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 muyuhill/100books-to-skills --skill peakgit clone --depth 1 https://github.com/muyuhill/100books-to-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/muyuhill/100books-to-skills/peak)<a href="https://agentmods.dev/skills/muyuhill/100books-to-skills/peak"><img src="https://agentmods.dev/badge/skills/muyuhill/100books-to-skills/peak/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/muyuhill/100books-to-skills/peak"><img src="https://agentmods.dev/badge/skills/muyuhill/100books-to-skills/peak.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 | $0.00049 | $0.03214 |
| Opus 5 | $0.00024 | $0.01607 |
| Sonnet 5 | $0.00010 | $0.00643 |
| Haiku 4.5 | $0.00005 | $0.00321 |
Grade A, and why
刻意练习-peak 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 — 190 lines — stays where its author put it; the contents beside it link to each section on GitHub.
《刻意练习》— 天才不是天生的,是「练」出来的
一句话核心
「天才」不是基因彩票,而是正确方法 × 持续投入的产物。 安德斯·艾利克森(Anders Ericsson)通过三十年的科学研究证明:顶级表现的关键不是练习的「时长」,而是练习的「质量」——即刻意练习(Deliberate Practice)。
一、刻意练习 vs 天真练习:一万小时定律的致命误读
马尔科姆·格拉德威尔(Malcolm Gladwell)在《异类》中提出的「一万小时定律」让全世界记住了「一万小时」这个数字,但也造成了严重的误解:
| 天真练习(Naive Practice) | 刻意练习(Deliberate Practice) | |
|---|---|---|
| 目标 | 模糊,「我要变好」 | 具体,「今天要把第三小节的速度提到120bpm」 |
| 注意力 | 自动驾驶,边练边走神 | 极度专注,每一分钟都在主动思考 |
| 反馈 | 没有或很少 | 即时、具体、可操作 |
| 舒适区 | 重复已经会的东西 | 持续挑战刚好超出当前能力的边界 |
| 结果 | 平台期,十年如一日 | 持续进步,不断突破天花板 |
关键洞察:开了二十年车的老司机,驾驶水平未必比开了五年的司机高。因为开车很快变成「自动化」行为——一旦自动化,练习就停止了,剩下的只是重复。真正的练习发生在「自动化」之前的那段有意识的、不舒服的、需要全神贯注的时光里。
如何判断自己是在刻意练习还是天真练习? 问自己一个问题:「练完后我是感到精力充沛(因为巩固了已有能力),还是感到精神疲惫(因为一直在挑战边界)?」 如果是前者,你可能只是在享受练习,而不是在进步。
二、心理表征(Mental Representation):高手大脑里的「高清地图」
艾利克森发现,顶尖高手和普通人的核心差异在于**心理表征(Mental Representation)**的质量。
什么是心理表征? 它是大脑中与某个技能、概念或情境相对应的心理结构——可以理解为一张大脑里的「地图」。
- 国际象棋大师:看到棋盘上的残局,不是一个个孤立的棋子,而是瞬间识别出「这是1987年卡斯帕罗夫对卡尔波夫第三局的第27步后的局面」,并自动激活相关的策略模式。
- 小提琴家:在拉出一个音之前,大脑中已经「预听」到了这个音的准确音高、音色和情感表达,然后用手去匹配心中的那个声音。
- 程序员:看到一个需求,脑子里自动浮现出数据流、模块边界和潜在边界情况,而不是从零开始思考。
心理表征的三个层次:
- 模式识别:在复杂信息中快速识别有意义的模式(专家看 X 光片一眼发现病灶,新手只能看到灰色阴影)
- 信息组织:将大量信息组织成有意义的「组块」(chunk),从而突破工作记忆的限制(普通人一次记 7 个数字,高手通过组块化可以记几十个)
- 预判与规划:基于当前状态,在脑中模拟多种可能的未来走向并选择最优路径
核心循环:更好的心理表征 → 更有效的练习 → 更精细的心理表征。这是一个自我强化的良性循环。所以高手和普通人的差距不是线性缩小,而是指数级拉大。
三、刻意练习的四要素
艾利克森将刻意练习的操作框架提炼为四个必不可少的要素:
1. 明确的目标(Specific Goal)
不是「我要提高写作水平」,而是「我要在接下来两周内,每天写 500 字,并且确保每个段落的第一句话都能让读者想读第二句」。好的练习目标必须具体到可以验证——练完了你知道自己做到还是没有做到。
2. 极度专注(Intense Focus)
刻意练习在生理上是「不舒服」的。研究发现,顶尖音乐家每天只能进行 3-5 小时的高质量刻意练习,再多大脑就无法维持专注。质量远大于数量。如果你练着练着开始「自动驾驶」,要么停下来休息,要么加大难度让自己重新需要专注。
3. 即时反馈(Immediate Feedback)
没有反馈的练习是盲目的。反馈可以来自:
- 导师/教练(最佳)
- 客观指标(速度、准确率、分数)
- 自我监控(录音/录像回看自己的表现)
- 同行对比(和高手做同一道题后对比思路差异)
关键:反馈必须即时——间隔太久,大脑无法把反馈和当时的具体行为联系起来。
4. 走出舒适区(Beyond Comfort Zone)
如果练习让你感到舒服、流畅、游刃有余,那你没有在进步。刻意练习发生在「学习区」——刚好超出当前能力边界,你能磕磕绊绊地完成,但需要全力以赴。太简单(舒适区)= 零成长,太难(恐慌区)= 无效崩溃。
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 · 190 lines · 49 tokens per session scan A b446495bc847
刻意练习-peak is a skill published in the GitHub repository muyuhill/100books-to-skills (12 stars, last pushed 2mo ago), licensed MIT. It adds 49 tokens to every session and 3,214 once invoked, about $0.0002 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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