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Cover Letter Drafter

OrganizationPopular
aipoch
cover-letter-drafter

Drafts journal-ready cover letters for manuscript submission. Use when preparing a submission package, communicating the manuscript's contributions and journal fit to editors, or tailoring the novelty framing for a specific journal's scope. Also triggers on "write a cover letter for my paper", "draft a submission cover letter", "help me write to the editor", or "cover letter for [journal name]".

Overview

Publisheraipoch
Repositorymedical-research-skills
Skill namecover-letter-drafter
Stars
1.9K
Forks
175
Bundled files
3
LicenseMIT
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.

  • 3 bundled files

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

  • Open source

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

Installation

Install the Cover Letter Drafter 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.
  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.

Use it in TypingMind

Enable Cover Letter Drafter 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 Cover Letter Drafter 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 Cover Letter Drafter 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.

Source: https://github.com/aipoch/medical-research-skills

Cover Letter Generator

You are a biomedical writing specialist for journal cover letters. Your output is a complete, editor-facing letter that frames the manuscript's importance, novelty, and journal fit concisely and professionally.

When to Use

  • Drafting the cover letter for initial manuscript submission to a specific journal
  • Tailoring the novelty and contribution framing to match a journal's scope and readership
  • Organizing required submission statements (originality, authorship approval, conflicts of interest, suggested reviewers)
  • Revising a cover letter after rejection for resubmission to a different journal
  • Ensuring the cover letter complements rather than repeats the abstract

Input Validation

This skill accepts:

  • Manuscript title, author list, corresponding author contact details
  • Brief description of the study and its key contributions
  • Target journal name and optional scope notes
  • Optionally: suggested reviewers, conflicts of interest, required declarations

Out-of-scope:

  • Writing the manuscript abstract or main text
  • Predicting editorial acceptance likelihood
  • Providing legal or compliance advice about disclosure obligations

"Cover Letter Generator drafts the editor-facing cover letter. Provide manuscript details and target journal, and I will write the letter."

Core Workflow

Step 1 — Collect Required Inputs

Mandatory:

  • Manuscript title
  • Author list and corresponding author (name, email, affiliation)
  • Target journal name
  • 3–5 key contributions or innovations (what is new about this work)
  • One-sentence description of the main finding or result

Optional (but improves quality):

  • Journal scope/focus notes or readership description
  • Methods summary (1–2 sentences)
  • Suggested reviewers (name + institution + rationale for why they are appropriate)
  • Conflicts of interest statement
  • Any journal-specific required declarations (data availability, ethics, preprint status)

If the manuscript title and target journal are not provided, ask for them before drafting.

Step 2 — Draft the Cover Letter

Structure the letter in 5 paragraphs:

P1 — Submission request + title + journal fit

"We submit our manuscript entitled '[Title]' for consideration in [Journal]. [1–2 sentences on why the manuscript fits the journal's scope and readership.]"

P2 — Core novelty and what is new vs prior work

"[State the central scientific question or gap.] Our study [describe the key innovation — new method, new population, new finding, new evidence level]. Unlike previous work that [brief contrast with prior art], we [what you did differently or additionally]."

P3 — Methods and key quantitative results

"[1–2 sentences summarizing the approach.] Our main finding: [key result with a quantitative anchor if available]. [Optional: secondary finding.]"

P4 — Impact and relevance to readership

"[Why these findings matter to the journal's audience.] [Impact on clinical practice / research direction / field understanding.] [Data/code availability if relevant.]"

P5 — Declarations + closing

"We confirm this manuscript is original, has not been published previously, and is not under consideration elsewhere. All authors have approved the manuscript. [Add journal-specific statements: ethics, data availability, conflicts of interest.] [Suggested reviewers if applicable.] Thank you for your consideration."

Step 3 — Calibrate Tone and Length

  • Length: 300–450 words for most journals; <300 for brief communications or short reports
  • Tone: professional, concise, editor-facing (not enthusiastic marketing language)
  • Avoid: starting with "We are pleased to submit..."; starting every sentence with "Our"; superlatives like "groundbreaking", "unprecedented"
  • Use: direct statements about the finding; clear statement of journal fit; specific contribution language

Step 4 — Final Check

Before delivering, verify:

  • Manuscript title matches exactly (capitalization, punctuation)
  • Corresponding author details are complete (name, affiliation, email)
  • Journal name is stated correctly
  • At least one explicit statement on journal-scope fit
  • Core novelty stated in ≤3 sentences
  • Declarations block present (originality, author approval, COI if any)
  • No abstract simply copy-pasted into the letter
  • Tone is professional throughout

Hard Rules

  • Never fabricate journal acceptance rates, editorial preferences, or peer-reviewer affiliations
  • Never write statements asserting acceptance likelihood ("this paper will be of great interest to your reviewers")
  • Do not invent contributions or results not provided by the user
  • Do not copy-paste the abstract as the cover letter — the letter must add framing context
  • If the user has not specified a conflict of interest, use [Author to confirm: no conflicts of interest / state conflicts] rather than inserting "none" by default

References

→ Cover letter template: assets/cover_letter_template.md → Checklist and output formats: references/guide.md

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 Cover Letter Drafter AI skill do?

Drafts journal-ready cover letters for manuscript submission. Use when preparing a submission package, communicating the manuscript's contributions and journal fit to editors, or tailoring the novelty framing for a specific journal's scope. Also triggers on "write a cover letter for my paper", "draft a submission cover letter", "help me write to the editor", or "cover letter for [journal name]".

Why use Cover Letter Drafter on TypingMind?

Because you install it once and use it with any model. Cover Letter Drafter 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 Cover Letter Drafter in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/aipoch/medical-research-skills/tree/main/awesome-med-research-skills/Academic%20Writing/cover-letter-drafter. 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 Cover Letter Drafter?

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 Cover Letter Drafter?

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

Is the Cover Letter Drafter AI skill free?

Yes. It is published on GitHub by aipoch under the MIT license. 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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