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research-paper-writing

Pipeline for ML/AI research papers — lit review to LaTeX submission

Skill by taracodlabs

IndexedApache-2.0★ 863
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Install

Works with Claude Code, Claude apps, Codex, Cursor, Gemini CLI, GitHub Copilot, VS Code, OpenCode, Goose, Windsurf. Read the repository before you give any tool access to your data.

npx agentmarket install skill/taracodlabs-research-paper-writing

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About

Pipeline for ML/AI research papers — lit review to LaTeX submission

Use cases: documents, data, ml, writing

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Permissions

What this skill can do and what it asks for, from its SKILL.md. Checked Oct 25, 2026.

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Network hosts it talks to 1

  • codeload.github.com · found in install command

Files it touches

  • ~/.claude/skills/research-paper-writing

What's inside

Skill name
research-paper-writing
Description
Pipeline for ML/AI research papers — lit review to LaTeX submission
License
Apache-2.0
Instructions
150 lines in SKILL.md · view on GitHub

Before installing

  • Instructions call the network

Files (2)

  • SKILL.md
  • skill.json

SKILL.md (first lines)

# Research Paper Writing Pipeline

A structured, step-by-step pipeline for writing ML/AI research papers: from problem framing through literature review, experiment design, writing, and LaTeX formatting for arXiv submission.

## When to Use

- User wants to write or structure an academic research paper
- User wants help organizing experiments and results for a paper
- User wants to format a paper in LaTeX for arXiv or a conference
- User wants to do a literature review on a topic
- User wants to write an abstract, introduction, or related work section

## How to Use

### Phase 1: Frame the contribution

Define the paper's core claim before writing anything else.

```
1. One-sentence contribution: "We show that X outperforms Y on Z by doing W"
2. Key insight: what is non-obvious about your approach?
3. Research question: what question does the paper answer?
4. Limitations scope: what is explicitly out of scope?
```

### Phase 2: Literature review

Use the arXiv skill to find related work, then organize findings:

```
Search strategy:
- Start with 2-3 "seed" papers you know are relevant
- Find papers that cite them (via Semantic Scholar API)
- Search arXiv for your core keywords + recent date filter
- Organize into: direct predecessors, concurrent work, tangential work

For each related paper, note:
- Core method
- Dataset/benchmark used
- Key result number
- How your work differs
```

```python
# Semantic Scholar API — find papers citing a known paper
import requests
paper_id = "arXiv:2305.17333"
resp = requests.get(f"https://api.semanticscholar.org/graph/v1/paper/{paper_id}/citations?fields=title,year,authors,externalIds&limit=20")
for c in resp.json()["data"]:
  print(c["citingPaper"]["title"])
```

### Phase 3: Structure the paper

Standard ML/AI paper structure:

```
Abstract   (150-250 words) — problem, method, key result, significance
1. Introduction — motivation, gap, contribution, paper overview
2. Related Work — organize by theme, not chronologically
3. Method — notation, architecture/algorithm, key design choices
4. Experiments — datasets, baselines, metrics, implementation details
5. Results — main table, ablation study, qualitative examples
6. Discussion — limitations, failure modes, future work
7. Conclusion — restate contribution, broader impact
References
Appendix (optional) — proofs, additional experiments, hyperparameters
```

### Phase 4: Write in LaTeX

Basic arXiv-ready template:

```latex
\documentclass[10pt,twocolumn]{article}
\usepackage{arxiv}       % from https://github.com/kourgeorge/arxiv-style
\usepackage{amsmath,amssymb,graphicx,booktabs,hyperref}

\title{Your Paper Title}
\author{Author One \and Author Two}
\date{\today}

\begin{document}
\maketitle

\begin{abstract}
Your abstract here. State the problem, method, key result, and significance in 150--250 words.
\end{abstract}

\section{Introduction}
...

\bibliography{refs}
\bibliographystyle{plain}
\end{document}
```

### Phase 5: Tables and figures

```latex
% Results table with booktabs
\begin{table}[t]
\centering
\caption{Comparison on benchmark dataset.}
\begin{tabular}{lcc}
\toprule
Method & Accuracy & F1 \\
\midrule
Baseline   & 72.3 & 71.1 \\
Prior SOTA & 78.6 & 77.9 \\
\textbf{Ours} & \textbf{83.2} & \textbf{82.7} \\
\bottomrule
\end{tabular}
\label{tab:results}
\end{table}
```

### Phase 6: Compile and check

From taracodlabs/aiden, Apache-2.0.

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    Stars
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    Open issues
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    Last commit (this folder)
    May 6, 2026 (5 months ago)
    Last release
    Oct 19, 2026 (8 days ago)

    From GitHub (fetched Oct 24, 2026).

    Details

    License
    Apache-2.0
    First seen
    Oct 24, 2026
    Last checked
    Oct 24, 2026

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    Cite this page

    research-paper-writing skill. Agent Mart. https://agentmart.dev/skills/taracodlabs-research-paper-writing (last updated 2026-10-24)