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Exam Help

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ZeKaiNie
exam-help

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。

Overview

PublisherZeKaiNie
Repositoryuniversal-examprep-skill
Skill nameexam-help
Stars
314
Forks
17
Bundled files
Instructions only
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by ZeKaiNie on GitHub. Read the source before you install it.

Installation

Install the Exam Help AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/ZeKaiNie/universal-examprep-skill/tree/main/full/skills/exam-help
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/ZeKaiNie/universal-examprep-skill.git /tmp/universal-examprep-skill
mkdir -p .claude/skills
cp -r /tmp/universal-examprep-skill/full/skills/exam-help .claude/skills/exam-help
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Exam Help in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Exam Help on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Exam Help is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

exam-help — quick-reference card

Purpose

Render one read-only card covering the validated workflow, three modes, four time tiers, lightweight|full, chat|visual, workspace truth/views, six quiz types, provenance, and subskill routing.

Activation

Use only when the student asks how the suite works, which modes/types exist, or what workspace files mean.

Inputs

No files, arguments, or state reads. The caller supplies the selected language.

Workflow

  1. Emit the matching static language-pack card: persisted zh, en, or bilingual, otherwise an explicit ad-hoc request.
  2. Read no wiki, bank, plan, progress, or workspace file; run no script/subskill.
  3. Stop without tutoring, quizzing, ingesting, grading, or initialization.

The card must say:

  • processing_mode=lightweight is the default/recommended startup choice. It inventories names, then visually processes only the current-phase PDF pages or definitely single-frame PNG/JPEG/BMP (maximum eight primary pages and one active batch). Overview contact sheets group at most four pages at roughly 768 px/tile; page/prompt/dependency detail and target-answer-only solution calls use source-qualified locations and canonical PNG evidence under .lightweight/assets/. Bind exact external answer pages with register-answer-dependency; dependency pages are locator/detail only. Figure prompt/answer crops stay distinct. An unfinished batch can close only through receipt-backed abandon --reason; taught progress cannot be abandoned, while replace-taught --reason preserves it as superseded history and plans an exact-slice successor. It keeps the page-batch / progress state machines and creates no Study Guide/PDF. processing_mode=full is explicit opt-in and opens the complete ingestion/review route. Input-token savings never shorten the teaching explanation.
  • artifact_mode is independent from processing intensity and never inferred from subscription. Missing/legacy/unknown means chat. In full mode, chat stops without PDF while standing visual additionally requires typed Guide, render, receipt hashes, every-page QA, and artifact_ready=ready. A one-shot artifact leaves stored state unchanged. In lightweight, a saved visual preference is dormant and effective output remains chat; it never builds a Study Guide.
  • answer_explanation_mode is also independent. Its stored-schema fallback is ordinary, and every full-Guide item still gets a detailed beginner-first explanation. At full-v2 Guide entry, a verified host-native child with a fresh independent context plus exact single-item input/tool restrictions makes isolated the default unless the learner opted out; tell the learner once about extra host quota/time, with no second API key or external upload. Missing or incomplete capability stays ordinary and is stated honestly. A separately billed external Provider is explicit-request-only and retains no-upload planning, current pricing/privacy disclosure, and exact-plan upload consent. A model name, subscription, key, full, or visual alone proves neither route.
  • ingest_course.py is the full-mode build entry; exit 10 is process success with blocked readiness, and teaching remains forbidden. .ingest/ is full-mode build/review truth, .lightweight/session.json is on-demand page-batch truth, study_state.json is progress truth, and Markdown is a generated view.
  • Lightweight completion uses current-phase taught-batch/notebook events and skips typed Guide/full-build evidence; superseded predecessors/events remain history but leave the current denominator. verified needs revision-bound checkpoints from an unchanged bank that pre-existed lightweight initialization; startup captures only its immutable stat baseline. Routine health checks use metadata/physical identity, not stream hashes; exact hashes occur at transitions/completion or explicit status --verify-live. Older taught history is unchecked_historical until that phase is resumed.
  • MinerU, Docling, and LangGraph are named-request-only and remote/cloud-only. Never download, install, probe, import, or execute them locally.
  • Provenance is exact: 🟢 来自资料 / 🟡 AI补充,可能与你老师讲的不完全一致 / ⚠️ AI生成答案,非老师/教材提供.

Output Contract

Output exactly one help card and mutate nothing. Student prose is English by default, Simplified Chinese for a Chinese opening, or explicit bilingual composition.

Language packs

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

Boundaries

This card is read-only. Route actual review to exam-cram.

Frequently asked questions

What does the Exam Help AI skill do?

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。

Why use Exam Help on TypingMind?

Because you install it once and use it with any model. Exam Help is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Exam Help in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/ZeKaiNie/universal-examprep-skill/tree/main/full/skills/exam-help. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Exam Help?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Exam Help?

As many as you like. As long as a model supports skills, you can use Exam Help with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Exam Help AI skill free?

Yes. It is published on GitHub by ZeKaiNie under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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