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Amj Submission

Community
franklee16
amj-submission

Use when running the final pre-submission preflight for an Academy of Management Journal (AMJ) manuscript — ScholarOne portal, anonymization for double-blind review, AOM house-style formatting, files, and ethics declarations. Checks readiness to submit; it does not handle the post-decision response (amj-rebuttal).

Overview

Publisherfranklee16
Repositoryacademic-research-skills
Skill nameamj-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 Amj 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-Journal-Skills/skills/amj-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-Journal-Skills/skills/amj-submission .claude/skills/amj-submission
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Amj 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 Amj 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 Amj 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 (amj-submission)

When to trigger

  • "We're submitting this week" — the last check before hitting submit
  • Unsure what ScholarOne requires (anonymized manuscript, title page, cover materials)
  • Need to confirm double-blind anonymization is complete
  • Verifying the manuscript matches current AMJ/AOM formatting requirements

Always re-verify current limits and required files on the official AMJ submission page and the AOM Style Guide before submitting — specifics change. As of 2026-05-30 the verified key specs are below.

Verified AMJ/AOM specs (confirm current values)

  • Length: full manuscripts have a 40-page maximum for the main body, which includes text, references, and appendices but excludes tables and figures. (AOM uses a page limit, not a word cap.)
  • Formatting: double-spaced throughout (including references and notes), Times New Roman 12-point, 1-inch margins on all sides, pages numbered consecutively.
  • Abstract: no more than 200 words.
  • Keywords: three keywords supplied at submission.
  • Submission portal: ScholarOne Manuscripts at mc.manuscriptcentral.com/AMJ.
  • Review: blind review; desk review typically takes ~1-2 weeks, and AMJ targets developmental feedback to authors within roughly 60 days. Authors who submit are expected to reciprocate by reviewing for AMJ when asked.
  • Style: APA conventions per the AMJ Style Guide for Authors (citations, reference list, headings, tables).
  • Integrity: manuscripts are screened with iThenticate; no simultaneous submission; any preprint posted online must be removed during the review period.
  • Fees: AOM charges no submission fee; immediate open access is optional and carries an APC of US$3,500 (AMJ is otherwise subscription-published). Verify current amounts.
  • AI disclosure: any use of AI tools must be disclosed in the cover letter and the acknowledgements, with confirmation that you have read the AOM AI policy; AI cannot be listed as an author.

Pre-submission checklist

Anonymization (double-blind)

  • Manuscript file contains no author names, affiliations, or acknowledgments
  • Self-citations are worded neutrally ("prior research (Author, 2020)"), not "our earlier work"
  • Acknowledgments, funding, and author bios live on a separate title page, not in the manuscript
  • File metadata/properties scrubbed of author identity
  • File names contain no author or institution identifiers

Format (verify against the current AOM Style Guide)

  • Title page (separate): title, authors, affiliations, contact, acknowledgments, funding
  • Abstract ≤ 200 words; three keywords supplied
  • AOM/APA-style citations and reference list, alphabetized and complete
  • Headings follow the AOM hierarchy; double-spaced, Times New Roman 12-pt, 1-inch margins
  • Tables and figures placed/numbered as the portal requires; each self-contained
  • Main body ≤ 40 pages (text + references + appendices; tables/figures excluded)

Files for ScholarOne

  • Anonymized main document (manuscript + tables + figures, or as the portal specifies)
  • Separate title page with all identifying information
  • Cover letter to the editor (concise: fit, contribution, not under review elsewhere)
  • Any required supplementary/online appendix files
  • High-resolution figure files if requested separately

Declarations & ethics

  • Human-subjects/IRB approval stated where applicable (separate from anonymized text)
  • Data-availability/transparency statement as required by current policy
  • No concurrent submission; prior conference/working-paper versions disclosed in the cover letter
  • AI use disclosed in the cover letter and acknowledgements per the AOM AI policy (AI is never an author)
  • Conflicts of interest and funding disclosed on the title page
  • Authorship and contribution roles agreed by all authors

References & consistency

  • Every in-text citation appears in the reference list and vice versa
  • Canonical theory works for the focal domain are cited (a frequent reviewer check)
  • Hypothesis labels, construct names, and table/figure numbers are consistent throughout

ScholarOne operation notes

  • AMJ submits through ScholarOne Manuscripts at mc.manuscriptcentral.com/AMJ; create/keep your author account and ORCID current.
  • Select the correct article type and the most fitting division/keywords so the manuscript routes to an appropriate action editor.
  • You may be asked to suggest qualified, non-conflicted reviewers — propose people in the focal conversation without recent co-authorship.
  • Upload anonymized files and the title page in the slots the system designates; preview the built PDF before final submission.

Anti-patterns

  • Submitting with self-identifying language ("in our 2019 study") intact.
  • Acknowledgments/funding left inside the anonymized manuscript.
  • Reference list in a non-AOM default style straight from the reference manager.
  • Missing data-availability/ethics statement, or undisclosed AI use, where the policy requires one.
  • Inconsistent hypothesis labels or table numbers between text and exhibits.
  • Letting the main body exceed the 40-page limit by forgetting that references and appendices count toward it.

Output format

【Anonymization】pass / fix: [...]
【Format vs. AOM guide】pass / fix: [...]
【Files ready】manuscript / title page / cover letter / supplements: yes/no
【Declarations】IRB / data availability / disclosures: complete? [...]
【References】citations↔list reconciled; canonical theory cited: yes/no
【Article type & division】selected ...
【Next step】await decision → amj-review-process; on R&R → amj-rebuttal

Resources

  • templates/manuscript_template.md — full AMJ manuscript skeleton (title page, abstract ≤200 words, three keywords, theory & hypotheses, methods, results, discussion, references) with verified AOM format specs
  • The full pre-submission self-check (anonymization / format / files / declarations / references / portal) is inline above in this skill
  • ../../resources/external_tools.md — management-research data sources and analysis software (Mplus / R lavaan / HLM / Stata / SPSS PROCESS)
  • ../../resources/official-source-map.md — official AOM/AMJ URLs behind every verified fact in this pack (accessed 2026-05-30)

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 Amj Submission AI skill do?

Use when running the final pre-submission preflight for an Academy of Management Journal (AMJ) manuscript — ScholarOne portal, anonymization for double-blind review, AOM house-style formatting, files, and ethics declarations. Checks readiness to submit; it does not handle the post-decision response (amj-rebuttal).

Why use Amj Submission on TypingMind?

Because you install it once and use it with any model. Amj 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 Amj 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-Journal-Skills/skills/amj-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 Amj 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 Amj Submission?

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

Is the Amj 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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