Claude Skills by brycewang-stanford

Use when targeting The Journal of Allergy and Clinical Immunology (JACI) or deciding whether an allergy/asthma/clinical-immunology study fits this venue. Encodes the journal's fit, the clinical-and-mechanistic immunology evidence bar, reporting-guideline and registration requirements, AAAAI/Elsevier house style, official-submission re-check, and desk-reject heuristics. Venue-fit aid only, not clinical advice.

Use when targeting the Journal of Clinical Endocrinology and Metabolism or deciding whether a clinical-endocrinology or metabolism study fits this venue. Encodes the journal's broad endocrine-organ fit, the clinical-evidence and methodological bar, reporting-guideline and registration requirements, Endocrine Society/OUP house style, official-submission re-check, and desk-reject heuristics. Venue-fit aid only, not clinical advice.

Use when targeting Journal of Hepatology or deciding whether a liver-disease study fits this venue. Encodes the journal's fit, the EASL clinical-and-translational evidence bar, reporting-guideline and registration requirements, Elsevier/EASL house style, official-submission re-check, and desk-reject heuristics. Venue-fit aid only, not clinical advice.

Use when targeting the Journal of the American Society of Nephrology or deciding whether a nephrology clinical, translational, or basic study fits this venue. Encodes the journal's fit across kidney disease, dialysis, transplantation, and renal physiology, the mechanistic and evidence bar, reporting-guideline and registration requirements, ASN house style, official-submission re-check, and desk-reject heuristics. Venue-fit aid only, not clinical advice.

Use when targeting Kidney International or deciding whether a nephrology or hypertension clinical/translational study fits this venue. Encodes the journal's fit with a global ISN perspective, the evidence and mechanistic bar, reporting-guideline and registration requirements, ISN house style, official-submission re-check, and desk-reject heuristics. Venue-fit aid only, not clinical advice.

Use when targeting Nature Reviews Clinical Oncology or deciding whether a clinical-oncology review or perspective fits this invited-review venue. Encodes the journal's fit, the commissioned-review and authoritative-synthesis bar, scope and house style, the topic-proposal route, official-submission re-check, and desk-reject heuristics. Venue-fit aid only, not clinical advice.

Use when targeting Radiology (RSNA) or deciding whether a medical-imaging study fits this venue. Encodes the journal's fit, the diagnostic-accuracy and imaging-methodology bar, STARD/CLAIM reporting and reproducibility expectations, RSNA house style, official-submission re-check, and desk-reject heuristics. Venue-fit aid only, not clinical advice.

Use when targeting Stroke or deciding whether a cerebrovascular-disease study fits this venue. Encodes the journal's fit, the clinical/translational/basic cerebrovascular evidence bar, reporting-guideline and registration requirements, AHA/ASA house style, official-submission re-check, and desk-reject heuristics. Venue-fit aid only, not clinical advice.

Use when targeting The Lancet Diabetes & Endocrinology or deciding whether a diabetes, endocrine, or metabolic study fits this venue. Encodes the journal's fit, the major-trial and population-research evidence bar, reporting-guideline and registration requirements, Lancet specialty house style, official-submission re-check, and desk-reject heuristics. Venue-fit aid only, not clinical advice.

Use when targeting The Lancet Psychiatry or deciding whether a psychiatry or mental-health study fits this venue. Encodes the journal's fit, the clinical-trial, population, and policy evidence bar, reporting-guideline and registration requirements, Lancet specialty house style, official-submission re-check, and desk-reject heuristics. Venue-fit aid only, not clinical advice.

Use when targeting The Lancet Public Health or deciding whether a population-health study fits this venue. Encodes the journal's fit, the population-level intervention, epidemiology, and policy evidence bar, reporting-guideline and registration requirements, Lancet specialty house style, official-submission re-check, and desk-reject heuristics. Venue-fit aid only, not clinical advice.

Use when targeting The Lancet Respiratory Medicine or deciding whether a respiratory or critical-care study fits this venue. Encodes the journal's fit, the practice-changing trial and major-cohort evidence bar, reporting-guideline and registration requirements, Lancet specialty house style, official-submission re-check, and desk-reject heuristics. Venue-fit aid only, not clinical advice.

