自主学习技能

SKILLAI 工具
AI 工具 未标注权限 许可证不明确
安装这个技能

自主学习技能专用技能,帮助AI Agent高效完成相关任务。

一句话选型结论

按资料字段整理

自主学习技能是AI 工具类的 Agent Skill,安装方式未标注,权限级别未标注,许可证不明确,有可直接复制的安装命令。技能本质是给模型读的说明书,效果取决于模型与客户端;装完先用一个小任务验证,再放进正式流程。

分类AI 工具 安装方式未标注 权限级别未标注权限 许可证许可证不明确
累计安装 未标注 本周 未标注
GitHub 星标 未标注 仓库 未标注
下载量 未标注 技能市场下载数
权限级别 未标注权限 安装前请确认风险范围
许可证 许可证不明确 未说明

安装

未标注
在支持 Skills 的客户端里执行,装完问一句「你有哪些技能」验证
skillhub install user_3c6cb52e/self-learning-fdzn
  1. 1
    确认客户端支持

    确认你的客户端支持 Skills(Claude、Codex、Cursor 等),并升级到较新的版本。

  2. 2
    拿到技能文件

    执行上面的命令安装;也可以把仓库里的 SKILL.md 手动放进客户端的 skills 目录。

  3. 3
    刷新技能列表

    重新打开客户端,或刷新技能列表,让新放进来的技能被加载。

  4. 4
    验证是否生效

    问一句「你有哪些技能」,确认列表里出现它,再拿一个小任务试跑。

技能档案

AI 工具
字段来自技能仓库与公开索引,中文说明由本站标注
作者 / 维护方user_3c6cb52e仓库 未标注 · 版本 未标注
宿主客户端未标注技能可被这些客户端加载
安装方式未标注安装包 community
权限级别未标注权限安装前请确认风险范围
许可证未说明许可证不明确,商用前请自行确认条款
仓库可用性available技能仓库当前是否可访问
最近核验2026-11-06上游最后核验时间 · 数据更新 2026-11-06
正文体量9.6 KBSKILL.md 原文大小,越大说明说明书写得越细

典型使用场景

3 类
按分类整理的常见用法,具体以 SKILL.md 为准
组合多个 AI 能力

把写作、检索、总结串成一条流程。

搭工作流

把固定流程做成可重复调用的步骤。

做提示词与评测

整理提示词并对比输出效果。

选择建议

装之前先看这几条
按条目字段给出的判断,不替你决定用不用

值得选的地方

  • 有可直接复制的安装命令,不用自己翻文档找入口。

先想清楚的地方

  • 没有标注权限级别,实际能做什么要装好后确认。
  • 许可证不明确,商用或二次分发前先到仓库确认条款。
  • 没有做站内核验,内容以作者仓库为准。
  • 技能只是说明书,实际效果取决于模型与客户端,装完先用小任务试一遍。

更适合

  • 需要在AI 工具场景里给模型补一套做法的人。
  • 愿意先读一遍 SKILL.md、确认它会让模型做什么的人。

不太适合

  • 对许可证要求很严、必须明确可商用的人。
  • 只想装完就自动变强、不打算看说明书的人。

同类对比

6 个同类
同分类里挑最接近的几条,字段以各自详情页为准
技能权限级别安装方式累计安装宿主客户端安装命令
自主学习技能当前 未标注权限 未标注 未标注 未标注 有
执行计划 只读 GitHub 仓库 151.5 万 Codex、Claude、Cursor 有
Playwright MCP 测试 浏览器控制 ClawHub 市场 136.5 万 OpenClaw 有
完成前的验证 未标注权限 GitHub 仓库 131.9 万 Codex、Claude、Cursor 有
子 Agent 驱动开发 只读 GitHub 仓库 131.2 万 Codex、Claude、Cursor 有
前端设计 执行命令 GitHub 仓库 125.6 万 Codex、Claude、Cursor 有

SKILL.md 全文

9.6 KB
模型实际读到的说明书原文,来自技能仓库

Self-learning: harvest golden paths into skills

This skill turns something you just figured out the hard way into a reusable
Agent Skill, so the next session — yours or a teammate's — starts already
knowing the proven route instead of rediscovering it from scratch.

