Loading skill
Install any skill in seconds. Free to start, no credit card required.
Get Started Free →taracodlabs/research-paper-writing
Pipeline for ML/AI research papers — lit review to LaTeX submission
Passed 19 of 22 test cases with the skill, and 15 of 22 without it.
and 6 more in the full report
5 fixed14 passed either way2 still failing1 broke
Tokens, turns and time describe resource use, not a dollar price.
One of 5 test cases the skill fixed. Same model, same prompt, with and without the skill.
List the standard 7 main numbered sections in sequence for a machine learning research paper submission before References.
| Checked | Without skill | With skill |
|---|---|---|
| Lists section 1 as Introduction, 2 as Related Work, 3 as Method, 4 as Experiments, 5 as Results, 6 as Discussion, and 7 as Conclusion | Missed | Passed |
The instructions your model reads when the skill loads.
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.
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?
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
test cases passed, vs 15 / 22 without
Published skills whose descriptions closely match this one, with their headline benchmark lift.
More skills from the same source and nearby in the registry, with their headline benchmark lift.