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Reference Generator

Community
dmccreary
reference-generator

Generates 10 curated academic references per chapter, prioritizing Wikipedia plus credited textbook authors known for innovative explanations, with relevance descriptions, stored in chapter references.md files. Use when an intelligent textbook chapter needs citations.

Overview

Publisherdmccreary
Repositoryibook-skills
Skill namereference-generator
Stars
109
Forks
21
Bundled files
Instructions only
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 dmccreary on GitHub. Read the source before you install it.

Installation

Install the Reference Generator 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/dmccreary/ibook-skills/tree/main/skills/reference-generator
  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/dmccreary/ibook-skills.git /tmp/ibook-skills
mkdir -p .claude/skills
cp -r /tmp/ibook-skills/skills/reference-generator .claude/skills/reference-generator
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Reference Generator 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 Reference Generator 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 Reference Generator 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.

Reference Generator

Version: 1.0

Overview

Generate high-quality, curated reference lists for educational textbooks. Each chapter receives exactly 10 references, prioritizing Wikipedia articles first for reliability, then crediting the specific textbook authors who pioneered clear or innovative ways of teaching the chapter's concepts, followed by authoritative online resources. References are never just a list of Wikipedia links — the textbook slots exist specifically to give credit to the authors behind influential explanations, analogies, or pedagogical techniques (e.g., a particularly intuitive derivation, a widely-copied diagram, a teaching analogy that became standard). References are stored in separate references.md files for token-efficient maintenance by AI agents.

When to Use This Skill

Use this skill when:

  • Creating a new intelligent textbook that needs chapter references
  • Adding references to an existing textbook
  • Updating or expanding references for educational content
  • A user explicitly requests reference generation

Key Principles

10 References Per Chapter

Every chapter receives exactly 10 high-quality references:

  • References 1-3: Wikipedia articles (most reliable, always accessible)
  • References 4-5: Textbooks that credit a specific author's innovative explanation, analogy, derivation, or notation for a chapter concept (title, author, publisher - no URLs that break)
  • References 6-10: Online resources (tutorials, courses, verified working links)

Wikipedia First

Wikipedia links are placed first because they:

  • Have stable, reliable URLs that rarely break
  • Provide comprehensive, well-sourced overviews
  • Are freely accessible to all students
  • Cover most technical topics thoroughly
  • Are maintained and updated by the community

Separate Reference Files

References are stored in separate references.md files (not inline in chapters) for:

  • Token efficiency: ~150 tokens vs ~6,000 tokens to read/update
  • Batch processing: Agents can glob **/references.md for bulk updates
  • Separation of concerns: Chapter edits don't risk breaking references

Reference Generation Workflow

Step 1: Analyze the Course Description

Read the /docs/course-description.md file to determine:

  • Subject matter - determines reference topics
  • Target audience - guides complexity of descriptions
  • Learning objectives - ensures references support goals

Step 2: Identify Chapter Structure

Locate all chapter directories:

bash
# Find chapter folders
ls docs/chapters/

For each chapter, read the chapter index.md to understand:

  • Chapter title and topic
  • Key concepts covered
  • Learning objectives

Step 3: Generate 10 References Per Chapter

For each chapter, create exactly 10 references following this priority:

Positions 1-3: Wikipedia Articles

Find the most relevant Wikipedia articles for the chapter's main concepts:

markdown
1. [Concept Name](https://en.wikipedia.org/wiki/Concept_Name) - Wikipedia - Description of article content and relevance to chapter.

Positions 4-5: Textbooks Crediting Innovative Authors (No URL)

These two slots exist to give explicit credit to authors, not just to cite a source. For each chapter's key concepts, identify the textbook author(s) most associated with an innovative, intuitive, or influential way of teaching that concept — a distinctive analogy, derivation, notation, worked example, or diagram that other authors have since adopted or that students consistently find clarifying. Search for who "originated" or is "best known for" the chapter's core explanation before defaulting to a generic well-known textbook. Reference these textbooks without URLs (which often break):

markdown
4. Textbook Title (Edition) - Author Name - Publisher - Names the specific innovation (analogy, derivation, notation, example) this author is known for and why it makes the concept easier to grasp.

Positions 6-10: Online Resources

Verified online tutorials, courses, and educational sites:

markdown
6. [Resource Title](https://verified-url.com/path) - Source Name - Description of content and specific relevance to chapter topics.

Step 4: Verify Online URLs

For references 6-10, verify each URL:

python
WebFetch(url=reference_url, prompt="Is this page accessible? What is the main topic?")

Preferred sources (stable, educational):

  • All About Circuits (allaboutcircuits.com)
  • Electronics Tutorials (electronics-tutorials.ws)
  • ChipVerify (chipverify.com)
  • HDLBits (hdlbits.01xz.net)
  • Nandland (nandland.com)
  • MIT OpenCourseWare (ocw.mit.edu)
  • GeeksforGeeks (geeksforgeeks.org)
  • Digilent Reference (digilent.com/reference)

Step 5: Write Reference Files

Create a references.md file in each chapter directory:

File location: docs/chapters/XX-chapter-name/references.md

File format:

markdown
# References: [Chapter Title]

1. [Wikipedia Article](https://en.wikipedia.org/wiki/Topic) - Wikipedia - Comprehensive overview of [topic] including [specific aspects relevant to chapter].

2. [Wikipedia Article 2](https://en.wikipedia.org/wiki/Topic2) - Wikipedia - Detailed explanation of [concept] with [relevant details].

