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Write Abstract

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ShaishavMaisuria
write-abstract

Writes, rewrites, and lints venue-aware paper abstracts and prepares abstract-registration packages. Enforces venue length norms (e.g. LNCS 150-250 words), generates the correct keywords block (ACM CCS Concepts, IEEE Index Terms, LNCS \keywords, or none for NeurIPS-style), structures the abstract as motivation-gap-approach-results-impact, and builds the abstract-registration card (title, abstract, authors, topics, conflicts/COI, deadline countdown) for venues with a separate abstract deadline. Use when the user asks to write, revise, shorten, lengthen, or polish an abstract; asks about abstract word limits, CCS concepts, index terms, or keywords; or needs to register an abstract / meet an abstract-registration deadline (NeurIPS, ICML, KDD, CVPR, CHI, SIGSPATIAL) before the full-paper deadline.

Overview

PublisherShaishavMaisuria
Repositoryresearch-paper-lifecycle-skills
Skill namewrite-abstract
Stars
59
Forks
22
Bundled files
7
LicenseApache-2.0
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.

  • 7 bundled files

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

  • Open source

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

Installation

Install the Write Abstract 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/ShaishavMaisuria/research-paper-lifecycle-skills/tree/main/skills/write-abstract
  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/ShaishavMaisuria/research-paper-lifecycle-skills.git /tmp/research-paper-lifecycle-skills
mkdir -p .claude/skills
cp -r /tmp/research-paper-lifecycle-skills/skills/write-abstract .claude/skills/write-abstract
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Write Abstract 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 Write Abstract 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 Write Abstract 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.

Write Abstract

Produce a venue-compliant abstract — right length, right keywords block, five-move structure, verified numbers only — and, when the venue has a separate abstract-registration deadline, the complete registration card (title, abstract, authors, topics, COI list) ready to paste into the submission form.

When to use

  • Drafting or rewriting an abstract for a specific venue or template family (acmart / IEEEtran / llncs / NeurIPS-style).
  • Fitting an abstract to a word limit, or adding the missing CCS Concepts / Index Terms / keywords block.
  • An abstract-registration deadline is approaching and the user must register title + abstract + topics + conflicts before the paper PDF.

Related skills: tailor-to-venue (whole-paper retargeting), parse-cfp (build a missing venue profile), preflight-check (final desk-reject lint), verify-citations (gate for any reference work).

Inputs

  • The draft (main .tex preferred — keyword blocks are checked in context) or the abstract as plain text; or, for a fresh draft, the paper's contributions and verified results from the user.
  • Venue profile: venues/conferences/<id>.yml or venues/families/<f>.yml (schema: venues/schema.yml). If neither exists, do NOT invent venue facts — run parse-cfp on the CFP URL or quote the live CFP directly.

Process

1. Resolve venue norms, then re-verify (mandatory)

Load the profile (format.abstract_words, format.keywords, deadlines.abstract/paper + timezone, review.blind). Profiles go stale: before the user relies on a word limit, keyword requirement, or any deadline, re-verify it against the live cfp_url and say what was checked and when. If the CFP cannot be fetched, label every profile-derived fact "UNVERIFIED — confirm on CFP". When abstract_words is null, present 150-250 words as a convention, never as a venue rule — see references/venue-norms.md.

2. Draft (or diagnose) with the five-move structure

Build the abstract as motivation → gap → approach → results → impact, with family-appropriate tone and word budget per move: references/abstract-structure.md.

Hard rules while drafting:

  • Results numbers come from the draft's evaluation or the user — NEVER invent, round up, or extrapolate. The quantified result is the abstract's single most-predictive surface; the results→impact arc cannot score in the top band without it. If results are pending, leave exactly ONE typed quantified-result slot — a structured contract with metric name, units, sign/direction, and comparison target, e.g. [RESULT: +XX% Recall@20 vs best hashing baseline under matched budget] — never a bare [RESULT: ...] or free-text prose. Any bracketed slot leaves the abstract DRAFT-not-submittable; bind every slot with a verified value before delivery. Contract details: references/abstract-structure.md.
  • No \cite, \ref, math, or undefined acronyms in the abstract (it ships as standalone metadata). Any prior work named in prose that needs a citation elsewhere goes through verify-citations.
  • At double-blind venues, no identity leaks (institution, grant numbers, "our previous work", personal repo URLs).

For rewrites, run the linter first and let its findings drive the edit.

