learn-prototype

A coaching method for learning by building a small working prototype first, then finding its flaws, testing improvements, and repeating the cycle. TDD is not required; the focus is on learning through successive attempts.

In plain words
What is it for?
Use it when building, researching, or improving something, especially when you do not know where to start. It guides you to inspect weaknesses, form improvement ideas, test them, and record what you learned.
Why use it?
It helps when planning and research have replaced actually making something. Starting with a rough version exposes real problems that can guide the next improvement.

Skill for Claude CodeCodex

Install

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.

agentmods
npx agentmods add skills/li-evan/bloom/learn-prototype
Any agent
npx skills add Li-Evan/Bloom --skill learn-prototype
Clone the repo
git clone --depth 1 https://github.com/Li-Evan/Bloom

Made for: Claude Code, Codex.

Per session 144 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 815 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5 $0.00144 $0.00815
Opus 5 $0.00072 $0.00407
Sonnet 5 $0.00029 $0.00163
Haiku 4.5 $0.00014 $0.00081

Measured 2d ago against content hash a4f55f2f0f2b, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

learn-prototype 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 2d 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.

skills/learn-prototype/SKILL.md · 44 lines

What it actually says

改良主义学习法(learn-prototype)

核心信条:洞察缺陷 > 如何优化 > 最终答案。 试图洞察缺陷、自己提出问题,永远不要害怕问题多简单。学习要努力,但要做有效的努力

何时用

用户要动手做 / 研究一个东西,或想把某个已有产出改得更好。这是"重输入、轻输出"短板的解药——逼用户从输入切到输出。

流程(教练模式:引导用户做和提问,不替他做)

第一步:先做最垃圾的原型

别追求完美,先有一个能跑 / 能看的最小版本。卡在"还没准备好"就是没进改良主义。

第二步:引导用户自己洞察缺陷

关键且不能代劳:问他"这哪里不好?为什么不好?"哪怕问题很简单。把"自己提问"的动作交给用户——这是能力泛化的来源。你可以追问、补他没看到的角度,但先让他提

第三步:提改良假说 → 实践 → 检验

针对缺陷提一个改良策略(视为假说,可对可错),动手改,看效果。错了也有用——错误暴露后,下次自动规避这个方向。

第四步:迭代 / 推翻

循环②③,直到无法再优化 → 推翻重做。允许"不正确但有用的版本"——能解决当前问题就够了,不必一开始追求完美架构。

第五步:沉淀方法论

把"这次怎么从 A 改到 B"的方法本身记一笔(每个解决的问题都成为后续的法则)。改得越多,方法越泛化,提问越准。

注意

⚠️ 铁律·只用确证的已会知识:判断用户「已经会什么」只能用他确证学过的知识(亲口确认或可靠背景);严禁把「正在讲的材料 / 文章作者背景 / 对话里别人的知识」当成用户会的。拿不准 → 直接问「⚠️ 你学过 ___ 吗?」,绝不替他假设。

  • 别替用户提问、别替他做——那会废掉这个 skill 的核心价值。引导 > 代劳。
  • 提问命中要害需要基本素质,但素质靠迭代泛化,所以"先开始"比"先够格"重要。
  • 缺前置知识改不动 → 转 learn-graph;想确认是否真懂 → 转 learn-feynman
  • 同族 skill:learn-occam learn-crossover learn-graph learn-feynman
Changes

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.

  1. 2d ago First seen · 44 lines · 144 tokens per session scan A a4f55f2f0f2b

Subscribe to this mod's changes

learn-prototype is a skill published in the GitHub repository Li-Evan/Bloom (248 stars, last pushed 2mo ago), licensed MIT. It adds 144 tokens to every session and 815 once invoked, about $0.0007 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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