ipsn-writing-style

GitHub

指导IPSN系列论文修订,强调首段呈现真实传感问题、基于真值与实机硬件的量化证据、能量/延迟预算及双盲规范,防止离线ML风格或无实测权衡的报告。

IPSN-Skills/skills/ipsn-writing-style/SKILL.md brycewang-stanford/Awesome-Journal-Skills

Trigger Scenarios

修改传感器系统论文 撰写信息处理或平台贡献章节 检查部署报告真实性 优化双盲匿名内容

Install

npx skills add brycewang-stanford/Awesome-Journal-Skills --skill ipsn-writing-style -g -y
More Options

Non-standard path

npx skills add https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/IPSN-Skills/skills/ipsn-writing-style -g -y

Use without installing

npx skills use brycewang-stanford/Awesome-Journal-Skills@ipsn-writing-style

指定 Agent (Claude Code)

npx skills add brycewang-stanford/Awesome-Journal-Skills --skill ipsn-writing-style -a claude-code -g -y

安装 repo 全部 skill

npx skills add brycewang-stanford/Awesome-Journal-Skills --all -g -y

预览 repo 内 skill

npx skills add brycewang-stanford/Awesome-Journal-Skills --list

SKILL.md

Frontmatter
{
    "name": "ipsn-writing-style",
    "description": "Use when revising an IPSN-lineage paper for a real sensing problem on the first page, a load-bearing information-processing or platform contribution, ground-truth methodology, energy\/latency\/accuracy budgets, honest deployment reporting, double-blind wording, and disciplined use of the ≤12-page ACM two-column budget."
}

IPSN Writing Style

Use this when revising the main paper. IPSN papers are read by sensor-systems and information-processing reviewers, so they need a real sensing problem on the first page and evidence measured on real hardware against ground truth. The failure this skill prevents is a technically fine paper that reads like an offline ML result, or a hardware report with no measured trade-off.

Revision rules

  • Lead with the sensing problem and its physical budget: the phenomenon being sensed, why current sensing/processing is inadequate, the contribution (an estimator/inference method and/or a platform), the real-hardware evidence, and the energy/latency/accuracy budget that makes it deployable.
  • Make the information processing load-bearing (IP track). State the estimator, inference, or learning method precisely enough to re-implement, and tie it to a quantity that matters (error bound, joules, bits, latency) — not just "accuracy improved."
  • Make the platform reusable and measured (SPOTS track). Give the MCU/SoC, sensor, radio, and toolchain, and justify design choices with measured power, timing, and robustness — a datasheet is not a contribution.
  • Pair every claim with proportional, real-hardware evidence — a measured energy number, a ground-truth-referenced accuracy, a deployment yield — not adjectives.
  • Report deployments honestly. Yield, synchronization error, packet loss, and energy as measured; an idealized deployment reads as a tell.
  • Respect the ≤12-page ACM two-column budget as a design constraint; a paper that only fits by cutting the measurement setup or the limits is over-scoped.
  • Maintain double-blind in self-citations, tool/testbed names, board photos, acknowledgements, funding, and dataset links.

Sensor-systems paper skeleton

Section Job it must do Common failure
Intro Sensing problem, inadequacy, contribution, real-hardware evidence preview, budget — first page Leads with a model/technology trend, not a sensing problem
Background The modality, the platform constraints, why this is hard physically Motivation by assertion; no physical grounding
Method / System The estimator/inference (IP) or the platform/tool (SPOTS), reproducibly Method too thin to re-implement; platform under-specified
Evaluation Each claim answered with measured, ground-truth evidence Simulation or offline accuracy standing in for on-device/in-field results
Energy/latency budget Joules, memory, timing as measured on the real platform "Feasible on embedded devices" with no numbers
Limits / threats Site-specificity, generalization, calibration drift, bounded Generic paragraph untethered from this system
Related work Delta-first against the sensing literature Citation catalog with no contrast

Sentence-level rewrites

Draft pattern IPSN-safe rewrite
"Our method significantly improves accuracy." "reduces localization error to X m (95% CI ...) vs on <N real traces>"
"It is energy-efficient." "consumes X µJ per inference on <MCU> at , measured on an instrumented rail (Table 2)"
"We deploy it in the real world." "deployed <N> nodes for ; packet yield Y%, sync error < Z µs (Fig. 4)"
"Runs in real time on embedded devices." "end-to-end latency X ms on <SoC>; fits <RAM/flash> footprint"
"The model detects the event well." "detection rate D at F false alarms/hour on hand-labeled field audio, per site"

Energy/latency/ground-truth discipline

[Energy]     joules or µJ per operation, measured (rail/shunt/instrument named), not estimated
[Latency]    end-to-end timing on the real SoC/MCU at a stated clock; number of runs
[Footprint]  RAM/flash used vs available; where the model/pipeline had to shrink
[Ground truth] the reference (labels, co-located instrument, surveyed positions) and its own error
[Limits]     site-specificity / calibration drift / generalization -> stated next to the result

Vignette: compressing a deployment paper

A draft with a long system tour, six figures, and a thin evaluation: keep the system description at the level needed to reproduce, the two figures that carry the energy and yield story, a per-site false-alarm table, and a limits subsection; move the full protocol and secondary plots to the artifact with forward references. The test of a good cut: a reviewer should be able to answer "what was measured, on what hardware, against what ground truth, and how well did it hold up?" from the body alone.

Output format

[Writing diagnosis] clear / under-motivated / over-claimed / evidence-mismatched / over-scoped
[First-page fix] <new framing leading with the sensing problem and its budget>
[Claim audit] <claim -> measured evidence -> on real hardware / ground truth? yes/no>
[Budget check] <energy / latency / footprint reported? where>
[Anonymity edits] <tool/testbed names / board photos / self-citations / dataset links to fix>

Version History

  • 9f86f09 Current 2026-07-19 16:04

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Metadata

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Version
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2026-07-19 16:04

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