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Amr Theory Development

Community
franklee16
amr-theory-development

Use when building the actual theory for an Academy of Management Review (AMR) manuscript — turning a positioned puzzle into defined constructs, explicit relationships, propositions, and boundary conditions. Constructs the theory; it does NOT stress-test the argument's logic (that is amr-data-analysis) or design any data collection (AMR has none).

Overview

Publisherfranklee16
Repositoryacademic-research-skills
Skill nameamr-theory-development
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 Amr Theory Development 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-Review-Skills/skills/amr-theory-development
  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-Review-Skills/skills/amr-theory-development .claude/skills/amr-theory-development
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Amr Theory Development 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 Amr Theory Development 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 Amr Theory Development 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.

Theory Development: Constructs, Relationships, Propositions (amr-theory-development)

When to trigger

  • The puzzle and conversation are set; now you must build the theory
  • You have propositions but no defined constructs underneath them
  • Your relationships are asserted, not derived
  • You have not stated boundary conditions or assumptions

The build order

AMR theory is assembled in a disciplined sequence. Skipping a step is the most common reason a draft reads as "assertions, not theory."

  1. Define the constructs. For each new or re-specified construct: a precise conceptual definition, its domain (what it includes and, crucially, excludes), scope conditions, and how it differs from neighboring constructs. This is the construct-clarity standard from Suddaby's AMR editorial (2010, DOI 10.5465/amr.2010.0419): definition, scope conditions, semantic relationships, coherence. A construct that overlaps an existing one without distinction will be challenged as a relabel.
  2. State the assumptions. What must be true about actors, the setting, and the world for the theory to operate? Make them explicit; hidden assumptions are where reviewers attack.
  3. Specify the relationships. Name the form of each link: causal, recursive, moderating, mediating, constitutive. "X relates to Y" is not a relationship — specify direction, shape, and why.
  4. Articulate the mechanism. The why. The mechanism is the engine that makes the relationship hold. A proposition without a mechanism is a guess. Whetten's AMR editorial (1989, DOI 10.5465/amr.1989.4308371) is explicit that the Why is what makes theory theory; the What and How without the Why is description. (Develop the mechanism logic with amr-data-analysis.)
  5. Write the propositions. Each proposition is a falsifiable theoretical claim that follows from the constructs + mechanism. Number them (P1, P2...). Each must be preceded by the argument that earns it.
  6. Set boundary conditions. State when the theory holds and when it does not — the contextual, temporal, and level limits. Boundary conditions are a contribution, not a disclaimer.

Construct definition template

For each construct, fill:

  • Label (one term, used consistently throughout)
  • Conceptual definition (one or two precise sentences)
  • Domain — included instances / excluded instances
  • Distinction — how it differs from the nearest existing construct
  • Level of theory (individual / dyad / group / organization / field)

Proposition discipline

  • A proposition states a relationship between constructs, not an empirical magnitude.
  • Every proposition is preceded by its logical argument; the proposition is the summary of an argument already made.
  • Propositions build on each other; later ones may depend on earlier constructs.
  • Keep them theoretical (P: "the stronger A, the more likely B, because mechanism M"), never operational ("A measured by survey predicts B at p<.05").
  • Never write "H1" or "supported / not supported" — that support/rejection vocabulary is AMJ's, not AMR's. Each proposition should be testable in principle (AMR's scope: "testable knowledge-based claims") but you do no testing.

Exemplar

Oliver's "Strategic Responses to Institutional Processes" (AMR 1991, DOI 10.5465/amr.1991.4279002) builds a typology of five responses (acquiescence, compromise, avoidance, defiance, manipulation) and derives propositions linking antecedent conditions (cause, constituents, content, control, context) to them — defined constructs, explicit mechanisms, numbered propositions, stated boundaries, and not a single datum.

Checklist

  • Every construct has a definition, a domain, and a distinction from neighbors
  • All assumptions are stated explicitly
  • Each relationship's form is specified (causal / recursive / moderating / mediating / constitutive)
  • Each proposition has an explicit mechanism behind it
  • Propositions are numbered and each is earned by a preceding argument
  • Boundary conditions specify where the theory holds and fails
  • Level(s) of theory are consistent (or level shifts are theorized, not accidental)

Anti-patterns

  • Propositions stated as bullet points with no preceding logical argument
  • A new construct that is an old construct with a new name
  • "X affects Y" with no specified form and no mechanism
  • Assumptions left implicit, then exposed by reviewers
  • A "process model" figure standing in for the theoretical argument it should summarize
  • Boundary conditions written as apologies ("limited to...") rather than as theory
  • Smuggling in empirical claims ("data show...") — AMR has no data

Output format

【Constructs】[name: definition / domain / distinction / level] for each
【Assumptions】[explicit list]
【Relationships】[construct → construct : form + mechanism]
【Propositions】P1...Pn (each with one-line mechanism)
【Boundary conditions】where the theory holds / fails
【Next step】amr-methods (refine construction) → amr-data-analysis (logic check)

Frequently asked questions

What does the Amr Theory Development AI skill do?

Use when building the actual theory for an Academy of Management Review (AMR) manuscript — turning a positioned puzzle into defined constructs, explicit relationships, propositions, and boundary conditions. Constructs the theory; it does NOT stress-test the argument's logic (that is amr-data-analysis) or design any data collection (AMR has none).

Why use Amr Theory Development on TypingMind?

Because you install it once and use it with any model. Amr Theory Development 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 Amr Theory Development 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-Review-Skills/skills/amr-theory-development. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Amr Theory Development?

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 Amr Theory Development?

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

Is the Amr Theory Development 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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