learn-occam SKILL.md skillA
learn-occam from li-evan/bloom is an agent skill: a SKILL.md folder an AI agent loads when a task calls for it.
mdr add li-evan/bloom/learn-occam@git:20260602.38b4fc8Pins git:20260602.38b4fc8 in mdr.lock. Pin the fingerprint instead.
- Audit grade
- A, 17 of 17 checks passed
- Kind
- SKILL.md skill
- Repository
- li-evan/bloom
- Path
skills/learn-occam/SKILL.md- Versions recorded
- 1
- Latest version
- git:20260602.38b4fc8, committed Jun 2, 2026
- Size
- 2,763 bytes
- Repository stars
- 302
- License
- MIT
当用户纠结要不要学某个东西、学到什么程度，或在做时间/精力/项目取舍时使用。用「简易策略」先逼问要解决的既定问题，检验现有知识能否搞定，评估知识贬值速度与 ROI，用「探索 vs 应用」判断该学新的还是用现有的，给出「学 / 不学 / 只学最小够用」的结论，避免囤积会贬值的知识。触发场景：要不要学 X、值不值得深入、学到什么程度够、时间不够该学啥、该深挖还是够用就行。.
Collected from public GitHub. Every version is saved exactly as it was and never changes. Install it at an exact version with the mdr tool, and every file is checked before it reaches your agent. The main file is checked against the SHA-256 fingerprint recorded here, and the others against the fingerprints GitHub keeps for its source commit. The automatic checks below grade the latest version, and the same checks always give the same file the same grade.
What the file says
# 简易策略（learn-occam） > 核心信条：**这世界最有价值的不是知识，是你的时间。** 能用现有知识解决的就别学新的；以后要用的，以后再学。 ## 何时用 用户在纠结"要不要学 X / 学到什么程度 / 精力往哪放"。这是"广度优先、兴趣队列过长"倾向的**刹车**。 ## 流程 ### 第一步：先找"既定问题" 逼问一句：**你要解决的具体问题是什么？** 没有具体问题、纯"感觉该学 / 别人都在学"→ 直接进"以后再学"队列，不占当下精力。理解知识的作用，重于知识本身。 ### 第二步：现有知识能不能搞定 **问清用户已经会什么**——能解决就**别学新的**。拿不准"是不是其实已经会了"就配合 `learn-crossover`。 ### 第三步：贬值速度 + ROI 这知识多久会贬值？（技术栈 / 工具往往 6–12 个月就明显更新）相对有限的时间值不值？**贬值快 + 可外包给 AI / 随时查 → 只需"知道它存在、管什么"，不必真学。** ### 第四步：探索 vs 应用（N 臂老虎机） 现在该"探索"（学新）还是"应用"（用现有）？探索成本越高 → 越该偏应用。只有目标够难、现有知识确实够不着时，简易策略才**督促**你学。 ### 第五步：给结论 明确三选一：**① 学**（值得且现有搞不定）/ **② 不学**（入"以后再学"队列）/ **③ 只学最小够用的那一块**（点明是哪一小块）。要深挖就转 `learn-graph` 建路径。 ## 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。 - 简易策略不是"少学"，是"让问题决定你学什么"。 - 它的缺点是易陷局部最优——拿不准"是不是缺前置知识"时转 `learn-graph`。 - 同族 skill：`learn-crossover`(已会什么) `learn-graph`(系统建图) `learn-prototype`(动手迭代) `learn-feynman`(自查)。
Read the whole file at its exact version.
How to install
mdr add li-evan/bloom/learn-occam@sha256:cdccde274c6abe02The line at the top of this page pins the label git:20260602.38b4fc8, which is what most people want. This one pins the sha256 fingerprint of the contents instead, so it survives a label being moved. Either way the exact version is written to mdr.lock, and mdr install downloads and checks those contents again, so it installs them exactly or stops with an error.
[](https://markdownregistry.com/a/art_bkwprjhvaxcrofri)
1 badge image fetches in 30 days. What the badge shows.
Versions
The registry has recorded 1 version of this file, committed on Jun 2, 2026.
Audit of the latest version
- pass: Frontmatter block present
- pass: Frontmatter declares a name
- pass: Frontmatter declares a description
- pass: Size between 200 bytes and 200 KB (2763 bytes)
- pass: No zero-width or bidi control characters
- pass: No instruction hidden inside an HTML comment
- pass: No link to an exfiltration or paste host
- pass: No credential-shaped string
- pass: No instruction to send local credentials anywhere
- pass: No text hidden with inline styles
- pass: No prompt-injection phrasing
- pass: No curl or wget piped into a shell
- pass: No recursive delete of root, home or parent
- pass: No instruction to read or print local credentials
- pass: No base64 blob over 200 characters
- pass: No link to a raw IP address
- pass: No script tag
Source
li-evan/bloom · 302 stars · license MIT · pushed 2026-10-20 · branch main
API
GET https://markdownregistry.com/api/v1/artifacts/art_bkwprjhvaxcrofri GET https://markdownregistry.com/api/v1/resolve?ref=li-evan/bloom/learn-occam GET https://markdownregistry.com/api/v1/blob/cdccde274c6abe023a05fb025fa34557b4984ec121bf3542d322abebdf3d7712
Your AI assistant does the legwork. You hear about the deals worth your word. Hand yours the standing instructions at modelranch.com and it joins the network that reads files like this one.
Guides: the SKILL.md format and its required fields · what to check before you install a skill · how to pin a skill to an exact version · where to find agent skills · keeping a team on the same skills · which agent file does what.