本文へ移動
cccskills
無料GitHub で公開

exam-cheatsheet

全员通关后把 错题本+笔记本+知识点窗口+wiki 编译成考前速记小抄 cheatsheet.md(每条要点带可溯源 锚点),并在视觉产物模式或用户明确要求 PDF/打印版时按指定页数渲染成打印级 PDF:按「必背结论/公式 → 有难度例题(必要时含题面图)→ 例题解答(代入公式、保留基础过程)→ 要点解释(同类题怎么办)」 四段组织。

当复习收尾、用户要「考前小抄/速记/总结/打印版」时使用。

インストール方法を見る

含まれるファイル(1)

  • SKILL.md7.6 KB

SKILL.md(原文)

インストールする前に、エージェントに与えられる指示の中身を確認できます。

exam-cheatsheet — pre-exam cheatsheet compiler

Purpose

Compile, rather than free-generate, mastered content into workspace-root cheatsheet.md. Every top-level bullet must link into notebook/, mistakes/, or references/wiki/. Do not teach new material or invent questions. Render the requested-page-count PDF only for standing visual mode or an explicit PDF/print request. Never write the retired walkthrough.md; leave an existing copy untouched.

Activation

Trigger on an explicit request for 「考前小抄 / 速记 / 总复习」, or when review is wrapping up after all phases and persisted artifact_mode=visual. Automatic final review under chat stays a conversational exam-review summary.

Inputs

  • Weak-spot source: study_state.json (mistake_archive, confusion_log, and phase_checklist) when it exists; otherwise the possibly stale generated study_progress.md. Read these first, then mistakes/index.md and notebook/index.md when present; their full entries provide preferred ready-made anchors.
  • Rank knowledge_window status out_window above in_window and verified (codes are defined by scripts/i18n.py).
  • Read core conclusions and formulas from every mastered chapter in references/wiki/, derived from study_state.json's current_phase/phase_checklist when it exists, otherwise study_progress.md, checked against study_plan.md. Lazy-load one chapter at a time.
  • Use references/quiz_bank.json for teacher-flagged items and answer frameworks. Resolve scripts/select_hard_questions.py from ${CLAUDE_SKILL_DIR}, never the student workspace; it returns a flat ranked list which the agent groups by knowledge point.

Workflow

  1. Gate artifacts. Read study_state.json.artifact_mode; missing, legacy, or unknown means chat. Never infer a subscription tier or add a fourth required first-contact question. Automatic chat review creates no sheet; an explicit sheet request may create Markdown. Only standing visual or an explicit one-shot PDF/print request authorizes rendering. A one-shot request does not modify the persisted value. Never install dependencies or skills silently.
  2. Build the skeleton. Weak spots come first. Per chapter retain only high-frequency or high-scoring formulas, conclusions, and one-sentence definitions.
  3. Select one hard example per key point. For each mastered chapter run python "${CLAUDE_SKILL_DIR}/scripts/select_hard_questions.py" --workspace <ws> --chapter <N> --mode 查缺补漏 -n <M> --json. Both --chapter and --mode are required: they avoid a missing-range failure in 某章起步补弱 and override easy-first 零基础从头讲. Set <M> at least to the bank length so the default top ten cannot starve later points. Group the flat result, prioritize points linked to mistakes/confusions, and choose the hardest candidate per point. With no linked bank item, emit 「无题库例题」 and only the 「必背结论/公式」 and 「要点解释」 sections; never invent a replacement.
  4. Fail closed on prompt assets. For requires_assets=true or maybe_requires_assets=true, embed every question_context, figure, diagram, and table as workspace-relative references/assets/ links, labeled 题面图 for zh/bilingual or Question-side asset for en. Preserve but never embed student_attempt; one declaration taints the same physical path across the complete quiz, teaching, and content-unit layers, including a duplicate official-looking declaration. Missing or unusable assets require a self-contained alternative. A stub or page_reference item likewise needs its original-page render or replacement by a full item. Never include an example whose prompt figure/page is invisible. cheatsheet_render.py performs the shared three-layer policy and canonical-path gate; do not bypass it with a custom Markdown/image renderer.
  5. Write the four sections. The worked solution states the formula, substituted values, and result; only intermediate arithmetic may be omitted. The takeaway starts with the recognition cue and then the answer framework. Material-backed lines may remain unlabeled; AI supplements require 🟡 AI补充,可能与你老师讲的不完全一致, AI answers require ⚠️ AI生成答案,非老师/教材提供, and missing/unknown bank answer provenance requires 「来源未知」. Do not let uncertain content inherit the material default; see docs/language-policy.md.
  6. Attach traceability. End every top-level - bullet with [→](notebook/chNN.md#<anchor>), [→](mistakes/chNN.md#<anchor>), or [→](references/wiki/<file>.md), preferring notebook/mistake evidence. Run python "${CLAUDE_SKILL_DIR}/scripts/validate_workspace.py" <ws> and fix every untraced or dead link before delivery.
  7. Write only when authorized. Create workspace-root cheatsheet.md with the four sections for every mastered chapter and a refreshed progress panel. Under chat, this requires an explicit sheet request.
  8. Render only when authorized. For standing visual or explicit one-shot PDF/print, ask for the page count if omitted (default 2), then run python "${CLAUDE_SKILL_DIR}/scripts/cheatsheet_render.py" --workspace <ws> --pages <N>. Exit 0 must produce exactly N print-safe pages with margins ≥12 mm. Exit 3 returns cheatsheet.html plus the emitted print instruction. Visually inspect the result; adjust --font-size, not margins, until it fits N pages and the last page has at most about 15% blank. Under ordinary chat, stop after validated Markdown and do not ask for page count.
  9. Never invent teacher emphasis; only material-flagged points may be described that way.

