Agent skill

Flashcards

by open-octo in open-octo/octo-agent

生成和复习记忆卡片——Leitner 分桶间隔重复、按学科存储、自评式复习. An agent skill from open-octo/octo-agent.

Apache-2.0Auto-check passedEducation

Install Flashcards

skills CLI
$ npx skills add open-octo/octo-agent --skill flashcards -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install open-octo/octo-agent flashcards --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/open-octo/octo-agent.git skills-src && mkdir -p .claude/skills && cp -r skills-src/internal/skills/experts/flashcards .claude/skills/flashcards && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
flashcards
GitHub stars
125
Token cost
~870 tokens
SKILL.md length
166 words
Files
3
Skills in repo
40
Repo updated
First seen
Licence
Apache-2.0

At a glance

生成和复习记忆卡片——Leitner 分桶间隔重复、按学科存储、自评式复习. An agent skill from open-octo/octo-agent.

  • Works in 4 steps: 一个概念一张卡。 "光合作用的三个阶段"应该拆成3张卡,不是1张。 → 正面是问题,不是主题。 "光合作用"不好;"光合作用的三个阶段分别是 → 背面是规则/定义,不是一段话。 如果答案需要一整段才能说清楚,拆成 → …
  • 用户说帮我做闪卡抽认卡考我一下这些卡片我要背这些规则/单词/ 概念等需要记忆巩固的场景。不是完整的 SRS 系统——如果用户已经在用 Anki 之类 的工具,建议他们继续用;这是在对话里就想快速过一遍的轻量方案
  • SKILL.md covers 置信度纪律, 存储, 卡片结构 and 写卡规则, plus 3 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Flashcards is an agent skill from open-octo/octo-agent. 生成和复习记忆卡片——Leitner 分桶间隔重复、按学科存储、自评式复习。 Use when 用户说"帮我做闪卡""抽认卡""考我一下这些卡片""我要背这些规则/单词/ 概念"等需要记忆巩固的场景。不是完整的 SRS 系统——如果用户已经在用 Anki 之类 的工具,建议他们继续用;这是"在对话里就想快速过一遍"的轻量方案。

Its SKILL.md is about 870 tokens, which your agent loads only when the skill is triggered. The skill folder holds 2 other files (for example `PROVENANCE.md`).

It sits in Education, covering Study guides and flashcards. The repository describes itself as: Open-source, single-binary, self-hosted AI agent — your models and data stay on your machine. A coding agent on par with Claude Code and a personal assistant lighter than… The licence is Apache-2.0.

When your agent uses it

  • 用户说帮我做闪卡抽认卡考我一下这些卡片我要背这些规则/单词/ 概念等需要记忆巩固的场景。不是完整的 SRS 系统——如果用户已经在用 Anki 之类 的工具,建议他们继续用;这是在对话里就想快速过一遍的轻量方案
  • Tasks that involve Study guides and flashcards

Example prompts

  • “考我一下这些卡片”
  • “我要背这些规则/单词/ 概念”
  • “在对话里就想快速过一遍”
  • “/flashcards”

Workflow steps

4 steps, taken from the first numbered list in SKILL.md.

  1. 一个概念一张卡。 "光合作用的三个阶段"应该拆成3张卡,不是1张。
  2. 正面是问题,不是主题。 "光合作用"不好;"光合作用的三个阶段分别是
  3. 背面是规则/定义,不是一段话。 如果答案需要一整段才能说清楚,拆成
  4. 标注来源,方便复习时回去核对。

What it can do on your machine

Read from SKILL.md and the folder at commit fc1385f. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md (its code samples are markdown and yaml).

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Flashcards loads about 870 tokens when it runs. Until then it costs about 44 tokens; SKILL.md has 166 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~44
When it runs · the whole SKILL.md, loaded when a task matches
~870

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from open-octo/octo-agent at commit fc1385f, republished under its Apache-2.0 licence (© open-octo). 166 words, ~870 tokens.

Download SKILL.mdSave it as .claude/skills/flashcards/SKILL.md (or your agent's skills folder). This skill also uses 2 other files; get the full folder from GitHub.
name
flashcards
description
生成和复习记忆卡片——Leitner 分桶间隔重复、按学科存储、自评式复习。 Use when 用户说"帮我做闪卡""抽认卡""考我一下这些卡片""我要背这些规则/单词/ 概念"等需要记忆巩固的场景。不是完整的 SRS 系统——如果用户已经在用 Anki 之类 的工具,建议他们继续用;这是"在对话里就想快速过一遍"的轻量方案。
license
Apache-2.0 (adapted from anthropics/claude-for-legal, law-student/skills/flashcards; complete terms in LICENSE.txt)
metadata.origin
卡片结构、写卡规则、Leitner 分桶间隔表、生成/复习/统计模式, 改编自 anthropics/claude-for-legal 的 law-student/skills/flashcards (Apache-2.0);已移除该项目的法学院场景专属内容("这是真实法律问题请找律师"…