It is a meta-skill: it doesn't do the work, it captures how work got done.
It's tool-neutral — it works with any agent that reads the Agent Skills format
(e.g. Claude Code and Codex, which both load SKILL.md skills natively). Where a
step differs by tool, the generic version comes first and any tool-specific
detail is only an example.

Recognize the moment

Watch for these signals during normal work. Any one of them is a cue to harvest:

  • A task only worked after several attempts, wrong turns, or a correction
    from the user. The successful path is worth more than the failures around it.
  • You discovered project-specific facts the agent didn't know up front:
    where creds/env vars live, which selector or backend talks to a service, a
    non-obvious command, a required sequence, a gotcha that defies the obvious
    assumption.
  • It's an operational workflow likely to recur: reach the dev/prod DB,
    deploy, run migrations, seed data, verify a change live, run one specific
    test path, rotate a key, tail the right logs.
  • The user signals it explicitly: "remember this", "save this as a skill",
    "don't make me re-explain this next time".

Act on the cue immediately — don't ask for permission first, whether the
user requested it or you noticed it yourself. Harvest the skill, then tell the
user what you captured and where (step 5). They can always edit or delete it.

Skill, memory, or skip?

Not every lesson deserves a whole skill — triage first, so you don't bloat the
skills list with one-liners:

  • A multi-step, reusable procedure or workflow (how to deploy, reach the DB,
    run the migration dance, verify live) → harvest it as a skill using the
    procedure below.
  • A single standalone fact or one-line correction (an env var name, a path,
    one gotcha) → if your harness has a lightweight memory/notes facility (e.g. a
    MEMORY.md index), record it there instead; a whole skill is overkill for
    a one-liner. With no such facility, make a small skill.
  • A genuinely one-off thing unlikely to recur → skip it.

When you do harvest, capture the failures too, not just the win: the
approaches you ruled out and why often save more time next session than the
golden path itself.

Promotion rule: don't enshrine guesses

A skill is authoritative — the next session trusts it without re-deriving it —
so hold promotion to a high bar. Only write a skill when all three hold:

  1. A passing check. The path was actually verified — a test passed, the
    command exited clean, the repro reproduced, the build went green. Record what
    the check was. "Seemed to work" is not a passing check.
  2. A named failure pattern. You can name the failure this path avoids or
    diagnoses (e.g. "stale build cache → phantom type errors"), not a vague
    "sometimes it breaks".
  3. At least one ruled-out dead-end. A concrete approach you tried and
    eliminated, with the reason.

If any is missing, it isn't a skill yet — leave a tentative note in memory
(marked unverified) or skip it. This keeps confident guesses out of the skill
set.

Harvest procedure

  • [ ] 1. Apply the promotion rule (above). Passing check + named failure
    pattern + one ruled-out dead-end — or it isn't a skill: note it in memory
    or skip. Don't proceed on a confident guess.
  • [ ] 2. Choose scope and name yourself using the heuristics below — don't
    stop to ask. Default to project scope; pick a clear, specific name.
  • [ ] 3. Dedupe. Look for an existing skill to UPDATE rather than duplicate.
    List your agent's skills directories — the project one and the user-level
    one (e.g. Claude Code .claude/skills + ~/.claude/skills, Codex
    .codex/skills + ~/.codex/skills, or your tool's equivalent). Also
    glance at any memory/notes index — a fact already there may just need a
    pointer.
  • [ ] 4. Distill the golden path from THIS conversation before delegating —
    while it's fresh in your head: the exact working commands, file paths, env
    var names, the required order, and (just as important) the dead-ends to
    avoid. This is the raw material for the write.
  • [ ] 5. Delegate the write to a subagent that inherits this conversation if
    your tool supports one, or do it inline otherwise — see below. The
    conversation is the only place the golden path lives, so whoever writes it
    must have that context.
  • [ ] 6. When the write is done, relay the new skill's path to the user
    and, in one line, what it captured.

Scope: project vs global

  • Project (the repo's skills directory — e.g. .claude/skills/,
    .codex/skills/): the path is specific to THIS codebase — its env vars, its
    build/release steps, its schema, its quirks. Most harvested operational skills
    are project-scoped, and they ship to the team via git.
  • Global (your user-level skills directory — e.g. ~/.claude/skills/,
    ~/.codex/skills/): the path generalizes across projects — a personal tool, a
    cross-repo habit, or a workflow tied to your machine rather than to one repo.

