Browse reusable Agent Skills, each with a clear purpose and practical guidance.
Use when building the related-work section and positioning for a CVPR paper, covering literature that moves at arXiv speed, concurrent-work etiquette, the CVPR/ICCV/ECCV sibling triangle, double-blind self-citation, verifying that cited "CVPR papers" are actually CVPR papers, and defining deltas against the true nearest neighbors.
Use when hardening a CVPR paper's reproducibility story, covering the Compute Reporting Form's hardware and compute sections, training-recipe disclosure, benchmark protocol and split hygiene, seed and variance reporting for vision experiments, and closing the gaps reviewers probe at a benchmark-driven venue.
Use when deciding whether a project belongs at CVPR or should route elsewhere, covering what counts as a vision contribution at the field's flagship, fit tests for methods, datasets, and application papers, realistic odds at 25% acceptance and 16k submissions, and routing to ICCV, ECCV, WACV, 3DV, NeurIPS, or a journal.
Use when reasoning about how an ACM/IEEE Design Automation Conference (DAC) Research Manuscript is evaluated, covering double-blind TPC review, the novelty-plus-QoR decision criteria, program-committee discussion, the accept/reject (no major-revision) outcome, the ~20-25% selectivity, and how DAC's industry-facing, single-shot process differs from the architecture venues' rebuttal-and-revision cycles.
Use to understand how Demography (PAA / Duke University Press) evaluates a manuscript — double-blind review, pre-review/desk screening by the Editor or a Deputy Editor, the role of topic-area Deputy Editors, and the grounds for desk rejection (inappropriate fit or unlikely to receive favorable reviews). Sets expectations and shapes the paper to survive review; it does not contact editors.
Use when deciding whether a project fits Demography (PAA / Duke University Press) and which article type to target. Demography is the multidisciplinary population-science flagship, so the test is general interest to demographers and a genuine population-change question, not just use of demographic data. Helps frame the question; it does not collect data.
Use when analyzing and reporting results for a Developmental Psychology (APA) manuscript. The journal expects analyses that model developmental change correctly — growth-curve/multilevel/SEM, mediation/moderation, measurement invariance — with effect sizes and confidence intervals, JARS-compliant disclosure, and a clear confirmatory/exploratory split. Guides analysis norms; it does not fabricate results.
Use when designing studies for a Developmental Psychology (APA) manuscript so they can actually support a developmental-change claim. Covers age-appropriate experimental and longitudinal designs, age vs. cohort confounds, attrition, measurement invariance across ages, sample-size justification, and ethics with minors and vulnerable populations. Strengthens the design and pre-analysis plan; it does not write code.
Use when targeting 《电子政务》(E-Government — 中国科学院主管、中国科学院文献情报中心主办, 2004 年创刊) or deciding whether a Chinese digital-government/e-governance manuscript fits this journal. Encodes the journal's fit, framing, abstract/citation house style, multi-stage review, official-submission re-check, and desk-reject heuristics.
Use when positioning an EACL paper against fast-moving NLP literature, covering ACL-Anthology-first citation, correct Findings attribution, handling concurrent preprints fairly, freshness sweeps across recent *ACL rounds and European venues like LREC-COLING, and framing related work as a contrastive argument rather than a list.