Skill: flashcards

大纲/笔记是用来综合理解的,记忆卡片是用来强记的。这个技能从用户提供的材料 (或在用户明确要求时,从模型知识)生成卡片,用轻量间隔重复复习,并追踪哪些 概念还没记牢。

不是完整的 SRS 系统。 只是简单的 Leitner 分桶。够用、不重——如果用户已经 习惯用 Anki 之类的专门工具,建议继续用那个;这个技能是给在对话里想快速过一遍 的场景用的。

置信度纪律

  • 从用户提供的材料(笔记、教材节选、课件)生成的卡片:内容来自材料本身, 可信。
  • 从模型知识(用户没给材料)生成的卡片:每张卡片如果陈述的规则不是模型有 把握的,标注 [待核实]。生成前先说清楚"这些卡是从我的知识生成的,不是 从你的材料,请自行核对"。
  • 如果某个领域模型把握不大,宁可少生成几张有把握的卡,也不要为了凑数瞎编。 8张靠谱的卡比20张里有5张错的要好。

存储

~/.octo/learning-data/flashcards/[学科]/cards.md

每个学科一个文件,跨会话持久(不受技能本身版本更新影响)。

卡片结构

markdown
### 卡片 [N]
**问:** [问题——一个概念一张卡]
**答:** [答案——规则/定义,一到两句话]
**来源:** [材料出处:笔记/教材页码/课堂日期]
**分桶:** new
**上次复习:** —
**下次复习:** [今天日期]
**备注:** [可选——易混淆点、例外情况、常见陷阱]

写卡规则

  1. 一个概念一张卡。 "光合作用的三个阶段"应该拆成3张卡,不是1张。
  2. 正面是问题,不是主题。 "光合作用"不好;"光合作用的三个阶段分别是 什么"好。
  3. 背面是规则/定义,不是一段话。 如果答案需要一整段才能说清楚,拆成 多张卡。
  4. 标注来源,方便复习时回去核对。

模式

Flag: --generate | --drill | --review | --stats | --session <n>(不带 flag 时先问用户要哪种)

--generate——生成卡片

输入: 学科/主题、来源材料(笔记路径、教材节选,或"就用我已有的大纲")、 可选的目标卡片数量(默认每次10-20张)。

按上面的卡片结构和写卡规则生成,写入 ~/.octo/learning-data/flashcards/ [学科]/cards.md(已有文件则增量追加,不要覆盖)。

如果是从模型知识生成的:每张卡的规则/答案是模型生成的,未经核实。用户 背下来之前,建议对照教材、笔记或权威来源核实一遍——背了一张错卡比没有这张 卡更糟。

--drill(默认)——复习

优先级:

  1. 下次复习 <= 今天 且分桶不是 mastered 的卡
  2. 还没复习过的新卡
  3. 如果没有到期卡也没有新卡:问用户要不要复习已经 mastered 的卡(防遗忘)

复习流程(逐张):

  1. 显示问题,等用户回答
  2. 用户回答(或输入"跳过"/"不会")
  3. 显示答案
  4. 用户自评:对 / 部分对 / 错 / 不会
  5. 按下表更新分桶和下次复习时间:
自评分桶变化下次复习
对升一档(new→learning→review→mastered)+1天(new) / +3天(learning) / +7天(review) / +21天(mastered)
部分对不变+1天
错降一档(review→learning;learning→new;new不变)今天+4小时
不会降一档今天+4小时
--review——浏览卡组

按分桶分组展示某学科的所有卡片。用于快速扫一眼卡组内容,或手动调整卡片。

--stats——进度快照

按学科统计:卡片总数、各分桶分布、今天到期数、本周已复习数。标出反复降到 new 两次以上的卡——这些是真正卡住的概念,值得用 weak-point-drill 或 向老师/教材再确认一遍,光靠卡片记不住的东西说明理解上有缺口。

--session <n>——聚焦N卡片小节

用户说"来5张合同法的卡"或类似需求时用这个模式。

  • 读取 ~/.octo/learning-data/study-plan.yaml(如果存在)里该学科的 session_history。
  • 优先级:之前答错的卡 > 到期卡 > 新卡。
  • 按 --drill 流程逐张跑完N张。
  • 小节结束后,把结果追加到 study-plan.yaml 的 session_history:
yaml
session_history:
  - date: 2026-05-08
    subject: 合同法
    type: flashcards
    n_cards: 5
    right: 3
    partial: 1
    wrong: 1
    stuck_topics: [不可抗力条款]

