Twelve IPSN-specific skills for the ACM/IEEE International Conference on Information Processing in Sensor Networks and its move into the merged SenSys (Embedded AI and Sensing Systems) at CPS-IoT Week, grounded in the IPSN 2024 (23rd, Hong Kong) call, CPS-IoT Week pages, ACM Digital Library, IEEE Xplore, and dblp.
Plugin ipsn-skills from marketplace awesome-journal-skills in brycewang-stanford/Awesome-Journal-Skills. Commands read from the repo's manifest — 1 month ago.
ipsn-artifact-evaluationUse 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
ipsn-author-responseUse 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.
ipsn-camera-readyUse 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 l
ipsn-experimentsUse 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 sens
ipsn-related-workUse 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 co
ipsn-reproducibilityUse 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 p
ipsn-review-processUse 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
ipsn-submissionUse 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 succ
ipsn-supplementaryUse 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 s
ipsn-topic-selectionUse 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/HSC
ipsn-workflowUse when planning an IPSN-lineage project timeline from track/venue selection through the CPS-IoT Week deadline, double-blind submission, deployment and hardware logistics, rebuttal, the Best Research Artifact Award, and the dual ACM/IEEE camera-ready — with honest handling of the fact that IPSN mer
ipsn-writing-styleUse 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
AI-first computer-science conference skill stack: 155 conference fit-and-submission profiles plus a CS/AI router. Covers top AI/ML, data mining, vision, NLP, robotics, HCI, systems, security, software engineering, programming languages, databases, and theory venues, with current-cycle CFP and author-kit re-check discipline.
156 skills
English natural-science / clinical / physical / formal-science journal routing and per-journal fit skills with official-submission-check discipline.
155 skills
Chinese social-science journal routing and per-journal fit skills with official-submission-check discipline.
103 skills
English economics / business journal routing and per-journal fit skills with official-submission-check discipline.
101 skills
English engineering / technology journal routing and per-journal fit skills with official-submission-check discipline.
41 skills
English humanities journal routing and per-journal fit skills with argument-, source-, and style-guide discipline.
37 skills
5 skills + 35 modes + Material Passport pipeline. Includes v3.6.7 cross-model audit gate and v3.6.8 generator-evaluator contract.
5 skills · 16 commands · 4 agents · hooks
Exa AI web search, deep research, and content extraction. Provides MCP tools and research skills for comprehensive web search, people discovery, company research, academic papers, and more.
2 skills · 1 MCP server
Exa AI web search, deep research, and content extraction. Provides MCP tools and research skills for comprehensive web search, people discovery, company research, academic papers, and more.
2 skills · 1 MCP server
Enterprise / cross-functional Research Operations domain — the managed counterpart to the academic research/ domain. v2.9.0 ships 5 skills: orchestrator (context: fork), clinical-research (protocol synopsis, endpoint selection, sample-size/power for means/proportions/survival, phase-gate feasibility), research-finance (R&D budgeting with F&A split, burn/runway, capitalize-vs-expense routing, portfolio ROI), market-research (TAM/SAM/SOM top-down and bottoms-up, survey sampling with FPC, Kotler segmentation), and product-research (goal-matched study design, method-based saturation, insight synthesis flagging single-source anecdotes). Hard rules: outputs are estimates routed to a named clinical or finance owner, market sizes show method + assumptions, product insights require recurrence across independent participants. 24 stdlib Python tools, 12 reference docs. Distinct from ra-qm-team, finance, research/grants, product-team, and marketing-skill.
6 skills · 7 commands · 2 agents
Contribution-first, reviewer-aware academic paper and report writing system.
2 skills
Semi-automated research assistant with skills for literature review, experiments, analysis, writing, and project knowledge management
45 skills · 66 commands · 6 agents · hooks
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