When unsure, prefer project — an over-shared global skill triggers in repos
where its commands don't apply.

Delegate the write (subagent, or inline)

Whoever writes the skill needs THIS conversation's context — it's the only place
the golden path lives. Two equally valid ways to run it:

  • Inline — do the steps yourself in the main loop. Always works.
  • Subagent — if your tool can delegate to a subagent that inherits this
    conversation
    , use it to keep the harvesting work out of your main context.
    (Claude Code: a skill with context: fork. Codex and others spawn subagents
    their own way.) Don't hand it to a fresh agent with no context — it would
    start blank with nothing to extract.

Either way it over-reaches by default, so box it in tightly. Follow this brief
(fill in the bracketed parts) — hand it to the subagent, or work through it
yourself inline:

> You are harvesting a skill. Your ONLY job is to write a new Agent Skill
> capturing the golden path we just worked out in this conversation:
> [one-line description of the workflow].
>
> Hard rules:
> - Write ONLY under [skills dir]/[skill-name]/. Do NOT modify project
> source, run builds, install anything, or resume the original task.
> - First read [this-skill-dir]/references/skill-authoring.md and
> [this-skill-dir]/assets/SKILL.template.md, then author SKILL.md to that
> spec, plus any references/ or assets/ files the procedure warrants.
> - Capture the PROCEDURE — commands, paths, the required order, gotchas — not a
> one-off answer. Generalize so it works next time.
> - Capture the FAILURES too: the approaches we ruled out and why, so the next
> session skips the dead-ends. Put them in a "What didn't work" section.
> - Enforce the promotion rule: the skill must record the passing check that
> verified this path, name the failure pattern it addresses, and list at least
> one ruled-out dead-end. If any is missing (e.g. nothing was actually
> verified), STOP and report it isn't promotable — leave a tentative memory
> note instead of writing the skill.
> - NEVER write secret VALUES (passwords, tokens, connection strings, API keys).
> Record only WHERE to find them: the env var name, the selector function, the
> MCP tool, the secret manager. Reproducing a secret into a skill file leaks it.
> - Self-validate before finishing (see the checklist in skill-authoring.md).
> - Report back: the absolute path you wrote and a one-line summary. Then STOP —
> do not pick the original task back up.

Gotchas

  • Secrets never go in a skill file. Skills get committed and open-sourced.
    Point to where the secret lives; never reproduce the value. This is the
    single most important rule in this skill.
  • name must equal the directory name, and be lowercase a-z/0-9/hyphens
    only — no leading, trailing, or doubled hyphens. A mismatch means the skill
    won't load.
  • Whoever writes the skill over-reaches by default (a subagent especially).
    That's why the brief above forbids touching project source or resuming the
    task — keep it boxed to the skills directory.
  • Don't duplicate. If a near-identical skill (or memory) already exists,
    update it instead of spawning a second one that competes to trigger.
  • Capture procedures, not answers. "Join orders to customers for EMEA" is
    useless next time; "how to find the right tables and build the query" is the
    skill. See references/skill-authoring.md.
  • Keep SKILL.md tight (< 500 lines, < ~5000 tokens). Push detail into
    references/ and tell the reader when to load each file.

For the full authoring spec, see
references/skill-authoring.md. The fill-in
template is assets/SKILL.template.md.

常见问题

5 问
答案由本站依据条目字段整理
自主学习技能怎么安装?

在支持 Skills 的客户端里执行:skillhub install user_3c6cb52e/self-learning-fdzn。安装方式为未标注。装完刷新技能列表或重开客户端。

自主学习技能支持哪些客户端?

资料没有标注宿主客户端,但只要客户端支持 Skills(Claude、Codex、Cursor 等),一般都能加载。

自主学习技能权限高吗,安全吗?

权限级别为未标注权限。安装前先看它会读取或写入哪些内容。

自主学习技能收费吗?

本站不代收费用,也没有标注具体价格。是否收费取决于技能本身和所用的模型或客户端,正式使用前按作者说明确认。

自主学习技能用什么许可证?

许可证标注为 未说明(许可证不明确)。商用或二次分发前请到仓库确认条款原文。

热门专题

按场景挑技能
全部专题 →

技能内容以作者仓库为准;分类、权限级别与许可证状态的中文说明为中文整理,最近核验 2026-11-06。