Individual skill

recsys-writing-style

Use when revising an ACM RecSys paper for a recommendation-first first page, honest offline-versus-online framing, equal-budget baseline claims, leakage-aware evaluation wording, ACM two-column 8-page compression, double-blind phrasing, and claims scoped to what the ranking evidence actually supports rather than to leaderboard language.

RecSys-Skills/skills/recsys-writing-style/SKILL.md

Read pinned source

Source commit 932eb23331721b16e967c59f093781be1928b498

What was checked

Matches the observed repository HEAD
Yes
Scanner rules are current
Yes
Repository scan complete
No
Skill scan complete
Yes
Observed behavior
Network or broad shell
Last checked
Nov 9, 2026

These are observations at the recorded commit, not a guarantee of safety. Review the source before running it.

Install this skill

Choose an agent in your Stack or copy a command below. Commands fetch the pinned commit and copy only this skill directory. Existing destinations are refused. Copying a command does not install anything.

An install command is unavailable: current rules, complete repository and skill scans, an eligible behavior level and a permitted license are required.

Repository context

Repository stars (not skill ratings)
1,405
Repository last updated
Sep 27, 2026
License
MIT

Observed agent integration: No specific integration evidence. Standard SKILL.md installation does not imply verified compatibility.

Files and excerpt

File metadata and permitted, redacted excerpts come from the recorded scan. Source links are pinned to that commit.

Browse files
Read excerpt

# RecSys Writing Style

Use this when revising the main paper. RecSys papers need a compact statement of why a
**recommendation** result matters and enough evaluation detail to survive a reproducibility-minded
reviewer.

## Revision rules

- Put the recommendation contribution on the first page: problem, gap, method, offline evidence,
  and the offline-to-deployment bridge.
- Make the evaluation protocol explicit early: the split (temporal vs random), whether metrics are
  full-ranking or sampled, and that baselines are tuned under an equal budget.
- Pair every empirical claim with a table, an ablation, or an off-policy/A-B result — not with a
  superlative.
Back to top