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Paper Writing

Community
msimchowitz
paper-writing

Plan, draft, revise, and structure technical research papers while preserving claims, notation, evidence, citations, and author voice. Use for abstracts, introductions, related work, methods, theory, experiments, results, discussions, conclusions, figures, appendices, LaTeX project organization, or whole-manuscript design.

Overview

Publishermsimchowitz
Repositorywriting-skills
Skill namepaper-writing
Stars
67
Forks
4
Bundled files
21
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.

  • 21 bundled files

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

  • Open source

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

Installation

Install the Paper Writing 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/msimchowitz/writing-skills/tree/main/for-agents/paper-writing
  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/msimchowitz/writing-skills.git /tmp/writing-skills
mkdir -p .claude/skills
cp -r /tmp/writing-skills/for-agents/paper-writing .claude/skills/paper-writing
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Paper Writing 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 Paper Writing 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 Paper Writing 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.

Paper Writing

Preserve the facts and evidence supplied for the task. Never invent citations, experiments, quantitative results, theorem conditions, novelty claims, or completed revisions.

The ../../for-humans/human-writing-guide/ directory is a companion written for people, not an agent skill. For ordinary drafting, use this skill and its focused references. When the user asks how to use the bundled OGPO-derived LaTeX template, wants material for teaching or onboarding, or asks for a human-readable explanation, consult or point them to the relevant part of the human guide. If that companion is not present in an installed copy, continue with this skill's bundled references. Never route to the guide as though it were a skill.

Select The Workflow

  • For an abstract-only request, read and follow the sibling abstract-writing skill. Let that skill own the final general-writing pass so the prose pipeline runs once.
  • For other drafting or revision of scholarly prose, read the sibling academic-voice skill before the relevant paper-specific references.
  • For a new paper or major restructure, copy paper-plan.md into the project and complete it before drafting.
  • For a theory-led paper, use theory-paper-outline.md.
  • For an empirical method or mechanism paper, use empirical-paper-outline.md.
  • For a figure plan or figure review, use figure-storyboard.md.
  • For the Simchowitz-group paper patterns distilled from DPPO, OGPO, Much Ado About Noising, and Action Chunking, read group-paper-conventions.md.
  • For drafting or line-editing paper prose, read sentence-style.md before writing.
  • For LaTeX structure, venue styles, project styles, toggles, macros, and source hygiene, read latex-project-conventions.md. For the exact theorem environments, heading toggles, algorithm-name macros, revision colors, title metadata, and other conventions in the bundled OGPO-derived template, also consult the template chapter in the human guide when it is present. Copy latex-paper-skeleton only when creating a new LaTeX project. Rename its paper-main.tex entry point to a stable, descriptive <project-name>-main.tex before drafting. Adapt an existing repository in place otherwise.

Resolve Optional Example Papers

The bundled paper conventions are sufficient by default. When the task calls for inspecting original examples, such as matching the author's established voice or checking a distilled convention:

  1. Use an example directory explicitly supplied for the current task.
  2. If no directory was supplied, ask: "Where is the folder containing the example papers for this task? You can say none to use the bundled conventions."
  3. Accept a direct corpus directory under any name. Also accept a parent directory containing the conventional example-papers child.
  4. Confirm that the resolved directory is readable before relying on it.
  5. If the user answers none or the directory is unavailable, use group-paper-conventions.md and say that the original papers were not inspected.

Do not search above the repository, infer a location from the user's home directory, or copy private examples into this repository.

Build The Argument Before The Prose

  1. State the practical or scientific problem in one sentence.
  2. State why the strongest current explanation or method is insufficient.
  3. State the paper's central claim, demonstrated scope, and main limitation.
  4. Build a claim-evidence map. Assign every major claim a theorem, controlled comparison, ablation, mechanism study, qualitative result, or explicit limitation.
  5. Choose the paper architecture from the evidence rather than from a fixed section list.
  6. Give each section one question to answer and each paragraph one inferential job.
  7. Design Figure 1 as a compact version of the full argument, then make every later figure resolve one question left open by Figure 1.
  8. Draft from the strongest evidence outward. Write the abstract and title only after the claim hierarchy is stable.

