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Amj Literature Positioning

Community
franklee16
amj-literature-positioning

Use when the front end of an Academy of Management Journal (AMJ) manuscript needs to engage the right literatures and stake a clear position in an ongoing theoretical conversation. Positions the paper among theories; it does not derive the hypotheses (amj-theory-development) or write the contribution paragraph (amj-contribution-framing).

Overview

Publisherfranklee16
Repositoryacademic-research-skills
Skill nameamj-literature-positioning
Stars
225
Forks
34
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 franklee16 on GitHub. Read the source before you install it.

Installation

Install the Amj Literature Positioning 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/franklee16/academic-research-skills/tree/master/Awesome-Journal-Skills-main/Academy-of-Management-Journal-Skills/skills/amj-literature-positioning
  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/franklee16/academic-research-skills.git /tmp/academic-research-skills
mkdir -p .claude/skills
cp -r /tmp/academic-research-skills/Awesome-Journal-Skills-main/Academy-of-Management-Journal-Skills/skills/amj-literature-positioning .claude/skills/amj-literature-positioning
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Amj Literature Positioning 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 Amj Literature Positioning 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 Amj Literature Positioning 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.

Literature Positioning (amj-literature-positioning)

When to trigger

  • The introduction reads as "no one has studied X" (gap-spotting) rather than joining a debate
  • The literature review is an annotated list of prior findings, not an argument
  • Canonical theoretical works in the focal domain are missing or cited only in passing
  • You are unsure which conversation the paper enters and which scholars are the audience
  • A reviewer says "I don't see how this advances the literature" or "this misreads prior work"

The positioning move AMJ rewards

AMJ papers join an ongoing theoretical conversation and change it. The front end should name the conversation, show the unresolved tension or contradiction in it, and signal how this study resolves or extends it. "Gap-spotting" — pointing to an empty cell in a table of prior studies — is treated as a weak motivation; AMJ wants a problematization: surfacing and challenging an assumption the literature has taken for granted (Alvesson & Sandberg's problematization argument is the standard reference for this move). AMJ's From the Editors editorials repeatedly press the "so what?" and "who cares?" tests — your positioning must make the contribution matter to the broad management readership, not only a niche.

Three legitimate motivating moves

  1. Tension between theories — two literatures predict opposite things; your study adjudicates.
  2. Boundary/contingency — an established effect should not hold (or should reverse) under a condition the literature has overlooked, for a theoretical reason.
  3. Problematization — an assumption underlying a literature is questionable; relaxing it changes predictions.

A bare "gap" (no study has done X) is not on this list unless you supply the theoretical reason the gap matters.

Engaging the literatures

  • Identify the focal literature (the conversation you join) and any supporting literatures (the lens or mechanism you import). Keep them distinct.
  • Cite the canonical theoretical works that define the focal construct/theory, plus recent papers that show the conversation is live — favor AMJ and its AOM sister journals (AMR for the theory side, AMD for emerging phenomena) and, where the conversation spans them, ASQ and SMJ.
  • Review to build your argument, not to catalog: each cited stream should end with the tension your study addresses.
  • Place the paper relative to the closest 2–3 prior studies and say precisely how yours differs in mechanism, level, boundary, or design — not merely in context.

Front-end structure

A typical AMJ introduction: (1) hook the phenomenon, (2) name the conversation and the tension, (3) state the research question, (4) preview the theoretical approach and study, (5) state the intended contribution. The literature review/theory section then develops the streams in the order the hypotheses need them.

Checklist

  • The introduction names a specific theoretical conversation, not an empty cell
  • Motivation is a tension, boundary, or problematization — not bare gap-spotting
  • Canonical theoretical works defining the focal construct are cited and used
  • Recent AMJ/AMR/ASQ/SMJ papers establish the conversation is current
  • Closest 2–3 prior studies are named with a precise statement of how this paper differs
  • Each literature stream ends pointing at the tension this study resolves
  • The intended audience (division/scholars) is clear from the framing

Anti-patterns

  • Gap-spotting: "No prior work has examined X in Y" as the sole motivation.
  • Citation dump: long lists of "(Author, year; Author, year)" with no argumentative thread.
  • Misreading prior work: mischaracterizing a cited study (reviewers are often its authors).
  • Context-only novelty: claiming contribution because the setting is new, not the mechanism.
  • Burying the focal theory: the lens you actually use appears only in the methods.
  • Ignoring the obvious rival literature: a reviewer's first move is to name the stream you skipped.

Output format

【Focal conversation】the literature/theory you join ...
【Motivating move】tension / boundary / problematization (state it)
【Supporting literatures】lens or mechanism imported ...
【Canonical works engaged】[...]
【Closest prior studies】[...] — how this paper differs: ...
【Audience】division / scholars ...
【Next step】amj-methods (match design to the question)

Frequently asked questions

What does the Amj Literature Positioning AI skill do?

Use when the front end of an Academy of Management Journal (AMJ) manuscript needs to engage the right literatures and stake a clear position in an ongoing theoretical conversation. Positions the paper among theories; it does not derive the hypotheses (amj-theory-development) or write the contribution paragraph (amj-contribution-framing).

Why use Amj Literature Positioning on TypingMind?

Because you install it once and use it with any model. Amj Literature Positioning 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 Amj Literature Positioning in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/franklee16/academic-research-skills/tree/master/Awesome-Journal-Skills-main/Academy-of-Management-Journal-Skills/skills/amj-literature-positioning. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Amj Literature Positioning?

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 Amj Literature Positioning?

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

Is the Amj Literature Positioning AI skill free?

It is published on GitHub by franklee16. 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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