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.
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Before installing skills in Cursor, ensure your development environment meets these requirements:
node --versionacademic-paper-writerExecute the skills CLI command in your project's root directory to begin installation:
Fetches academic-paper-writer from meleantonio/awesome-econ-ai-stuff and configures it for Cursor.
The CLI shows a list of agents. Use arrow keys and space to select Cursor:
Confirm successful installation by checking the skill directory location:
Restart Cursor to activate academic-paper-writer. Access via /academic-paper-writer in your agent's command palette.
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Complete competitive research in 2 hours instead of 2 days
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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.
Ask the user:
For empirical papers, use:
\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.
\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}
\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 paper opens several avenues for future work.
[DIRECTION 1]. [DIRECTION 2]. We hope our findings
stimulate further research on [BROADER TOPIC].
Make data-driven prioritization decisions faster
Draft PRDs, status updates, and stakeholder presentations
Example
Create executive summary of Q3 roadmap, monthly progress report, feature launch announcement
Save 3-5 hours/week on communication overhead
Prerequisites
Time Estimate
30-60 minutes to see productivity improvements
Steps
Common Pitfalls
✓ Do
✗ Don't
💡 Pro Tips
✓ Use when
Use for user story writing, competitive research, roadmap prioritization, stakeholder communication, and PRD drafting. Best for reducing repetitive documentation and research work.
✗ Avoid when
Avoid for strategic product vision (requires deep customer empathy), pricing decisions (needs market and financial expertise), or when face-to-face customer discovery is more valuable than speed.
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ailabs-393/ai-labs-claude-skills
Useful defaults in academic-paper-writer — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
academic-paper-writer is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
Registry listing for academic-paper-writer matched our evaluation — installs cleanly and behaves as described in the markdown.
Keeps context tight: academic-paper-writer is the kind of skill you can hand to a new teammate without a long onboarding doc.
academic-paper-writer fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
I recommend academic-paper-writer for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
We added academic-paper-writer from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
Solid pick for teams standardizing on skills: academic-paper-writer is focused, and the summary matches what you get after install.
Registry listing for academic-paper-writer matched our evaluation — installs cleanly and behaves as described in the markdown.
academic-paper-writer is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
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