3. [Wikipedia Article 3](https://en.wikipedia.org/wiki/Topic3) - Wikipedia - Coverage of [related topic] including [applications/examples].

4. Textbook Title (Edition) - Author Name - Publisher - Author Name pioneered [specific analogy/derivation/notation] for [concept], now widely adopted because [why it clarifies the idea].

5. Textbook Title 2 - Author Name - Publisher - Credits Author Name's [specific innovative approach] to [chapter concept], noted for [what makes it distinctive/effective].

6. [Online Resource](https://verified-url.com) - Source - Tutorial on [topic] with [specific features like examples, exercises, visualizations].

7. [Online Resource 2](https://verified-url.com) - Source - [Description of content and relevance].

8. [Online Resource 3](https://verified-url.com) - Source - [Description of content and relevance].

9. [Online Resource 4](https://verified-url.com) - Source - [Description of content and relevance].

10. [Online Resource 5](https://verified-url.com) - Source - [Description of content and relevance].

Step 6: Update Chapter Files

Add a link at the end of each chapter's index.md:

markdown
[See Annotated References](./references.md)

Important: Replace any existing ## References section with this single link.

Step 7: Update mkdocs.yml Navigation

Nest an Annotated References: entry under each chapter in mkdocs.yml, following the canonical nav-editing rules (read-before-write, serialize edits, Content: label for the chapter page) in $BK_HOME/skills/book-installer/references/mkdocs-nav-editing.md:

yaml
  - 1. Chapter Name:
    - Content: chapters/01-chapter-folder/index.md
    - Quiz: chapters/01-chapter-folder/quiz.md
    - Annotated References: chapters/01-chapter-folder/references.md

Reference Quality Guidelines

Description Requirements

Each reference description should:

  • Explain what the resource covers (1 sentence)
  • Explain why it's relevant to this chapter (1 sentence)
  • Mention specific features (examples, exercises, visualizations)
  • Be 20-40 words total

Good example:

markdown
1. [Karnaugh map](https://en.wikipedia.org/wiki/Karnaugh_map) - Wikipedia - Detailed explanation of K-map theory, grouping rules, and don't-care conditions. Essential foundation for the simplification techniques covered in this chapter.

Bad example:

markdown
1. [Karnaugh map](https://en.wikipedia.org/wiki/Karnaugh_map) - Wikipedia - About K-maps.

Wikipedia Article Selection

Choose Wikipedia articles that:

  • Cover the chapter's primary concepts
  • Have substantial content (not stubs)
  • Include diagrams, examples, or formulas
  • Link to related topics students might explore

Textbook Selection

Reference textbooks whose author:

  • Is credited with originating or popularizing a specific explanation, analogy, derivation, notation, or diagram for one of the chapter's concepts
  • Is widely cited by other authors or instructors for that particular teaching innovation
  • Wrote a textbook that is reasonably accessible to students
  • Has an explanation the description names concretely — never just "covers the topic well"

If no author stands out as the originator of a distinctive teaching approach, choose the textbook most often praised (in reviews, syllabi, or educator discussion) for making the concept unusually clear, and say so explicitly in the description rather than defaulting to a generic "authoritative textbook" citation.

Online Resource Selection

Choose online resources that:

  • Have verified, working URLs
  • Come from educational or reputable technical sources
  • Provide practical examples or exercises
  • Complement (not duplicate) Wikipedia content

Reference Quality Checklist

Before finalizing references, ensure:

  • Exactly 10 references per chapter
  • References 1-3 are Wikipedia articles
  • References 4-5 are textbooks (no URLs) that name the specific author and the innovative explanation/analogy/derivation they're credited with
  • References 6-10 have verified working URLs
  • All descriptions are 20-40 words
  • Descriptions explain relevance to chapter
  • No duplicate sources across references
  • Proper formatting throughout

File Structure After Generation

docs/chapters/
├── 01-chapter-name/
│   ├── index.md          # Ends with: [See Annotated References](./references.md)
│   ├── quiz.md
│   └── references.md     # 10 curated references
├── 02-chapter-name/
│   ├── index.md
│   ├── quiz.md
│   └── references.md
...

Token Efficiency Benefits

TaskInline ReferencesSeparate Files
Read one chapter's refs~6,000 tokens~200 tokens
Update all 15 chapters~90,000 tokens~3,000 tokens
Batch reference checkNot feasibleGlob + process

Finish

After generating references:

  1. Report the number of chapters processed
  2. List any URLs that failed verification
  3. Confirm mkdocs.yml was updated
  4. Remind user to verify the site builds: mkdocs serve

Resources

This skill uses web-based verification tools built into Claude Code:

  • WebSearch: Find authoritative sources on topics
  • WebFetch: Verify URLs are accessible and extract metadata
  • Glob: Find all chapter directories and reference files
  • Write: Create reference files
  • Edit: Update chapter files and mkdocs.yml

No additional scripts or assets are required for this skill.

Frequently asked questions

What does the Reference Generator AI skill do?

Generates 10 curated academic references per chapter, prioritizing Wikipedia plus credited textbook authors known for innovative explanations, with relevance descriptions, stored in chapter references.md files. Use when an intelligent textbook chapter needs citations.

Why use Reference Generator on TypingMind?

Because you install it once and use it with any model. Reference Generator 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 Reference Generator in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/dmccreary/ibook-skills/tree/main/skills/reference-generator. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Reference Generator?

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 Reference Generator?

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

Is the Reference Generator AI skill free?

It is published on GitHub by dmccreary. Check the repository for licensing terms. 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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