Output Contract

  • cheatsheet.md uses active-language headings per mastered chapter: zh uses 「必背结论/公式」→「例题」→「例题解答」→「要点解释」; en uses Must-memorize conclusions & formulas → Worked example → Worked solution → Takeaway. Every bullet is traced and validation passes.
  • An explicit chat request delivers Markdown only unless it also requests print/PDF. Authorized rendering delivers exact-page-count cheatsheet.pdf, or cheatsheet.html plus print instructions on the no-browser path.
  • Student-facing output defaults to English (Simplified Chinese if the student opened in Chinese). Persisted language values zh, en, and bilingual select single-language or mirrored output per docs/language-policy.md.

Language packs

Display aliases are normalized to zh, en, or bilingual.

Boundaries

  • Unsupported content needs the applicable 🟡 or ⚠️ label. The sheet compresses completed review; it never bypasses source labels or the quiz_bank-only rule.

レビュー

まだレビューはありません。使ってみた感想をお寄せください。

同じリポジトリのスキル

概要と使いどころ

教学过程中自动捕获和记录学习者的概念疑难点("为什么/是什么/怎么推/什么意思"类型的问题),保存到进度文件的"概念疑难点记录"区,形成考前回顾清单。

日本語の概要は準備中です。原文の説明を表示しています。

ZeKaiNie/universal-examprep-skill3042026年9月28日 更新

只读检查一个已生成的备考工作区是否健康并报告问题,默认不做任何修改。核对 .ingest 原材料版本、 内容单元、接管队列与派生产物完整性,以及 wiki、题库、视觉证据、计划和进度的一致性。当用户怀疑 工作区有问题、建库 readiness 被阻断、或想在开始复习前体检时使用。

日本語の概要は準備中です。原文の説明を表示しています。

ZeKaiNie/universal-examprep-skill3042026年9月28日 更新

exam-cram

無料

临考前的极速备考总教练。把课件、大纲、重点与真题建成分章 wiki 和标准题库,再组织惰性授课、 题库判分、错题与疑难复盘及可选考前小抄,并持久化进度。用于期末、备考、突击、刷题、划重点、 错题与考前复习;不用于长期规划或与考试无关的写作/编程。

日本語の概要は準備中です。原文の説明を表示しています。

ZeKaiNie/universal-examprep-skill3042026年9月28日 更新

exam-help

無料

备考教练的一屏速查卡:工作流、3×4 学习选择、产物偏好、工作区文件、6 大题型、来源规则与子技能路由。 用户问怎么用、有哪些模式、文件用途或支持题型时使用。

日本語の概要は準備中です。原文の説明を表示しています。

ZeKaiNie/universal-examprep-skill3042026年9月28日 更新

从学生上传的课件/大纲/老师勾的重点/真题,一键初始化并验证备考工作区:解析 PDF、DOCX、PPTX、 XLSX、常见独立图片与 txt/md,建立分章节 LLM Wiki、标准题库、结构化接管队列与进度状态;仅在 Python 确实无法运行时 明确降级为手动写盘。当工作区尚未建立、资料发生变化、或建库 readiness 被阻断时使用。

日本語の概要は準備中です。原文の説明を表示しています。

ZeKaiNie/universal-examprep-skill3042026年9月28日 更新

exam-quiz

無料

从 references/quiz_bank.json 抽取本章题目并按标准答案判分,支持选择、主观、画图、填空、判断、代码; 主观题按 keywords 要点覆盖判分,连续错两次提供提示/跳过/归档。禁止现场编题。用于阶段检查或模考。

日本語の概要は準備中です。原文の説明を表示しています。

ZeKaiNie/universal-examprep-skill3042026年9月28日 更新

ZeKaiNie のスキルをすべて見る

このスキルの問題を報告する