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sigmetrics-writing-style
GitHub用于修订ACM SIGMETRICS论文，确保首页明确性能贡献、假设可验证、定理与实证匹配、遵守双盲及20页限制。
Trigger Scenarios
需要修改SIGMETRICS论文以符合严格学术规范
检查论文是否具备精确的性能指标和模型假设
Install
npx skills add brycewang-stanford/Awesome-Journal-Skills --skill sigmetrics-writing-style -g -y
SKILL.md
Frontmatter
{
"name": "sigmetrics-writing-style",
"description": "Use when revising an ACM SIGMETRICS paper for a rigorously stated performance contribution on the first page, explicit modeling assumptions and their validity, theorems paired with numerical\/empirical validation, evidence proportional to the claim, double-anonymous wording, and disciplined use of the 20-page single-column acmsmall budget."
}
SIGMETRICS Writing Style
Use this when revising the main paper. SIGMETRICS papers are POMACS journal articles read by performance-evaluation specialists, so they need a precise performance contribution stated on the first page and claims a reviewer can check. The failure this skill prevents is a paper that reads like a systems demo (numbers, no model) or a theory paper with no systems relevance (theorems, no validation).
Revision rules
- Lead with the performance contribution, stated rigorously: the systems-performance problem, a precise metric (mean vs. tail latency, throughput, regret, energy), why current models/policies fall short, the contribution (a model, policy, methodology — ideally with a proven bound), the validation, and what changes for real systems.
- State assumptions where the result uses them. A theorem is only as strong as its assumptions; name the arrival process, service distribution, independence, and stationarity your result needs, and show they are plausible for the target system. Hidden assumptions are the fastest reject.
- Pair every quantitative claim with proportional evidence — a proof for an analytic claim, a simulation whose curve matches the analysis, confidence intervals over repeated runs, effect sizes for a comparison — not adjectives.
- Validate the model against measurement. The SIGMETRICS signature move is showing that the analytic prediction and the measured/simulated data agree; a theorem with no validation, or a measurement with no model, is half a paper.
- Respect the 20-page acmsmall budget as a design constraint. References are unlimited, but body text, figures, and in-body appendices are not. A paper that only fits by shrinking the assumptions or the validation is over-scoped.
- Maintain double-anonymity in self-citations, system names, trace provenance, and acknowledgements (except in the Operational Systems Track).
Performance-evaluation paper skeleton
| Section | Job it must do | Common failure |
|---|---|---|
| Intro | Problem, precise metric, inadequacy, contribution, validation preview, systems payoff — first page | Leads with a trend and "improves performance," no metric or model |
| Model / System | The model and its assumptions, stated precisely and justified | Assumptions hidden or unjustified against the real workload |
| Analysis | Theorems/bounds with proofs (full proofs in an appendix) | A claimed bound with a hand-waved or incomplete proof |
| Validation | Analysis-vs-simulation agreement; measurement of the real system | A plot with no analytic comparison, or no confidence intervals |
| Evaluation | Baselines, fairly tuned; the systems payoff on real workloads | Untuned baseline; toy inputs; benchmark score as the whole result |
| Assumption validity / threats | Where assumptions hold and where they are stressed | Deferred or absent; no estimation-error / robustness discussion |
Sentence-level rewrites
| Draft pattern | SIGMETRICS-safe rewrite |
|---|---|
| "Our policy significantly improves performance." | "reduces p99 latency by X% (95% CI ...) over |
| "We assume the standard queueing model." | "We assume M/G/1 with service-time distribution fit to the trace (§5.1, QQ-plot Fig. 6)" |
| "The bound holds in general." | "Thm. 1 holds under assumptions A1-A3; §6 quantifies degradation when A2 is violated" |
| "Simulation confirms our approach." | "the analytic p99 curve lies within the simulated confidence intervals across three distributions (Fig. 4)" |
| "State-of-the-art results." | Claim scoped to the metric, workload, and regime actually analyzed and measured |
Assumption-and-validation discipline
[Assumptions] list each (arrival, service, independence, stationarity); justify against the target
[Analysis] prove the bound; put full derivations in an appendix within the reviewed pages
[Validation] overlay analysis on simulation/measurement; report CIs and number of runs
[Robustness] quantify what happens when an assumption is stressed (estimation error, heavy tails)
-> a theorem, its assumptions, and its validation are one unit -- present them together
Vignette: compressing a proof-plus-measurement paper
A draft with three theorems, a long simulator description, and a sprawling measurement section: keep all three theorem statements and their assumptions in the body, move full proofs to an appendix with forward references, keep the one figure showing analysis-vs-simulation agreement and the table with the trace-driven payoff, and cut redundant simulator detail to the artifact. The test of a good cut: a reviewer should be able to answer "what is claimed, under what assumptions, and does the measurement back it?" from the body alone.
Output format
[Writing diagnosis] clear / under-specified-assumptions / unvalidated / over-claimed / over-scoped
[First-page fix] <new framing leading with the precise performance contribution>
[Assumption audit] <assumption -> stated? justified against workload? where used?>
[Validation fix] <theorem/claim -> analysis-vs-measurement evidence to add>
[Anonymity edits] <system names / self-citations / trace provenance to rewrite>
Version History
- 9f86f09 Current 2026-07-19 17:37
