ai-research-writing-skill

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Bu listing icin henuz AI raporu yok.

SUMMARY

AI Research Writing Skill (AI论文写作技能) is an agent skill for ML / AI / CV / NLP researchers. Point your coding agent at code, experiment logs, notes, and a venue template; it helps you produce an auditable, evidence-backed LaTeX draft and submission package — not a polished fiction.

README.md

AI Research Writing Skill

中文说明

License: MIT
Python: stdlib only
Entrypoint
LaTeX templates

Turn an ML/AI research repo into an evidence-backed, build-ready conference paper draft.

Point your coding agent at code, experiment logs, notes, and a venue template. This skill helps it produce an auditable LaTeX draft and submission package: story, claim-evidence map, verified citations, figures, reviewer-style critique, rebuttal risks, and build notes.

Claim-evidence engineering, not prose generation.
Every major claim should trace to code, results, notes, or verified citations.

AI Research Writing Skill teaser


End-to-End Demo

Use AI Research Writing Skill to write a complete system paper about this repository itself.
Treat ai-research-writing-skill as the research artifact.
Inspect SKILL.md, references/, scripts/, templates/, examples/, and README.
Create paper_story.md, claim_evidence_map.md, literature positioning, verified citations, ICML-style method figures/tables, and a build-ready ICML LaTeX paper under examples/paper-about-ai-research-writing-skill/paper/.
Do not invent performance numbers. Use repository facts as evidence.

The example already includes the expected final paper package, so you can inspect what an end-to-end output looks like:

  • Read the generated ICML-style paper PDF: paper/main.pdf
  • evidence/repository_inventory.md: repository facts used as evidence.
  • paper_story.md and claim_evidence_map.md: story and claim boundaries.
  • literature/positioning.md and citation_verification.md: related-project positioning.
  • paper/figures/method_overview.tex and paper/tables/*.tex: ICML-style paper assets.
  • paper/main.tex: complete paper draft about this project.
  • paper/main.pdf: compiled paper for quickly judging output quality.
  • build_check.md: compilation command, expected result, and residual risks.

AI Research Writing Skill method overview

User Journeys

Use the skill at different stages of a research project. Start with the journey that matches what you already have.

Journey You have Ask the agent to do
Brainstorm and plan A topic, rough idea, or possible method Clarify the thesis, research gap, contribution boundary, evidence needed, and next experiment/writing plan.
Repo to full paper Ideas, method design, code, notes, experiment logs, partial results, or a venue template Build paper_story.md, claim_evidence_map.md, literature positioning, figures, tables, BibTeX, LaTeX draft, and build checks.
Draft review A complete or partial paper draft Act as a skeptical reviewer: write reviewer-style comments, identify rejection risks, and turn major issues into concrete edits.
Targeted revision A draft plus known weaknesses, reviewer feedback, or a section to improve Revise the section or whole paper while preserving claim-evidence boundaries and avoiding unsupported stronger claims.
Figures and tables Results, logs, CSVs, method notes, or a rough figure idea Produce figure/table plans, generated overview or method figures, deterministic result plots/tables, captions, and LaTeX wiring.
Submission readiness A near-final paper package Run citation, marker, build, venue, reviewer-risk, checklist, and packaging checks before submission or Overleaf/Git handoff.

Copyable prompts:

I only have a rough idea. Use AI Research Writing Skill to brainstorm the paper story, identify the research gap, define claims to make/avoid, and create a concrete plan for evidence, experiments, figures, and writing.
I have code, notes, method design, and some experiment logs/results. Use AI Research Writing Skill to generate a complete paper package: paper_story.md, claim_evidence_map.md, literature positioning, verified BibTeX, figures, tables, LaTeX draft, and build_check.md.
I have a paper draft. Use AI Research Writing Skill as a skeptical ICML reviewer: write detailed reviewer comments, identify rejection risks, and convert the high-risk issues into concrete revisions.
I have a draft and want to revise it. Use AI Research Writing Skill to improve the paper section by section, preserve supported claims, weaken unsupported claims, fix citations, improve figures/tables, and update the LaTeX package.

Why this skill

Typical AI paper help AI Research Writing Skill
Fluent paragraphs from memory Claims mapped to repo evidence
Citations guessed or invented BibTeX from arXiv / DOI / Semantic Scholar
Figure “plans” that never ship Generated overview/method figures + deterministic result plots
Stops at an outline Concrete artifacts: paper_story.md, claim_evidence_map.md, references.bib, figure files
Generic writing tips Reviewer-style comments, rejection-risk diagnosis, venue checklists, build & packaging gates

Supported venues (templates & checklists): NeurIPS, ICML, ICLR, CVPR, ICCV, ECCV, ACL, AAAI, COLM, and related ML/AI conferences. Always verify official author instructions before submission.

