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Abstract Writing

Community
msimchowitz
abstract-writing

Draft, revise, or diagnose research-paper abstracts as compact arguments written for readers rather than section-by-section summaries. Use for an abstract-only request, a conference or journal abstract, an arXiv abstract, or an abstract that reads like a contribution inventory, paper announcement, or compressed table of contents.

Overview

Publishermsimchowitz
Repositorywriting-skills
Skill nameabstract-writing
Stars
67
Forks
4
Bundled files
2
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.

  • 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 msimchowitz on GitHub. Read the source before you install it.

Installation

Install the Abstract 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/abstract-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/abstract-writing .claude/skills/abstract-writing
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Abstract 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 Abstract 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 Abstract 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.

Abstract Writing

Write the abstract so that a reader can understand the paper's central problem, answer, evidence, and demonstrated scope without seeing the rest of the manuscript. Do not give every section or contribution equal space.

Read The Evidence First

  1. Read the current abstract and the title.
  2. Read the introduction, headline results, conclusion, and limitations when they are available. Inspect the decisive figure, theorem, or experiment behind each abstract claim.
  3. Treat the manuscript and any example corpus selected for the task as voice evidence. Never infer a result, comparison, number, or limitation from a generic abstract pattern.
  4. When matching the Simchowitz-group research voice, read example-abstract-patterns.md.
  5. When no stronger voice sample governs the task, read the sibling academic-voice skill.

If only notes are available, distinguish planned work from completed work. Ask for a missing result when the abstract would otherwise imply evidence that the notes do not contain.

Build One Inferential Arc

Before drafting, state these elements in plain language:

  1. the concrete problem or successful practice;
  2. the limitation, tension, or missing explanation;
  3. the paper's central answer;
  4. the strongest evidence for that answer;
  5. the conditions or limitations that determine its scope; and
  6. the change in understanding or design that follows.

Use only the elements needed to understand the argument. Merge adjacent moves when they express one relation. Reorder them when a result-led opening gives the reader a clearer path. Do not force a separate limitation sentence when the comparator, regime, assumptions, or validation setting already makes the scope clear.

Draft For Understanding

  • Establish the tension before naming a method whose purpose would otherwise be unclear.
  • Explain the conceptual move before listing algorithmic components.
  • Give the headline result enough context to interpret the comparison, guarantee, or mechanism.
  • Prefer one decisive comparison to a catalog of benchmarks, settings, and implementation details.
  • Separate direct evidence from a proposed explanation. Use "shows" or "demonstrates" for direct evidence, "supports" for partial evidence, and "suggests" or "is consistent with" for interpretation.
  • End on the supported implication, design consequence, or limitation that changes the reader's understanding. Do not end by announcing code, future work, or another contribution unless that information matters to the venue.
  • Read the final two sentences together. The last sentence should complete the abstract's inferential arc rather than repeat the previous claim at a higher level of abstraction. If the penultimate sentence already provides the natural ending, stop there.
  • Do not force uplift or finality. An earned limitation, unresolved question, or precise statement of scope can close an abstract more naturally than a generic implication.

Avoid wrappers such as "This paper presents," "On the empirical side," "On the theoretical side," and "Beyond proposing." They describe the document's inventory instead of explaining the argument. Do not force the draft into a fixed number of sentences or equal-length contribution blocks.

Protect The Claim Boundary

Check every sentence against the manuscript:

  • Does the abstract name the same comparator, regime, metric, and uncertainty as the supporting result?
  • Does a mechanism claim remain a hypothesis when the evidence is correlational or indirect?
  • Does the scope include the conditions needed to interpret the result?
  • Do limitations qualify the exact claim they constrain?
  • Does the abstract omit interesting details that do not help a reader understand the central answer?

Use literal verbs for claims, evidence, and sections. A claim may hold, apply, depend on an assumption, or have limitations; it does not "stop," "want," or "do the work."

Revise The Cadence

Let sentence length follow the argument. A long sentence can hold a claim and its essential condition when the relation stays clear. A short sentence should carry real emphasis, not manufacture urgency. Avoid repeated sentence openings, contribution announcements, and several consecutive sentences with the same clause structure.

After the claim audit, run the complete sibling general-writing workflow once. It applies Humanizer and the shared cadence pass. Recheck every comparison, qualifier, number, citation, and claim boundary after the prose edit.

Return To The Abstract After The Body Is Final

For an abstract attached to a longer work, revisit it after the title, body, headline results, conclusion, and limitations are stable.

  1. Compare every abstract sentence with the final work.
  2. Confirm that the abstract represents the main points as one inferential arc, not as a tour of sections.
  3. Remove claims that are no longer central, and add any central supported result or limitation that the final revision made necessary.
  4. Rework the last sentence if the final body changes the implication, scope, or most natural point of closure.

For an abstract-only task, use the final evidence and notes as the completed body, then perform the same check.

Final Abstract Audit

  • Can a reader state the problem and central answer after one reading?
  • Does the abstract explain why the intervention or analysis resolves the stated tension?
  • Is the strongest evidence visible without a benchmark inventory?
  • Does each method detail help interpret a result?
  • Does the ending state a supported consequence or boundary rather than recap the paper?
  • Would deleting the final sentence make the abstract stronger? If so, cut it or replace it with the consequence, boundary, or unresolved point that the preceding evidence actually supports.
  • Does the paragraph sound continuous when read at speaking pace?

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 Abstract Writing AI skill do?

Draft, revise, or diagnose research-paper abstracts as compact arguments written for readers rather than section-by-section summaries. Use for an abstract-only request, a conference or journal abstract, an arXiv abstract, or an abstract that reads like a contribution inventory, paper announcement, or compressed table of contents.

Why use Abstract Writing on TypingMind?

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

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

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

Is the Abstract 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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