Use when converting an accepted ACM CoNEXT paper's package into optional ACM reproducibility badges via the CoNEXT reproducibility committee — from the badge opt-in due before submission, to the one-page artifact description due within a week of acceptance, to the Available / Functional / Reusable / Reproduced criteria and evaluator-proof reuse docs.

Use when drafting ACM CoNEXT author responses, covering the initial-review rebuttal and — distinctively — the one-shot "major" revision response letter that must stay double-anonymous, map every "minimum necessary change" to a concrete tracked edit, and survive a single re-review by the original reviewers and a shepherd under PACMNET.

Use when preparing the camera-ready of an accepted ACM CoNEXT paper for its assigned PACMNET issue — systematically de-anonymizing, completing PACMNET journal metadata and ACM rights/CCS/keywords, permanentizing artifact and DOI links, applying any shepherd-required changes, and passing ACM production checks.

Use when designing or auditing the evaluation of an ACM CoNEXT paper — matching evidence to claim shape with real testbeds and deployments, honest and tuned baselines, measurement statistics and uncertainty, trace and config provenance, and contamination-aware ablations for ML-for-networking work.

Use when writing the related-work and positioning of an ACM CoNEXT paper — covering the networking literature lanes (SIGCOMM, NSDI, IMC, SIGMETRICS, MobiCom, CCR), delta-first positioning against the venue's own recent programs, and keeping self-citations double-anonymous.

Use when building the reproducibility story for an ACM CoNEXT paper — pinned traces and configs, a runnable artifact, an honest data-availability posture, and the one-page artifact description the CoNEXT reproducibility committee needs — remembering that the ACM badge opt-in is due before the submission deadline.

Use when reasoning about how an ACM CoNEXT submission is evaluated, covering double-anonymous review, the two-round TPC process with online discussion and a TPC meeting, the Accept / Reject / one-shot "major" revision decision categories, the journal-style revise-and-resubmit re-read by the original reviewers, shepherding, and how CoNEXT's two-cycle process differs from SIGCOMM and NSDI.

Use when auditing an ACM CoNEXT submission for HotCRP readiness, covering the choice between the December and June cycles, the mandatory paper-registration step, the ACM acmart page budget (long ≤16 + ≤4 appendix; short ≤10 + ≤2 appendix), double-anonymous review, the reproducibility badge opt-in due at submission, PACMNET publication, and desk-reject triage before the cutoff.

Use when deciding what goes in the ACM CoNEXT main body versus the appendix budget versus the artifact — splitting content by decision-criticality so nothing a reviewer needs to accept the paper hides in an appendix or repository, within the acmart limits (long ≤4 appendix pages, short ≤2).

Use when deciding whether a networking project belongs at ACM CoNEXT or should be routed to SIGCOMM, NSDI, IMC, SIGMETRICS, MobiCom, or HotNets, and when using CoNEXT's two-cycles-per-year calendar and PACMNET journal-style fit to choose the venue and the cycle by contribution shape and evidence maturity.

Use when planning an ACM CoNEXT campaign backward from a deadline, covering the choice between the December and June submission cycles, the mandatory registration step, the one-shot major-revision window, the reproducibility badge opt-in due at submission, PACMNET camera-ready, and presentation — all on CoNEXT's distinctive two-cycles-per-year calendar.

Use when shaping the prose and structure of an ACM CoNEXT paper — leading with the networking problem and deployment context, tying every claim to a measurement on the real target platform, arguing limitations rather than reciting them, and holding the acmart page budget for long (≤16) and short (≤10) papers.

Use when packaging the artifacts of a CoRL paper — code, training configs, demonstration datasets, policy checkpoints, simulation environments, and benchmark definitions — as anonymous review-time evidence and as durable public releases after acceptance, in a venue with no formal artifact-badging track.

Use when drafting the CoRL rebuttal — a single-page PDF due days after reviews are released, aimed at reviewers, the Area Chair, and the discussion window that follows. Covers triage against the first-round gate, one-page layout economy, presenting new numbers compactly, and tone for an exchange that becomes public on acceptance.

