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academic-paper-writer

skill · meleantonio/awesome-econ-ai-stuffNOASSERTION licenceAudited 20 Oct 2026 · source 369fe15b2a25

★ 653pushed 24 days agoversion 1.0.0
✓SAFEGrade B · 89/100 · 20 Oct 2026 · 369fe15
653repo stars · whole meleantonio/awesome-econ-ai-stuff

Is it safe? Yes — SAFE, grade B (89/100). We read this skill's source at commit 369fe15b2a25 and found no filesystem, network or shell access and no hard-coded secrets. What it does: Draft economics papers with proper structure and academic style

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Cite this page

ModelsAtlas. “academic-paper-writer (meleantonio/awesome-econ-ai-stuff)”. Retrieved 20 Oct 2026. https://modelsatlas.com/skills/meleantonio/academic-paper-writer

Trust audit

Audit 0.4.1 · source read 20 Oct 2026

Trust score89/100✓SAFE B
0 critical0 high0 medium0 low0 info

SAFE means nothing in the source contradicts what the skill says it does. Grade B is shared by 16,667 of 17,602 audited skills.

What the source does

  • FilesystemNone observedNo reads or writes in the source
  • NetworkNone observedNo outbound calls in the source
  • ShellNone observedNo commands run in the source
  • DependenciesPinnedNothing floats
  • SecretsNone foundNo keys in source

Five audit layers

LayerWhat we checkResultFindings
L0 ProvenanceRepo owner, licence, archive status, activityPASS0
L1 Static sourceSecrets, path traversal, supply chain, hidden codeNA0
L2 InstructionsPrompt injection, authority framing, hidden directivesPASS0
L3 InventoryThe files and declarations match the sourcePASS0
L4 SandboxRun in isolation and watch behaviourSKIPPED why0

Gates applied: no behavioural pass.

Findings (0)

No findings at any severity. We re-audit when the source changes.

Audit 0.4.1 · source sha 369fe15b2a25 · 20 Oct 2026Report an issue or request a re-scan

Provenance

Who published it, and what the verdict is pinned to

  • Publishermeleantonio GitHub userOwner of the repository this skill is read from
  • Source foldermeleantonio/awesome-econ-ai-stuff/_skills/writing/academic-paper-writerThe exact folder we audited
  • LicenceNOASSERTIONAs the repository states it
  • Commit pinned for this verdict369fe15b2a25A new audit runs when the source changes
  • Repository statusNot archivedLast push 24 days ago
  • Sandboxed runNot runSkills are read, not executed; layer L4 is skipped

What it tells the agent

Full source on GitHub ↗

Its description: Draft economics papers with proper structure and academic style

---
name: academic-paper-writer
description: Draft economics papers with proper structure and academic style
workflow_stage: writing
compatibility:
  - claude-code
  - cursor
  - codex
  - gemini-cli
author: Awesome Econ AI Community
version: 1.0.0
tags:
  - LaTeX
  - academic-writing
  - papers
  - economics
---

# Academic Paper Writer

## Purpose

This skill helps economists draft, structure, and polish academic papers with proper conventions for economics journals. It provides templates for different paper types and guidance on academic writing style.

## When to Use

- Starting a new research paper from scratch
- Restructuring an existing draft
- Writing specific sections (introduction, literature review, conclusion)
- Preparing papers for journal submission

## Instructions

### Step 1: Identify Paper Type

Ask the user:
1. Is this empirical or theoretical?
2. What is the target journal/audience?
3. What stage is the paper at? (outline, first draft, revision)
4. What sections need help?

### Step 2: Follow the IMRAD Structure

For empirical papers, use:
1. **Introduction** - Motivation, research question, contribution
2. **Literature Review** - Related work and positioning
3. **Data & Methods** - Sources, sample, empirical strategy
4. **Results** - Main findings with tables/figures
5. **Discussion** - Interpretation, mechanisms, limitations
6. **Conclusion** - Summary and implications

### Step 3: Apply Economics Writing Conventions

- **First paragraph** should state the research question and main finding
- **Use present tense** for established facts, past tense for your findings
- **Be precise** with causal language (effect vs. association)
- **Cite heavily** in the literature review
- **Lead with results** in the results section

## Example Output: Introduction Template

```latex
\section{Introduction}

% Hook - Why does this matter?
[TOPIC] is a fundamental question in economics, with implications for 
[POLICY AREA] and [BROADER RELEVANCE]. Despite extensive research, 
we still lack clear evidence on [SPECIFIC GAP].

% Research question
This paper asks: [RESEARCH QUESTION IN PLAIN LANGUAGE]? 
Specifically, we examine whether [PRECISE FORMULATION OF THE QUESTION].

% Preview of answer
We find that [MAIN RESULT IN ONE SENTENCE]. This effect is 
[economically significant / modest / heterogeneous], with 
[QUANTITATIVE SUMMARY: e.g., "a one standard deviation increase 
in X associated with a Y percent increase in Z"].

% Methodology (brief)
To identify this effect, we exploit [IDENTIFICATION STRATEGY: 
natural experiment / RCT / instrumental variable / RDD]. 
Our data come from [DATA SOURCE], covering [TIME PERIOD] 
and [SAMPLE SIZE] observations.

% Contribution / Related literature
Our paper contributes to several strands of literature. 
First, we extend the work of \citet{Author2020} by [EXTENSION]. 
Second, we provide new evidence on [MECHANISM/CHANNEL] that 
complements \citet{OtherAuthor2019}. Finally, our findings 
have implications for [POLICY/FUTURE RESEARCH].

% Roadmap
The remainder of the paper is organized as follows. 
Section~\ref{sec:background} provides background and reviews 
related literature. Section~\ref{sec:data} describes our data 
and empirical strategy. Section~\ref{sec:results} presents our 
main findings. Section~\ref{sec:robustness} discusses robustness 
checks. Section~\ref{sec:conclusion} concludes.
```