Treat the abstract as a reader's first encounter with the argument, not as a compressed table of contents. It should establish the problem, central answer, decisive evidence, and the conditions that govern the extent of the claim. Do not give every section, benchmark, or implementation detail equal space.

Use Claim-Led Sections

  • Prefer informative section titles that state the result or question.
  • Put setup before the first result that needs it, but do not front-load every definition.
  • Present headline performance before mechanism studies and low-level ablations in empirical papers.
  • Present the motivating failure or impossibility before the intervention in theory papers.
  • Place related work early only when distinctions from prior methods are required to understand the approach. Otherwise place it after the main results to preserve momentum.
  • Move implementation detail, full proofs, complete sweeps, hyperparameters, and secondary controls to the appendix while keeping decision-critical evidence in the main paper.
  • End with supported scope, concrete limitations, and open questions. Do not introduce a new contribution in the conclusion.

Write In A Direct Technical Voice

  • Use active first-person verbs: "we show," "we find," "we compare," and "we hypothesize."
  • Build contrast explicitly: established view, observed failure, new finding, consequence.
  • Name the comparator, metric, regime, and evidence before interpreting a result.
  • Distinguish direct evidence from interpretation and proposed mechanism.
  • Use "shows" or "demonstrates" only for direct evidence; use "supports," "suggests," or "is consistent with" for partial evidence.
  • Use bold or italics to expose argumentative structure, not to decorate most sentences.
  • Prefer concrete claims over generic statements of importance.
  • Keep notation and method names semantic and consistent through macros.

Preserve Technical Integrity

  • Read the relevant manuscript, source, figures, captions, and appendix before editing claims.
  • Preserve notation, assumptions, theorem quantifiers, experimental settings, citations, and calibrated uncertainty.
  • Check that a figure caption and the surrounding paragraph make the same claim.
  • Check that every abstract claim appears in the main paper and that every introduction contribution has visible evidence.
  • Check the abstract separately from the body. Verify its inferential arc, evidence verbs, quantitative comparisons, and claim boundary against the supporting sections.
  • Surface unresolved logical gaps or missing controls instead of writing around them.
  • Make the minimum structural change needed unless the user requests a larger rewrite.

Run The Final Voice Pass

After the argument, claims, notation, citations, and section order are stable:

  1. Read sentence-style.md.
  2. Treat the current manuscript and any selected example papers as voice evidence.
  3. Read the sibling general-writing skill and its evaluation checklist.
  4. Run its complete edit workflow. It invokes Humanizer in embedded mode before applying the house-style check, so do not run Humanizer separately.
  5. Recheck every edited comparison, qualifier, number, citation, symbol, and claim boundary against the source.
  6. After the body, conclusion, and limitations are final, return to the abstract and apply abstract-writing's end-of-document check. Confirm that it represents the paper's final main points rather than an earlier draft or a section inventory.

Use general-writing as the prose enforcer, not as authority to simplify away technical meaning. Preserve a term that is technically necessary even if it appears on a general avoid-list. Preserve a logical contrast while removing canned binary phrasing. The final house-style check may restore a construction that Humanizer removed when the manuscript or example corpus shows that it is part of the author's technical voice.

Report substantive changes to claims, evidence, or section structure separately from line edits.

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 Paper Writing AI skill do?

Plan, draft, revise, and structure technical research papers while preserving claims, notation, evidence, citations, and author voice. Use for abstracts, introductions, related work, methods, theory, experiments, results, discussions, conclusions, figures, appendices, LaTeX project organization, or whole-manuscript design.

Why use Paper Writing on TypingMind?

Because you install it once and use it with any model. Paper Writing 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 Paper Writing in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/msimchowitz/writing-skills/tree/main/for-agents/paper-writing. 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 Paper Writing?

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 Paper Writing?

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

Is the Paper Writing AI skill free?

Yes. It is published on GitHub by msimchowitz 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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