3. Lint deterministically

Run from the repo root (or pass absolute paths):

python3 skills/write-abstract/scripts/abstract_check.py <main.tex|abstract.txt|-> \
    --venue venues/conferences/<id>.yml [--strict]

Reports length vs the venue limit, keywords-block presence/shape, self-containedness (cite/ref/math/URL/placeholders), the typed quantified-result-slot invariant, the acmart abstract-before-\maketitle gotcha, and lexical move signals. Fix RISK and WARN findings, re-run until RISK-free. --venue also accepts a family profile when no conference profile exists.

The slot gate is non-overridable: the script prints an open-slot count and hard-fails with a non-zero exit whenever any [LABEL: ...] slot remains (independent of --strict), marking the abstract DRAFT-not-submittable. A results-pending draft passes only once its one typed RESULT slot — and any [CONFIRM: ...] slots — are bound with verified values written into the prose. Never satisfy the gate by inventing a number.

4. Generate the keywords block

Pick keywords with the user (problem + technique + domain; mirror the CFP topic list where honest — guidance in references/keywords-blocks.md), then emit the family-correct LaTeX:

python3 skills/write-abstract/scripts/keywords_block.py \
    --venue venues/conferences/<id>.yml --keywords "kw1, kw2, kw3"

For ACM venues the script emits a CCS skeleton whose concept ids MUST be filled from the official tool at https://dl.acm.org/ccs — never fabricate CCSXML concept ids. For NeurIPS-style venues it correctly emits no block (topics live in the submission form).

5. Build the registration card (when there is an abstract deadline)

If deadlines.abstract is set — NeurIPS, ICML, KDD, CVPR, CHI, SIGSPATIAL all register abstracts 2-7 days before the paper — assemble everything the form will ask for:

python3 skills/write-abstract/scripts/abstract_registration.py \
    --venue venues/conferences/<id>.yml --title "<title>" \
    --abstract-file <main.tex|abstract.txt> \
    --authors "Name <email> (Affiliation)" --topics "t1; t2" \
    [--coi-file conflicts.txt] [--track <Track>] [--out abstract-registration-<id>.md]

The card includes the deadline countdown with the venue's timezone (watch for non-AoE venues — SIGSPATIAL is Pacific Time), placeholder-policy warnings (KDD/AAAI penalize dummy abstracts), a COI checklist built from the user's recent co-authors/advisors/institutions, and the submission system URL. Help the user fill the COI list from their actual recent papers; the venue form's window and categories are authoritative. Norms: references/venue-norms.md.

6. Deliver

Present the final abstract (LaTeX + a plain-text form version), the keywords block, the linter's clean report, and — if applicable — write abstract-registration-<venue-id>.md next to the draft. State explicitly that the user registers/submits themselves.

Output

  • The abstract in LaTeX and plain text, RISK-free and with zero open slots under abstract_check.py for the target venue (a results-pending draft is delivered explicitly labeled DRAFT-not-submittable until its typed RESULT slot is bound).
  • The venue-correct keywords block (or a note that the family has none).
  • When the venue registers abstracts: abstract-registration-<venue-id>.md with title, abstract, authors, topics, COI checklist, deadline math, and a verification record.

Guardrails

  • Never fabricate results, numbers, or claims for the abstract; unverified values stay as the one typed quantified-result slot (metric, units, sign/direction, comparison target), and the abstract ships labeled DRAFT-not-submittable until every slot is bound from real data.
  • Never fabricate citations or CCS concept ids; citations go through verify-citations, CCS ids come from dl.acm.org/ccs only.
  • Never state venue limits or deadlines from memory — profile + live-CFP verification only; unverifiable facts are labeled UNVERIFIED.
  • Never register, submit, or enter anything into any submission system on the user's behalf; deliverables stop at the card.
  • Never paste another paper's abstract text as a template; exemplar study happens transiently via the study-exemplars skill.

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 Write Abstract AI skill do?

Writes, rewrites, and lints venue-aware paper abstracts and prepares abstract-registration packages. Enforces venue length norms (e.g. LNCS 150-250 words), generates the correct keywords block (ACM CCS Concepts, IEEE Index Terms, LNCS \keywords, or none for NeurIPS-style), structures the abstract as motivation-gap-approach-results-impact, and builds the abstract-registration card (title, abstract, authors, topics, conflicts/COI, deadline countdown) for venues with a separate abstract deadline. Use when the user asks to write, revise, shorten, lengthen, or polish an abstract; asks about abst...

Why use Write Abstract on TypingMind?

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

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/ShaishavMaisuria/research-paper-lifecycle-skills/tree/main/skills/write-abstract. 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 Write Abstract?

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 Write Abstract?

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

Is the Write Abstract AI skill free?

Yes. It is published on GitHub by ShaishavMaisuria under the Apache-2.0 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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