## Example Output: Results Section Template

```latex
\section{Results}
\label{sec:results}

% Lead with the main finding
Table~\ref{tab:main} presents our main results. Column (1) shows 
the baseline OLS specification without controls. The coefficient 
on [TREATMENT VARIABLE] is [POINT ESTIMATE] (s.e. = [SE]), 
statistically significant at the [1/5/10] percent level.

% Add controls incrementally
In column (2), we add [CONTROL SET 1]. The point estimate 
[increases/decreases slightly/remains stable] to [ESTIMATE]. 
Column (3) includes [CONTROL SET 2] and adds [FIXED EFFECTS]. 
Our preferred specification in column (4) includes [FULL CONTROLS] 
and yields [FINAL ESTIMATE].

% Interpret magnitude
To gauge economic significance, note that [INTERPRETATION]. 
A one standard deviation increase in [X] is associated with 
a [Y] percent [increase/decrease] in [OUTCOME], or roughly 
[COMPARISON TO MEAN/OTHER BENCHMARK].

% Brief mention of mechanisms/heterogeneity if relevant
Table~\ref{tab:hetero} explores heterogeneity by [DIMENSION]. 
We find that the effect is [larger/concentrated among] 
[SUBGROUP], suggesting that [INTERPRETATION].

\begin{table}[htbp]
\centering
\caption{Main Results: Effect of X on Y}
\label{tab:main}
\begin{tabular}{lcccc}
\hline\hline
 & (1) & (2) & (3) & (4) \\
 & OLS & + Controls & + FE & Preferred \\
\hline
Treatment & 0.052*** & 0.048*** & 0.041** & 0.039** \\
          & (0.012)  & (0.011)  & (0.015) & (0.016) \\
\\
Controls       & No  & Yes & Yes & Yes \\
Fixed Effects  & No  & No  & Yes & Yes \\
Cluster SE     & No  & No  & No  & Yes \\
\\
Observations   & 10,000 & 9,850 & 9,850 & 9,850 \\
R-squared      & 0.05   & 0.12  & 0.35  & 0.35  \\
\hline\hline
\multicolumn{5}{l}{\footnotesize Notes: * p<0.10, ** p<0.05, *** p<0.01.} \\
\multicolumn{5}{l}{\footnotesize Standard errors in parentheses.} \\
\end{tabular}
\end{table}
```

## Example Output: Conclusion Template

```latex
\section{Conclusion}
\label{sec:conclusion}

% Restate question and answer
This paper examined [RESEARCH QUESTION]. Using [METHOD/DATA], 
we found that [MAIN FINDING]. This result is robust to 
[ROBUSTNESS CHECKS].

% Implications
Our findings have several implications. For policy, they suggest 
that [POLICY IMPLICATION]. For theory, they provide support for 
[THEORETICAL MECHANISM] and challenge [ALTERNATIVE VIEW].

% Limitations (brief, honest)
Several limitations warrant mention. First, [LIMITATION 1: 
e.g., external validity]. Second, [LIMITATION 2: e.g., 
data constraints]. Future research could address these by 
[SUGGESTION].

% Future directions
This 

Excerpt, first 6,000 characters of SKILL.md, verbatim from the audited commit. It is text from someone else’s repository, quoted so you can judge it before your agent reads it.

Install

Pinned to the audited commit 369fe15

Download folder ↗
git clone https://github.com/meleantonio/awesome-econ-ai-stuff
git -C awesome-econ-ai-stuff checkout 369fe15b2a25

The author documents no install command, so this uses the repository directly. Our verdict covers commit 369fe15b2a25 only.

Works in which agents?

What its own text says, not a test

AgentStatusMore
CodexMentioned in its text, not testedSkills for Codex · About Codex
CursorMentioned in its text, not testedSkills for Cursor · About Cursor
“Mentioned” means the skill’s text names the agent. We have not run it there.

Audit history

Every audit, every source change

  1. ✓SAFE B 89 / 100

    first audit · source 369fe15b2a25

README badge

For maintainers · shows the latest audit

ModelsAtlas: SAFE BMODELSATLASSAFE · B
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Questions about academic-paper-writer

What does the academic-paper-writer skill do?
AI Skills for Economists
Is academic-paper-writer safe to install?
The audit found nothing in the source that contradicts what it says it does, and graded it B (89/100). Grade A is held back for packages that have also passed a sandboxed behavioural run, which is why a clean skill reads B.
What can academic-paper-writer access on my machine?
The audit observed no filesystem, network or shell use at all in its source.
Which assistants does academic-paper-writer work with?
Its documentation mentions codex and cursor. That is what the text claims, not a compatibility test we ran.
How current is this page?
The grade is for one exact copy of the source (369fe15b2a25), read on 2026-10-20. The repository is watched, and a new audit runs when it changes — this is the first audit.

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