Agent Skills
› brycewang-stanford/Awesome-Journal-Skills
› fast-writing-style
fast-writing-style
GitHub用于优化USENIX FAST存储论文，确保首页明确存储贡献，以写入放大等成本指标而非吞吐量框架评估，强调真实设备证据与双盲合规，并严格遵循两栏篇幅限制。
Trigger Scenarios
修改USENIX FAST存储系统论文
重写引言以突出存储贡献
将性能评估转化为存储成本分析
Install
npx skills add brycewang-stanford/Awesome-Journal-Skills --skill fast-writing-style -g -y
SKILL.md
Frontmatter
{
"name": "fast-writing-style",
"description": "Use when revising a USENIX FAST paper for a storage contribution on the first page, a design\/mechanism narrative a storage reviewer can follow, an evaluation framed as the storage cost it changes (write amplification, tail latency, endurance, crash consistency), double-blind wording, and disciplined use of the USENIX two-column page budget."
}
FAST Writing Style
Use this when revising the main paper. FAST papers are read by storage systems people, so they need a storage contribution stated on the first page and an evaluation a storage reviewer trusts. The failure this skill prevents is a technically fine paper that reads like a general systems demo or a throughput-bar benchmark with "storage" in the title.
Revision rules
- Lead with the storage contribution: the storage problem a practitioner recognizes, the storage cost current designs pay (write amplification, tail latency, endurance, space, or a consistency gap), your design or finding, real-device evidence, and what changes for storage systems.
- Frame the evaluation as a cost you change, not a speed you win. State up front which storage quantity the paper moves; a reader should know by the end of the intro whether the headline is bytes-written, p99 latency, drive lifetime, or recovery correctness.
- Pair every claim with proportional, real-device evidence — named drives and firmware, standard workloads/traces, a distribution not just a mean, a device counter not an estimate — not adjectives.
- Make the device reality visible early. A storage reviewer wants to know the hardware and its state; a testbed table and a sentence on preconditioning/aging belong near the evaluation's start, not buried.
- Protect the invariant. If the design defers, batches, or reorders writes, say early that you verify crash consistency/durability still holds; do not let the reader wonder.
- Respect the USENIX page budget (FAST '27: ≤12 pages long / ≤6 short, references excluded) as a design constraint. It is a firm two-column limit; recover space editorially, never by shrinking the evaluation or the durability discussion.
- Maintain double-blind in self-citations (third person), system/tool names, acknowledgements, funding, datacenter names, and trace-hosting URLs.
Storage paper skeleton
| Section | Job it must do | Common failure |
|---|---|---|
| Intro | Storage problem, the cost paid, contribution, evidence preview, storage payoff — first page | Leads with a technology trend, not a storage cost |
| Background | The device/media/workload reality the design exploits | Generic background not tied to the mechanism |
| Design / Study | The mechanism or the study protocol, reproducibly | Design described too thinly to rebuild |
| Evaluation | Each claim answered with the right storage metric on real devices | Throughput bar standing in for the claimed cost |
| Consistency/durability | The invariant the change risks, tested | Consistency asserted, never crash-tested |
| Related work | Delta-first positioning against storage literature | Citation catalog with no contrast |
Sentence-level rewrites
| Draft pattern | FAST-safe rewrite |
|---|---|
| "Our system is much faster." | "cuts write amplification from X to Y on <SSD model, firmware> at steady state" |
| "We evaluate on an SSD." | "on <model/capacity/firmware>, preconditioned to steady state, fill Z%, TRIM on" |
| "Low latency." | "p99.9 read latency of ... under |
| "It is reliable / consistent." | "recovers a consistent state at all <K> injected crash points (§6)" |
| "State-of-the-art throughput." | Claim scoped to the devices, workloads, and state actually tested |
| "We reduce writes by ~2x." | "bytes-written from device counters fell 2.1x (95% CI ...), vs. the tuned baseline" |
Storage-metric discipline
[Endurance] report bytes-written / P/E cycles from device counters, not estimates
[Latency] report the distribution (p50/p99/p99.9) under load, not the mean
[Amplification] separate read vs. write amplification; say how each is measured
[Space] on-media footprint, including metadata/GC overhead
[Durability] the crash-consistency invariant and the test that checks it
-> lead each result with the metric that matches the claim; put device+state beside it
Vignette: compressing a design-plus-study paper
A draft with a new cache design, six microbenchmarks, and a sprawling background: keep the design, the two experiments that carry the headline (miss-ratio-vs-cost and tail latency on real traces), and a crash-consistency check; move secondary microbenchmarks and full parameter sweeps to the artifact with forward references; cut background to the media/workload facts the mechanism needs. The test of a good cut: a reviewer should be able to answer "what storage cost does this change, by how much, on what hardware, and does it stay correct?" from the body alone.
Output format
[Writing diagnosis] clear / under-motivated / wrong-metric / device-reality-missing / over-scoped
[First-page fix] <new framing leading with the storage cost the paper changes>
[Metric audit] <claim -> storage metric -> measured on real devices? yes/no>
[Durability check placement] <where the crash-consistency/invariant test is stated>
[Anonymity edits] <system names / self-citations / trace URLs / datacenter names to rewrite>
Version History
- 9f86f09 Current 2026-07-19 15:44
