colm-submission
Use when preparing or auditing a COLM submission on OpenReview — the late-March abstract and full-paper deadlines, the strict 9-page main text, double-blind rules banning acknowledgments and identity links, the Code of Ethics acknowledgment, LLM-usage disclosure, reciprocal-reviewer nomination, and pre-upload risk triage.
Profile →npx skills add brycewang-stanford/Awesome-Journal-Skills --skill colm-submission --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.
# COLM Submission Everything below is the COLM 2026 cycle as read from `colmweb.org` on 2026-07-08. COLM re-issues its instructions each edition and has already changed details between 2024, 2025, and 2026 — reopen the current submission-instructions page before acting on any number here. ## The 2026 mechanics - **Two deadlines a week apart:** abstract March 26, 2026; full paper March 31, 2026. Th
What does the colm-submission skill do?
Use when preparing or auditing a COLM submission on OpenReview — the late-March abstract and full-paper deadlines, the strict 9-page main text, double-blind rules banning acknowledgments and identity links, the Code of Ethics acknowledgment, LLM-usage disclosure, reciprocal-reviewer nomination, and pre-upload risk triage.
How do I install it?
Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill colm-submission --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.