问题
- 如何防止
建议的技能更新 (Suggested Skill Updates)
如果发现的模式具有重要意义，请建议更新以下文件：
skills/coding-standards/SKILL.mdskills/[domain]/SKILL.mdrules/[category].md
本能格式 (Instinct Format - 用于 continuous-learning-v2)
{
"trigger": "[触发此学习的情况]",
"action": "[该做什么]",
"confidence": 0.7,
"source": "session-extraction",
"timestamp": "[ISO 时间戳]"
}
提示 (TIP)：在长会话期间定期运行 /learn，以便在上下文压缩（Context Compaction）之前捕获见解。
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.
- 4d ago First seen · 62 lines · 11 tokens per session scan A f7e3697f4ad6
learn is a command published in the GitHub repository xu-xiang/everything-claude-code-zh (1,927 stars, last pushed 6mo ago), licensed MIT. It adds 11 tokens to every session and 437 once invoked, about $0.0001 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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