iclr-writing-style
Use when revising an ICLR manuscript for learning-representation framing, OpenReview readability, contribution clarity, limitations, ethics, and reviewer navigation. Use when the core representation insight is buried, when an abstract must read well as an OpenReview snippet, or when adding a "what to verify" path so reviewers can confirm the claim under permanent public review.
Profile →npx skills add brycewang-stanford/Awesome-Journal-Skills --skill iclr-writing-style --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# ICLR Writing Style Use this to turn a technically correct draft into an ICLR-readable paper. The style should make the learning-representation contribution easy to evaluate under public review. ## ICLR framing - State the representation, learning problem, or model-behavior insight in the first page. - Make clear whether the contribution is method, theory, benchmark, analysis, dataset, evaluation, systems support, or application-driven ML. - Explain why the result changes how the community should train, evaluate, understand, or deploy learning systems. - Avoid hiding the core idea behind implementation detail or benchmark trivia. - Connect limitations to real deployment, robustness, safety, fairness, or data constraints when those issues are relevant. ## Reviewer navigation - Give reviewers a short "what to verify" path: main theorem, key ablation, benchmark setting, reproducibility artifact, or appendix section. - Use figure captions as mini-arguments, not labels. - Keep notation local and consistent; ICLR reviewers span subfields. - Use the appendix to answer predictable objections, but do not move decisive evidence out of the main narrative. - Write the abstract and introductio
- ICLR framing
- Reviewer navigation
- Framing that survives public skimming
- Worked vignette
- Reviewer-pushback patterns
- Output format
What does the iclr-writing-style skill do?
Use when revising an ICLR manuscript for learning-representation framing, OpenReview readability, contribution clarity, limitations, ethics, and reviewer navigation. Use when the core representation insight is buried, when an abstract must read well as an OpenReview snippet, or when adding a "what to verify" path so reviewers can confirm the claim under permanent public review.
How do I install it?
Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill iclr-writing-style --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From brycewang-stanford/Awesome-Journal-Skills, a repository with 909 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.