Before / After

Before using this skill After using this skill
Scattered notes, logs, and half-written sections paper_story.md and scoped task packets
Claims that sound plausible claim_evidence_map.md with evidence status
Candidate citations from memory BibTeX fetched or verified from authoritative metadata
Figure ideas in prose Generated concept figures and deterministic result plots
"Looks done" Reviewer-style critique, build, TODO, citation, and submission checks

What you get

End-to-end coverage from idea to camera-ready:

Stage Outputs
Story Thesis, gap, contributions, claims to avoid
Evidence claim_evidence_map.md tied to code / logs / tables
Writing Abstract, Intro, Related Work, Method, Experiments, Limitations, Conclusion
Literature Local corpus, positioning, verified references.bib
Figures Plan + assets: generated overview/method diagrams; deterministic plots for numbers
Review Reviewer-style comments, rejection-risk diagnosis, self-review, concrete revision plan
Submit Venue checklist, LaTeX build check, TODO/citation audit, packaging

Quality gates (built in)

The skill enforces checkpoints agents must not skip:

  • Evidence — numbers from data/logs/scripts, not image models
  • Story — no full draft before contributions are explicit
  • Literature — positioning before Related Work prose
  • Citation — no unverified BibTeX without a visible placeholder
  • Figures — concept diagrams via image generation (default); TikZ/SVG only as optional reference
  • Reviewer — high-severity objections addressed before “done”
  • Build — compile or document why not

Installation

Simple rule: the only canonical entrypoint is the root SKILL.md.
The rest of the repository is supporting material that the skill loads as needed: references/, scripts/, templates/, and examples/.

Agent-Assisted Install

Ask your agent to install this repository as a local skill:

Install https://github.com/jin-s13/ai-research-writing-skill as a local skill.
Use the repository root SKILL.md as the canonical entrypoint.
If your platform needs a skills directory, copy or symlink the whole repository there.

Manual Install

git clone https://github.com/jin-s13/ai-research-writing-skill.git
# Then copy or symlink this repository into your agent's local skills directory.

You can also use it without installing by opening this repository and asking:

Use the AI Research Writing Skill in this repository.
Follow SKILL.md and load only the relevant references for my task.

Repository layout

ai-research-writing-skill/
├── examples/             # Minimal demo paper repo
├── SKILL.md              # Canonical agent entrypoint
├── references/           # Workflow, writing, citations, figures, venues, review
│   └── assets/           # Figure pattern references (figures4papers-style)
├── scripts/              # Claims, citations, TODOs, build-log, camera-ready checks
├── templates/            # NeurIPS / ICML / CVPR / ACL / … LaTeX starters
└── README.zh-CN.md

Start here when digging in:

File Purpose
references/workflow.md Full-paper state machine
references/artifacts.md What to create in your paper repo
references/figure-workflow.md Diagrams vs plots; generation defaults
references/citation-workflow.md Search, verify, BibTeX
templates/README.md Template list and compile tips
examples/paper-about-ai-research-writing-skill/ End-to-end paper about this project

Helper scripts

python3 scripts/extract_claims.py main.tex > claim_evidence_map.md
python3 scripts/check_citations.py main.tex references.bib
python3 scripts/check_todos.py main.tex checklist.tex references.bib figures
python3 scripts/parse_build_log.py main.log
python3 scripts/camera_ready_check.py main.tex
python3 scripts/research_quality_gate.py /path/to/paper-project

More: scripts/README.md.


Safety & hygiene

  • Bundled templates are convenience copies — confirm current venue rules before submitting.
  • Do not commit private PDFs, proprietary logs, API keys, or reviewer-confidential material.

Acknowledgements

This project is inspired by and builds on the excellent research-writing and figure-making projects below. It does not try to replace them; it narrows their ideas into one opinionated workflow: turn an ML/AI research repository into an evidence-backed, build-ready conference paper package.

Project What it is excellent at How this project is different
Master-cai/Research-Paper-Writing-Skills A compact skill package for ML/CV/NLP paper writing, adapted from research-writing notes into reusable agent skills. Adds a full repo-to-paper production contract: inventories, claim-evidence maps, verified BibTeX, figure assets, build checks, and submission packaging.
Norman-bury/research-writing-skill A broad, multi-platform research-writing assistant for thesis writing, chapter workflows, literature review, LaTeX output, and process tracking. Specializes in AI conference papers from code, logs, experiments, and venue templates instead of general thesis/chapter writing.
Orchestra-Research/AI-research-SKILLs A comprehensive AI research and engineering skills library for agents, spanning the broader research lifecycle from idea to paper. Focuses on one deep vertical: paper-writing execution and submission readiness for an existing ML/AI research repo.
Yuan1z0825/nature-skills Nature/CNS-style academic writing, polishing, reviewer response, data availability, citation, and publication-quality figure workflows. Targets ML/AI conference workflows and templates such as NeurIPS, ICML, ICLR, CVPR, ICCV, ECCV, ACL, AAAI, and COLM.
ChenLiu-1996/figures4papers High-quality Python scripts and examples for publication figures in top AI conferences and journals. Integrates figure planning into a larger paper pipeline: figures are tied to claims, evidence, captions, LaTeX references, and submission checks.

In short: the related projects provide writing wisdom, broad skill ecosystems, Nature-style publication craft, or figure-making expertise. This project packages those inspirations into a claim-evidence-engineering workflow for AI paper agents working inside real research repositories.

License

MIT License.

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