Amr Workflow

Community

franklee16

amr-workflow

Use when deciding which amr-* sub-skill to invoke next, or when sequencing a theory-building manuscript from theoretical-puzzle framing through developmental-review revision for an Academy of Management Review (AMR) submission. Routes — does not replace — the specialized skills.

Overview

Publisher	franklee16
Repository	`academic-research-skills`
Skill name	`amr-workflow`
Stars	225
Forks	34
Bundled files	Instructions only
Links	Skill source Repository

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

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.

Open the app and go to Plugins → Skills.
Choose "Install from GitHub".
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-workflow
Enable the skill in any chat where you want it available.

Store

Installed

Skills

Add skills

Import one or more skills from a public GitHub folder or a local .skill or .zip archive, or SKILL.md file.

From GitHub URLFrom .skill, .zip, or SKILL.md

GitHub repo or folder

https://github.com/franklee16/academic-research-skills/tree/master/Awesome-Journal-Skills-main/Academy-of-Management-Review-Skills/skills/amr-workflow

Points to a single skill folder, or any folder that contains multiple skills. Public repos only.

CancelContinue

Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.

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-workflow .claude/skills/amr-workflow

Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Amr Workflow 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 Workflow 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 Workflow 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.

AMR Theory-Building Workflow (amr-workflow)

Overview

This is the router. It does not replace any specialized skill — it tells you which amr- skill to use at the current stage* of an Academy of Management Review manuscript.

Default assumption: unless the user says otherwise, treat the target as AMR — the Academy of Management's premier theory-development journal. AMR publishes conceptual articles that build new theory; per its scope, submissions "must extend theory in ways that develop testable knowledge-based claims." It contains no datasets, no hypothesis tests, no results section — empirical hypothesis-testing is the lane of its sibling AMJ. The deliverable is a genuinely new theoretical contribution: new constructs, a new process model, or a reconceptualization — developed with rigorous logic, explicit assumptions, propositions, and boundary conditions. If the project has data and tests, it belongs at AMJ / ASQ / SMJ, not AMR.

The AMR contribution bar is set by two AMR-published editorials worth keeping in view at every stage: Whetten's "What Constitutes a Theoretical Contribution?" (1989, DOI 10.5465/amr.1989.4308371) — the What/How/Why/Who-Where-When rubric — and Suddaby's "Editor's Comments: Construct Clarity in Theories of Management and Organization" (2010, DOI 10.5465/amr.2010.0419). Pure-theory exemplars built by argument alone: Oliver, "Strategic Responses to Institutional Processes" (1991, DOI 10.5465/amr.1991.4279002); Dyer & Singh, "The Relational View" (1998, DOI 10.5465/amr.1998.1255632). References follow APA-style (AOM house style).

When to trigger

The user asks "what should I do next?" on a conceptual paper
A draft arrives and you must locate its bottleneck (puzzle? logic? contribution?)
Work is thrashing between theorizing, figure-building, and writing
An AMR decision letter (developmental review) has arrived and the work shifts to revision

Routing table

Current symptom	Next skill
Idea is vague; not sure there is a real theoretical puzzle	`amr-topic-selection`
Have a puzzle but constructs/relationships/logic are not built	`amr-theory-development`
Unsure which conversation to enter or what to "challenge"	`amr-literature-positioning`
Propositions exist but the construction method feels thin	`amr-methods`
Propositions stated but underlying logical argument is missing	`amr-data-analysis`
Cannot articulate what is NEW vs. prior theory	`amr-contribution-framing`
Box-and-arrow figure has no mechanism / typology not earning its keep	`amr-tables-figures`
Prose reads like a literature review, not an argument	`amr-writing-style`
Ready to submit; need the ScholarOne preflight	`amr-submission`
Want to understand AMR's developmental, multi-round review	`amr-review-process`
Received an R&R; need to write the response document	`amr-rebuttal`

Default order

amr-topic-selection — lock the theoretical puzzle (the "why doesn't existing theory explain this?")
amr-literature-positioning — identify the conversation to challenge and extend
amr-theory-development — build constructs, relationships, propositions, boundary conditions
amr-methods — theory-construction craft: construct domains, mechanisms, assumptions
amr-data-analysis — argument development: logic checks, counterfactuals, alternative explanations
amr-contribution-framing — differentiate the new theory from prior work
amr-tables-figures — finalize the conceptual figure / typology / propositions table
amr-writing-style — AOM house style; argument-driven prose (polish)
amr-submission — ScholarOne preflight
amr-review-process — understand the developmental review you are about to enter
amr-rebuttal — after the R&R

amr-writing-style is a late-stage polish. Do not polish prose before the theory's logic stands up (amr-data-analysis) and the contribution is differentiated (amr-contribution-framing).

Decision shortcuts

"I have an interesting phenomenon but no theory" → amr-topic-selection
"I don't know whose theory I'm arguing with" → amr-literature-positioning
"I have propositions but no logic connecting them" → amr-data-analysis
"My P1–P5 read like assertions" → amr-theory-development then amr-data-analysis
"A reviewer will ask 'what's new here?'" → amr-contribution-framing
"My model figure is boxes and arrows with no mechanism" → amr-tables-figures
"It reads like a review essay" → amr-writing-style
"I'm about to hit submit" → amr-submission
"I got a Reject & Resubmit / Major Revision" → amr-review-process then amr-rebuttal

Differences vs. AMJ / ASQ / SMJ skill stacks

If the manuscript has data, measures, and statistical tests, an empirical-management stack (AMJ / ASQ / SMJ) fits better. The core split:

AMR: builds theory; the contribution IS the theory; no data; propositions, not hypotheses tested.
AMJ / ASQ / SMJ: test theory; hypotheses, samples, estimation, results.

A common failure is sending an AMR draft that is really an under-powered empirical paper, or an AMJ draft whose "theory" is a literature summary. Pick the right stack early.

Anti-patterns

Do not skip amr-literature-positioning and jump to building — reviewers first ask whose conversation you are in.
Do not let amr-tables-figures pretty up a model before the propositions and mechanisms exist.
Do not let amr-rebuttal draft a response before the theory itself has actually been revised.
Do not treat AMR as a venue for data; route empirical work elsewhere.

Volatile specifics (editor-in-chief, exact length/abstract limits, fees, APA edition, acceptance rate) change or could not be machine-verified — see resources/official-source-map.md and confirm on the official AMR / AOM author page.

Frequently asked questions

What does the Amr Workflow AI skill do?

Why use Amr Workflow on TypingMind?

Because you install it once and use it with any model. Amr Workflow 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 Workflow 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-workflow. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Amr Workflow?

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 Workflow?

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

Is the Amr Workflow 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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Overview

Installation

Install in TypingMind

Install in another agent

Use it in TypingMind

Works with any AI model

Skill instructions

AMR Theory-Building Workflow (amr-workflow)

Overview

When to trigger

Routing table

Default order

Decision shortcuts

Differences vs. AMJ / ASQ / SMJ skill stacks

Anti-patterns

Frequently asked questions

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