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Amr Submission

Community
franklee16
amr-submission

Use when running the final pre-submission preflight for an Academy of Management Review (AMR) manuscript — ScholarOne portal, AOM format and length, abstract, anonymization for review, references, ethics/originality, and required files. Theory-only journal; there is no data-availability or replication step.

Overview

Publisherfranklee16
Repositoryacademic-research-skills
Skill nameamr-submission
Stars
225
Forks
34
Bundled files
2
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.

  • 2 bundled files

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

  • Open source

    Published by franklee16 on GitHub. Read the source before you install it.

Installation

Install the Amr Submission 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-submission
  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-submission .claude/skills/amr-submission
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Amr Submission 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 Submission 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 Submission 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.

Pre-Submission Preflight (amr-submission)

AMR is theory-only. There is no dataset, code, or replication package to deposit. The preflight centers on the theory paper's format, anonymization, and AOM ethics — not on empirical materials.

When to trigger

  • "I'm about to submit to AMR"
  • Final check before clicking submit in ScholarOne
  • Unsure which files the portal expects for a conceptual paper

Pre-submission checklist

Scope & fit

  • The paper builds new theory (constructs / process model / reconceptualization), not an empirical study
  • It enters and "challenges and extends" a specific theoretical conversation
  • There is no data, no measures, no statistical test anywhere in the manuscript
  • Fit confirmed against the current AMR aims & scope (verify on the official page)

Format (verify exact current requirements on the AOM author page)

  • Manuscript double-spaced, standard margins and 12-pt font
  • Title page separate from the manuscript body (for anonymous review)
  • Abstract present and within the journal's word limit (verify current limit)
  • Within the journal's overall length expectation (verify; AMR articles are full-length)
  • Figures meet AOM resolution/format specs; each is a conceptual model/typology, not a data plot
  • Propositions numbered consistently and matched to the figure

Anonymization for double-anonymous review

  • No author-identifying content in the manuscript body
    • Self-citations phrased neutrally ("prior work (Author, 2020)"), not "in our earlier paper"
    • Acknowledgments removed from the body (added after acceptance)
    • Funding/grant identifiers kept out of the body
  • Document file properties scrubbed of author name/affiliation
  • File names contain no author or institution name

References & citations

  • APA-style author–date in-text citations; full reference list per the AOM (APA-derived) Style Guide (APA edition UNVERIFIED — confirm; see source map)
  • Every in-text citation appears in the reference list and vice versa
  • The recent, live conversation in the target stream is cited, not only seminal works
  • All references are real and accurately quoted (no fabricated or mis-cited sources)

Ethics & originality (AOM Code of Ethics)

  • Manuscript is original, unpublished, and not under review elsewhere
  • Authorship reflects genuine intellectual contribution; order agreed by all authors
  • Any prior conference/working-paper version is disclosed as required
  • Similarity check run (institutional tool); overlap acceptable and self-overlap disclosed

Portal files (ScholarOne)

  • Anonymized main manuscript (body + figures + references), required format
  • Separate title page with author info and corresponding author
  • Cover note / response to editor if requested
  • Any author-agreement or conflict-of-interest forms the system requires

Desk-reject triggers to preempt

  1. It's an empirical study (reports data, tests hypotheses) — the defining AMR desk reject.
  2. Incremental theory — a minor extension with no new construct or mechanism.
  3. A literature review with no original theoretical move (AMR is not a review journal).
  4. Construct proliferation — relabeling existing ideas (cf. Suddaby, AMR 2010, DOI 10.5465/amr.2010.0419).
  5. Untestable-in-principle or tautological propositions (AMR's scope demands "testable knowledge-based claims").
  6. Poor fit/scope or anonymization/formatting failures.

ScholarOne operation notes

  • AMR uses ScholarOne Manuscripts (Manuscript Central); register and submit through the AMR portal linked from journals.aom.org/journal/amr (exact URL — confirm; see source map).
  • Enter author metadata only in the system, never in the anonymized manuscript.
  • Suggested/opposed reviewers: provide only if the system asks and per its limits.
  • Choose the correct submission/article type (theoretical/conceptual article).
  • Submission fee: none — the Academy of Management does not charge submission fees (verified at aom.org, 2026-05). AOM membership to submit: confirm on the AOM author guidelines (not assumed).
  • Keep within the file-size and file-type limits the portal states.

Anti-patterns

  • Submitting a paper that is really an empirical study or a literature review
  • Author identity leaking through "our prior study," acknowledgments, or file properties
  • Reference list missing the recent conversation reviewers belong to
  • Figures that are data plots (impossible at AMR) or undefined boxes-and-arrows
  • Forgetting to scrub document metadata after a final edit
  • Over-length manuscript that ignores the current limit (verify before submitting)

Output format

【Scope】builds new theory, no data: yes / fix
【Format】double-spaced / abstract within limit / figures conceptual: pass / fix
【Anonymization】body + properties + filenames clean: yes / fix
【References】AOM style; recent conversation cited; all real: yes / fix
【Ethics】original, not under review, authorship correct: yes / fix
【Portal files】anonymized MS + title page + forms: complete / missing [...]
【Next step】await decision → amr-review-process; R&R → amr-rebuttal

Related resources

  • templates/manuscript_template.md — Standard AMR conceptual-article skeleton (puzzle intro, theory development, propositions, conceptual model, discussion)
  • templates/checklist.md — 8-section pre-submission self-check (scope / format / anonymization / abstract / theory / figures / references / ethics & portal)
  • ../../resources/external_tools.md — Theory-building tools (citation mapping, reference managers, conceptual-diagram software, argument-logic aids)

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 Amr Submission AI skill do?

Use when running the final pre-submission preflight for an Academy of Management Review (AMR) manuscript — ScholarOne portal, AOM format and length, abstract, anonymization for review, references, ethics/originality, and required files. Theory-only journal; there is no data-availability or replication step.

Why use Amr Submission on TypingMind?

Because you install it once and use it with any model. Amr Submission 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 Submission 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-submission. 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 Amr Submission?

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 Submission?

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

Is the Amr Submission 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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