AI Research Writing Skill
A skill turns an ML research repository into a conference paper draft in LaTeX with a claim-evidence map.
- 64 ★ on the repository
- Last commit
- MIT
Extended access
Why this level
- The skill runs scripts and builds LaTeX on your machine while reading project code and logs.
Install
- Works in
In your terminal, with SkillFoxx CLI
npx skillfoxx add skills/ai-research-writing-skillDetects the agents on your machine, shows the access level and pins the version.
Other ways to install
Access and checks
How we reviewExtended accessThe tool runs code or makes network calls and only reads external data.
- The skill runs scripts and builds LaTeX on your machine while reading project code and logs.
This is third-party code. Review the repository files before installing.
What it does
The agent takes code, experiment logs, notes and a venue template and builds a checkable paper draft with a submission package: a story, a claim-evidence map, verified citations, figures, reviewer-style critique, rebuttal points and build notes. The main principle is that every major claim ties to code, results, notes or a verified citation. There is one entrypoint, the root `SKILL.md`, and the rest loads as needed: `references/`, `scripts/` on the Python standard library, audited template sources and a sample finished package. In the example the skill wrote a paper about itself.
Who it is for. Machine learning researchers who need a checkable paper draft from a finished experiment repository.
Good fit when
- A repository with code and logs becomes a conference paper draft.
- A claim-evidence map is built from code and results for each claim.
- Citations are verified so invented works do not slip in.
- A reviewer-style critique and a list of rebuttal points are produced before submission.
Not a fit when
- The paper is outside machine learning and has no experiments.
- You need prose from scratch with no repository or results.
- You would need invented numbers that are not in the data.
Example request
Use AI Research Writing Skill: build an ICML paper draft from this repository, invent nothing and take numbers from the results.Limitations
The skill performs claim-evidence engineering of the text rather than writing on demand: without results and code it invents no numbers. Building LaTeX needs an installed environment, and the final compile check is recorded in the example `build_check.md`. Templates come from audited official venue sources. The submission decision and the integrity of the conclusions stay with the authors, and the scripts run on the Python standard library with no external dependencies.
How to disable. Delete the copied or linked repository directory from the agent skills directory.
FAQ
How do I start with the skill?
Ask the agent to install the repository as a local skill with the root `SKILL.md` as the entrypoint, then give it code, logs and a venue template.
What does the final package contain?
A paper story, a claim-evidence map, literature positioning, citation verification, LaTeX figures and tables, `main.tex` and build notes.
Does the skill invent results?
No. The core requirement is that every major claim rests on code, results, notes or a verified citation.
Is there a sample result?
Yes, `examples/paper-about-ai-research-writing-skill/` holds a finished package with the compiled paper PDF.
What dependencies do the scripts have?
Only the Python standard library.
Discussion
No questions or reviews yet.
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README in short
The repository is presented as evidence engineering rather than a text generator. The root `SKILL.md` leads to supporting material and a full example shows the expected result.