如果 study-plan.yaml 不存在,写到 ~/.octo/learning-data/session-history.yaml。

和其他技能的配合

  • outline-builder: 建好或扩充大纲之后,主动提议从新内容生成卡片。
  • weak-point-drill: 某张卡连续错2次以上,说明光靠卡片记不住,路由给 weak-point-drill 做更深入的针对性练习或建议回去重新理解这个概念。
  • study-plan: --session 的结果写入学习计划,供计划自适应调整。

这个技能不做的事

  • 替代专门的 SRS 工具。 如果用户已经有 Anki 之类的习惯,建议继续用; 这个技能是给不想切换工具、想在对话里快速过一遍的场景用的。
  • 为了凑数量编卡片。 材料只够生成8张有把握的卡,就给8张。硬凑一堆 [待核实] 的猜测卡比小卡组更糟。
  • 强制学习纪律。 漏复习的天数会累积,这个技能只负责告诉用户今天该复习 什么,要不要复习是用户自己的事。
  • 教会用户规则本身。 卡片是用来复习已经学过的内容的。如果一张卡反复 答错,问题出在更上游——用 weak-point-drill 或回去重新看材料。

© open-octo, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 2 other files in internal/skills/experts/flashcards of open-octo/octo-agent.

  • SKILL.md
  • LICENSE.txt
  • PROVENANCE.md

Open the folder on GitHubat commit fc1385f

Compare with similar skills

Flashcards next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Flashcards compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Flashcards this skillopen-octo/octo-agent125—~870Automated safety check: PassApache-2.0
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NihaishaJuneYaooo/nihaisha-nishi-tcm2.2k—~4kAutomated safety check: PassNone
Claude Certification Tutorrohitg00/ai-engineering-from-scratch66k—~3kAutomated safety check: PassMIT
StudyVault Quiz Tutorbevibing/tutor-skills1.3k—~1.4kAutomated safety check: PassMIT
Project Mastery Coachtudoumashu/ai-memory-skillpack422—~1.8kAutomated safety check: PassMIT

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Categories

Questions about Flashcards

What does Flashcards do?

生成和复习记忆卡片——Leitner 分桶间隔重复、按学科存储、自评式复习. An agent skill from open-octo/octo-agent. Flashcards is an agent skill from open-octo/octo-agent.

When should I use Flashcards?

Flashcards fits situations like: 用户说帮我做闪卡抽认卡考我一下这些卡片我要背这些规则/单词/ 概念等需要记忆巩固的场景。不是完整的 SRS 系统——如果用户已经在用 Anki 之类 的工具,建议他们继续用;这是在对话里就想快速过一遍的轻量方案; tasks that involve Study guides and flashcards.

How do I install Flashcards in Claude Code?

Run `npx skills add open-octo/octo-agent --skill flashcards -a claude-code`. Or copy the skill folder (internal/skills/experts/flashcards in open-octo/octo-agent) into .claude/skills/flashcards in your project. Claude Code loads it when a task matches its description.

How do I install Flashcards in Codex?

Run `npx skills add open-octo/octo-agent --skill flashcards -a codex`. Or copy the skill folder (internal/skills/experts/flashcards in open-octo/octo-agent) into .agents/skills/flashcards in your project. Codex loads it when a task matches its description.

Can I use Flashcards in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add open-octo/octo-agent --skill flashcards -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/flashcards, .gemini/skills/flashcards, .github/skills/flashcards and .opencode/skills/flashcards in your project.

What does Flashcards need to run?

SKILL.md names no scripts, command-line tools or credentials: Flashcards is instructions for the agent only.

Does Flashcards access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Flashcards safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Flashcards use?

Flashcards is published under the Apache-2.0 licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Flashcards use?

About 870 tokens (SKILL.md is roughly 3.5k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Flashcards?

Skills that share tags, products or a category with Flashcards: Deep Reading Analyst (ginobefun/deep-reading-analyst-skill, 353 stars), Nihaisha (JuneYaooo/nihaisha-nishi-tcm, 2.2k stars), Claude Certification Tutor (rohitg00/ai-engineering-from-scratch, 66k stars) and StudyVault Quiz Tutor (bevibing/tutor-skills, 1.3k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Flashcards?

open-octo (a GitHub organization) maintains it in open-octo/octo-agent, which has 125 GitHub stars. The repository holds 40 skills in this directory. The repository was last updated on October 8, 2026.

Source: open-octo/octo-agent on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.