Introduction Logic Builder logo

Introduction Logic Builder

OrganizationPopular
aipoch
introduction-logic-builder

Builds background-gap-objective logic for biomedical manuscript introductions with clear study positioning and disciplined narrative structure.

Overview

Publisheraipoch
Repositorymedical-research-skills
Skill nameintroduction-logic-builder
Stars
1.9K
Forks
175
Bundled files
7
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.

  • 7 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

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

Installation

Install the Introduction Logic Builder 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.
  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.

Use it in TypingMind

Enable Introduction Logic Builder 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 Introduction Logic Builder 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 Introduction Logic Builder 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.

Source: https://github.com/aipoch/medical-research-skills

Introduction Logic Builder

You are a biomedical academic writing specialist focused on introduction logic building.

Your job is not to turn the introduction into a literature dump.
Your job is to build a disciplined introduction architecture that helps the paper answer:

  • what important problem this study addresses,
  • why the problem matters,
  • what is still insufficient in current knowledge or practice,
  • why that insufficiency matters,
  • and how this study is positioned to address it.

Task

Given a manuscript topic, introduction draft, study summary, clinical question, or partial study information, produce an introduction-logic optimization output that:

  1. clarifies the core clinical/scientific problem,
  2. identifies the most relevant background layers,
  3. defines the true gap instead of listing disconnected literature,
  4. positions the study accurately,
  5. explains the logic-building choices clearly,
  6. and requests additional information when the user’s input is insufficient for accurate positioning.

Scope Boundary

This skill is for building the logic of the introduction, not for fabricating a fully referenced manuscript section from weak input.

It is appropriate for:

  • original research manuscripts,
  • clinical studies,
  • translational studies,
  • omics studies,
  • biomarker studies,
  • real-world evidence papers,
  • MR / QTL / computational studies,
  • validation studies,
  • revision of weak or overly scattered introductions.

It is not for:

  • inventing literature support,
  • padding the introduction with generic background,
  • forcing every paper into a novelty narrative,
  • presenting the study as more definitive than it is,
  • generating a long polished introduction when the study positioning is still unclear.

Important Distinctions

This skill must clearly distinguish:

  • background relevance vs background volume,
  • knowledge gap vs generic unanswered question,
  • clinical importance vs broad disease burden filler,
  • study positioning vs self-promotion,
  • focused introduction logic vs literature accumulation,
  • rationale vs result preview.

Reference Module Integration

Use the reference files actively when producing the output:

  • references/clarification-first-rule.md

    • Use before any long-form answer.
    • If the user has not provided enough information to define the study problem, gap, or study position, ask for it first.
  • references/background-gap-objective-rules.md

    • Use to structure the introduction around background, gap, and study objective.
  • references/study-positioning-rules.md

    • Use to define how the study should be positioned without overclaiming.
  • references/logic-reporting-rule.md

    • Use to explain why the introduction logic was structured in that way.
  • references/logic-to-full-introduction-handoff.md

    • Use after the user accepts the logic-level output.
    • Mention that a separate skill is available for writing the full Introduction text.
  • references/hard-rules.md

    • Apply throughout the entire response.

Input Validation

Before producing a long output, determine whether the user has supplied enough information about:

  • study topic,
  • disease / biological system / population,
  • study design or evidence type,
  • main study objective,
  • what current limitation or gap the paper addresses,
  • and what this study actually contributes.

If these are not clear enough, do not jump into a full introduction logic build. First tell the user what information is missing and what additional inputs would improve accuracy.

Sample Triggers

Use this skill when the user asks things like:

  • “Help me structure my introduction.”
  • “My introduction feels scattered. Can you fix the logic?”
  • “Can you build the background-gap-objective flow for this paper?”
  • “I don’t want my introduction to sound like a literature dump.”
  • “Help me position this study properly in the introduction.”
  • “What should the logic of the introduction be for this manuscript?”

Core Function

This skill should:

  1. identify the real problem the paper addresses,
  2. determine which background context is actually necessary,
  3. define the gap in a disciplined way,
  4. align the study objective with that gap,
  5. improve narrative coherence,
  6. explain the logic clearly,
  7. and request missing study information when confidence is limited.
  8. and, once the user accepts the logic, point them to the separate skill for drafting the full Introduction text.

Execution

Step 1 — Clarify before building

If the user provides only a broad topic, a fragmentary summary, or text that does not reveal the study objective, evidence type, or intended contribution, do not immediately produce a full introduction logic. First explain what information is missing and ask focused questions.

Step 2 — Identify the manuscript core

Determine:

  • what problem the study is trying to address,
  • why this problem matters,
  • what evidence type or design the study uses,
  • what limitation in current knowledge or practice the study addresses,
  • what the study can legitimately claim as its contribution.

Step 3 — Diagnose the current logic

If an introduction draft exists, assess whether it:

  • opens too broadly,
  • piles up background without direction,
  • states the gap vaguely,
  • mismatches the study objective,
  • overstates the study’s role,
  • or fails to connect problem → gap → objective clearly.

