cikm-skills

Plugin cikm-skills from marketplace awesome-journal-skills in brycewang-stanford/Awesome-Journal-Skills. Commands read from the repo's manifest — 1 month ago.

Skills (12)

• cikm-artifact-evaluation

  Use when packaging the code, datasets, knowledge graphs, prompts, and demo systems around a CIKM paper — choosing the artifact form per track (research, applied, resource, demo), meeting the resource track's reuse-and-documentation bar, and staging anonymous review artifacts into citable public rele

• cikm-author-response

  Use when preparing author-side communication around CIKM reviews — drafting for a response window if the cycle offers one (unconfirmed for 2026), writing camera-ready revision notes that answer reviewer concerns, handling post-decision chair correspondence, and converting rejection reviews into a re

• cikm-camera-ready

  Use when turning an accepted CIKM paper into its ACM proceedings version inside the short notification-to-camera-ready window, covering de-anonymization, the e-rights and TAPS pipeline into the ACM Digital Library, CCS concepts and metadata, GenAI-disclosure retention, artifact link publication, and

• cikm-experiments

  Use when designing or auditing the empirical program of a CIKM paper — matching evidence to the claim's lanes across retrieval, mining, and knowledge-management evaluation cultures, choosing datasets and baselines that survive a blended panel, isolating the boundary mechanism, and meeting applied-tr

• cikm-related-work

  Use when positioning a CIKM submission against three literatures at once — retrieval, mining, and knowledge management/databases — building the boundary-work paragraph, guarding against misattributing SIGIR/KDD/ICDM classics to CIKM, and handling preprints under the arXiv-declaration and dual-submis

• cikm-reproducibility

  Use when hardening the reproducibility of a CIKM paper — pinning the pipeline stages where IR, mining, and knowledge-management results silently diverge, documenting KGs and enterprise data that cannot be released, keeping the GenAI disclosure consistent with how code and data were produced, and pre

• cikm-review-process

  Use when reasoning about CIKM peer review — the EasyChair double-blind pipeline, the mixed IR/data-mining/knowledge-management reviewer pool, per-track evaluation criteria, the ACM Peer Review Policy including the no-AI-written-reviews rule, notification timing, and what actually moves borderline de

• cikm-submission

  Use when auditing a CIKM submission for EasyChair readiness across the five tracks, covering page budgets with appendices counted inside, the mandatory GenAI Usage Disclosure section, author-reviewer nomination, double-blind rules with arXiv declaration, the abstract-gate authorship freeze, and desk

• cikm-supplementary

  Use when deciding what supporting material accompanies a CIKM submission given budgets that count appendices inside the page limit, structuring the in-PDF appendix versus the anonymously cited artifact, keeping both double-blind, and handling the uncounted GenAI-disclosure and reference sections cor

• cikm-topic-selection

  Use when deciding whether a project fits CIKM, the tri-community ACM venue spanning information retrieval, data mining, and knowledge management/databases, when weighing CIKM against SIGIR, KDD, WSDM, TheWebConf, SIGMOD/VLDB, or ISWC, and when choosing among CIKM's five tracks before writing begins.

• cikm-workflow

  Use when planning a CIKM project calendar across the May abstract/paper gates, June short-track gates, August notification and camera-ready, and the November conference, including the post-submission phase now live in the 2026 cycle, multi-track coordination, and fallback planning toward CIKM 2027 o

• cikm-writing-style

  Use when revising a CIKM manuscript for the tri-community readership — writing an opening that lands with IR, data-mining, and knowledge-management reviewers simultaneously, compressing into appendix-inclusive page budgets, keeping claims inside the evidence, and maintaining double-blind and disclos

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