IPSN Skills

A 12-skill depth pack for ACM/IEEE IPSN (Information Processing in Sensor Networks), the CPS-IoT Week venue for sensing theory, on-device/TinyML, and localization: routing between the Information Processing (IP) and Sensor Platforms, Tools and Design Methods (SPOTS) tracks, double-blind HotCRP submission on the ACM template, real-deployment evidence, the Best Research Artifact Award, and the hones

by @brycewang-stanford 11 skills

Install

npx skillmds@latest add plugin:brycewang-stanford/ipsn-skills

One command, no setup. In Claude Code it lands as a managed plugin you can enable, disable or remove with /plugin. On any other agent it installs the 11 skills into that agent's own folder.

Or inside Claude Code

In the Plugins tab, add this marketplace:

skillmds/skillmd
/plugin install brycewang-stanford-ipsn-skills@skillmd

Adds the marketplace once; later plugins need the second line only.

Or install by hand

Download the plugin and unzip its skills/ folder into your agent's skills directory. Works with every agent, no CLI needed.

Download plugin Paths per agent

Just the markdown? SKILL.md files only.

This plugin

skills: 11
authors: 1

Published by a registry member. Review its skills before installing.

Skills in this plugin

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Ipsn Submission · brycewang-stanford
Use when auditing an IPSN-lineage submission for HotCRP readiness, covering the IP-vs-SPOTS track choice, the ACM Primary Article Template and ≤12-page inclusive budget, the double-blind sweep for hardware/deployment papers, dataset/artifact links, and desk-reject triage — routed to the current successor (SenSys) call because IPSN no longer runs standalone.

1k repo stars
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Ipsn Experiments · brycewang-stanford
Use when designing or auditing IPSN-lineage evaluations, covering real testbeds and deployments, ground-truth instrumentation, energy/latency/footprint measurement on real hardware, on-device/TinyML profiling, estimation-theoretic baselines and bounds, and matching evidence to the shape of each sensing claim across the IP and SPOTS tracks.

1k repo stars
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Ipsn Camera Ready · brycewang-stanford
Use when preparing an accepted IPSN-lineage paper for camera-ready, covering de-anonymization, the ACM Primary Article Template and the dual ACM/IEEE metadata (CCS concepts, ORCID, DOI, IEEE PDF eXpress/e-copyright), integrating required changes without scope creep, permanentizing dataset/firmware links, and the artifact-award handoff.

1k repo stars
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Ipsn Related Work · brycewang-stanford
Use when positioning an IPSN-lineage submission against the sensor-networks and information-processing literature (IPSN, SenSys, MobiCom, MobiSys, INFOCOM, and signal-processing venues), writing delta-first contrast rather than a citation catalog, keeping self-citations double-blind, and handling concurrent, preprint, and prior-version overlap.

1k repo stars
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Ipsn Supplementary · brycewang-stanford
Use when deciding what belongs in an IPSN-lineage paper body versus its artifact, appendix, and demo/poster track, covering the ≤12-page ACM two-column budget, the rule that decision-critical evidence stays inside the reviewed pages, double-blind supplementary material, dataset release, and how to split a sensor-systems paper between body and package.

1k repo stars
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Ipsn Writing Style · brycewang-stanford
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.

1k repo stars
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Ipsn Review Process · brycewang-stanford
Use when reasoning about how an IPSN-lineage submission is evaluated, covering double-blind review, the per-track (IP / SPOTS) program committees, the rebuttal, Best Paper and Best Research Artifact judging, and how IPSN's process differs from SenSys's revision model, OpenReview venues, and CPS-IoT Week neighbors.

1k repo stars
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Ipsn Author Response · brycewang-stanford
Use when drafting an IPSN-lineage rebuttal, covering the double-blind response to sensor-systems reviewers on ground truth, baseline fairness, deployment realism, energy accounting, and simulation-vs-real-hardware doubts, without leaking identity and without promising experiments not yet run.

1k repo stars
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Ipsn Reproducibility · brycewang-stanford
Use when strengthening IPSN-lineage reproducibility for a hardware/embedded/deployment artifact, covering firmware and board files, pinned toolchains, raw traces and calibration, honest degrees of reproducibility for a physical system, anonymized-but-runnable artifacts, and consistency between the paper and the package.

1k repo stars
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Ipsn Topic Selection · brycewang-stanford
Use when deciding whether a sensing/embedded project is an IPSN Information-Processing (IP) contribution or a Sensor Platforms, Tools and Design Methods (SPOTS) contribution, and whether it should go to the IPSN lineage (now the merged SenSys at CPS-IoT Week), a CPS-IoT Week neighbor (RTAS/ICCPS/HSCC), MobiSys/MobiCom, INFOCOM, or a signal-processing journal.

1k repo stars
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Ipsn Artifact Evaluation · brycewang-stanford
Use when packaging an IPSN-lineage artifact for the ACM badges and the IPSN Best Research Artifact Award, covering hardware-plus-software artifacts (firmware, board files, datasets), what sensor-systems evaluators check first, DOI-issuing archives, evaluator-proof documentation for a physical system, and the separate post-acceptance timing.

1k repo stars