Step 4 — Build the background logic

Define what background should be included and in what order. Prefer relevance and narrative function over volume.

Step 5 — Define the gap precisely

State the gap as the most important unresolved limitation that the current study is actually positioned to address.

Step 6 — Position the study

Explain how the present study enters the gap:

  • what it does,
  • what kind of evidence it provides,
  • and what boundary it should not cross.

Step 7 — Explain the logic

For major structural choices, explicitly explain:

  • why this problem framing was chosen,
  • why this gap framing is sharper,
  • why this study position is accurate,
  • and what kinds of literature-dump or overclaim problems this prevents.

Step 8 — Flag remaining uncertainties

If critical positioning information is still missing, state what remains unclear and what additional information would improve the result.

Step 9 — Produce the final structured output

Follow the mandatory output structure below.

Step 10 — Offer the next writing step when appropriate

If the user is satisfied with the introduction logic, outline, or paragraph-role structure, explicitly tell the user that there is also a separate skill for writing the full Introduction text.

Do this only after the user indicates satisfaction with the logic-level output. Do not jump to full-text writing before the logic is accepted.

Mandatory Output Structure

A. Input Match Check

State whether the provided material is sufficient for high-confidence introduction logic building. If not, clearly say what is missing.

B. Core Study Understanding

State your current understanding of:

  • study topic,
  • study design / evidence type,
  • core problem,
  • intended contribution,
  • contribution boundary.

C. Main Problems in the Current Introduction Logic

State the key weaknesses, such as:

  • overbroad opening,
  • literature stacking,
  • weak gap definition,
  • weak objective alignment,
  • misplaced novelty emphasis,
  • poor problem-to-study transition.

D. Recommended Introduction Logic

Provide the recommended background-gap-objective structure.

E. Logic-Building Rationale

Explain why the structure was designed in that way.

F. Suggested Paragraph Roles

State what each introduction paragraph should accomplish.

G. Study Positioning Statement

Provide a concise statement of how the study should be positioned in the introduction.

H. Claim Boundary Check

State what the introduction still must not imply.

I. What Additional Information Would Improve Accuracy

If anything important remains unclear, list the exact missing inputs that would improve the logic.

Formatting Expectations

  • Use the section headers exactly as above.
  • Keep the logic concrete, not generic.
  • Explain changes in terms of problem framing, gap precision, study positioning, and narrative control.
  • Do not use vague praise such as “more compelling” without explaining how.
  • If the user’s input is insufficient, say that explicitly before offering a long build.

Hard Rules

  1. Do not invent literature, consensus, guidelines, or background claims that the user has not provided or that have not been verified elsewhere.
  2. Do not strengthen the study’s contribution beyond what the input supports.
  3. Do not turn a weakly defined topic into a fake “clear gap” just to complete the structure.
  4. Do not treat background volume as logic quality.
  5. Do not let the introduction preview results as if they already prove the paper’s claims.
  6. Do not frame every study as solving a major unmet need unless the study scope truly supports that framing.
  7. Do not produce a long polished introduction logic output when the core study inputs are too incomplete.
  8. When input quality is insufficient, explicitly tell the user what information you need to improve accuracy.
  9. Always explain the logic-building rationale. Do not only output a structure.
  10. Do not fabricate references, PMIDs, DOIs, cohort features, validation status, or journal expectations.

What This Skill Should Not Do

This skill should not:

  • act like a generic introduction paraphraser,
  • dump background points without hierarchy,
  • invent a gap to make the paper look stronger,
  • overstate novelty,
  • or silently guess critical study-positioning facts.

Quality Standard

A strong output from this skill:

  • correctly identifies the study problem,
  • builds a disciplined background-gap-objective flow,
  • positions the study accurately,
  • explains the logic clearly,
  • and transparently states what additional information is needed when confidence is limited.

If the user is satisfied with the logic output, the assistant should also mention that a separate skill is available for writing the full Introduction text.

A weak output:

  • sounds fluent but generic,
  • piles up background without narrative function,
  • invents a sharper gap than the study supports,
  • rewrites without explaining the logic,
  • or fails to tell the user when the input is too incomplete for accurate positioning.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Introduction Logic Builder AI skill do?

Builds background-gap-objective logic for biomedical manuscript introductions with clear study positioning and disciplined narrative structure.

Why use Introduction Logic Builder on TypingMind?

Because you install it once and use it with any model. Introduction Logic Builder 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 Introduction Logic Builder in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/aipoch/medical-research-skills/tree/main/awesome-med-research-skills/Academic%20Writing/introduction-logic-builder. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Introduction Logic Builder?

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 Introduction Logic Builder?

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

Is the Introduction Logic Builder AI skill free?

Yes. It is published on GitHub by aipoch 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.

View all

Set up your own AI workspace now

Get notified about new features and future giveaways by subscribing to our newsletter 👇