Use when converting an accepted CoRL paper into its final form — the 9-page camera-ready main text with the extra page for review feedback, the final-mode corl LaTeX template, appendix merged into one PDF, de-anonymization, external hosting for videos because PMLR accepts none, and the October deadline into the PMLR volume.

Use when designing or auditing experiments for a CoRL robot-learning paper — seeds and evaluation-episode counts, task-suite breadth, real-robot versus simulation evidence, sim-to-real gap measurement, baseline fairness across BC/RL/VLA families, generalization splits, and statistics for success-rate claims.

Use when positioning a CoRL paper against the literature — the robot-learning lineage across CoRL/RSS/ICRA, the ML-methods stream from NeurIPS/ICLR/ICML, the fast-moving VLA and foundation-model wave, classical robotics baselines, concurrent arXiv work, and PMLR citation hygiene including the year-offset trap.

Use when making a CoRL robot-learning paper reproducible — pinning simulator and driver versions, releasing training configs, demonstration data and checkpoints, documenting hardware setups that cannot be rerun, seed policy, evaluation scripts, and honest availability statements for code, data, and robot platforms.

Use when reasoning about how CoRL reviews a paper — the OpenReview double-anonymous pipeline, reviewer/AC/SAC hierarchy, rubric scoring with weak accept as the acceptance threshold, the first-round rejection gate before rebuttal, the reviewer-AC discussion window, decision meetings, and public reviews for accepted papers.

Use when preparing or auditing a CoRL OpenReview submission — the corl_2026 LaTeX template, the 8-page main text with a mandatory Limitations section counted inside it, uncounted references and appendix, the supplementary file and 250 MB video, double-anonymous rules, abstract registration, and dual-submission checks.

Use when assembling CoRL supplementary material — the strongly encouraged overview video under the 250 MB cap and roughly three minutes, the optional appendix inside the same PDF that reviewers need not read, code and data attachments, and anonymization of everything, with the PMLR no-video rule shaping camera-ready plans.

Use when deciding whether a project belongs at CoRL, the Conference on Robot Learning, or should be routed to ICRA, IROS, RSS, NeurIPS, ICLR, ICML, or a journal — based on whether the learned component is the contribution, what embodied evidence exists, and which reviewer community should judge the claim.

Use when planning a CoRL submission cycle end to end — the late-May abstract and paper deadlines, the summer review window, first-round rejection risk, the August one-page rebuttal and discussion period, autumn decisions, the October PMLR camera-ready, and the November conference — including what to do between milestones.

Use when writing or revising a CoRL paper's prose — leading with the embodied task and the learned component, calibrating claims to evaluation scale, writing the mandatory Limitations section as a scored asset, fitting the argument into 8 pages, and satisfying a dual reviewer audience of ML and robotics readers.

Use when analyzing data and fitting/comparing models for a Cognitive Psychology (Elsevier) manuscript. The journal expects principled model fitting and comparison (AIC/BIC/Bayes factors), parameter and model recovery, (generalized) linear mixed models or hierarchical Bayesian estimation where apt, and effect sizes with uncertainty — all reproducible from shared code. Guides the analysis and modeling; it does not fabricate results.

Use when positioning a Cognitive Psychology (Elsevier) manuscript against the field, especially against rival models and prior empirical programs. In a long-form, model-driven venue, positioning means showing what theoretical question your model adjudicates and why prior accounts fall short. Stakes the contribution against the right contrast class; it does not write the full literature review.

Use when meeting Cognitive Psychology (Elsevier) open-science expectations — sharing data, model code, analysis scripts, and materials so the modeling is reproducible, depositing in repositories with persistent identifiers, completing the Elsevier research-data and competing-interest declarations, and preregistering where applicable. Prepares compliance; it does not waive requirements. Verify current wording on the official guide for authors.

Use when writing the response to a Cognitive Psychology (Elsevier) major/minor revision. Reviews here often demand added experiments, more model comparisons, recovery analyses, or fuller reproducibility, so the response must address every point and strengthen the model-driven inference. Structures the response letter; it does not fabricate new results or model fits.

Use when you need to understand how Cognitive Psychology (Elsevier) evaluates a manuscript — editorial triage for theoretical impact and fit, expert review weighing model rigor, recovery, design, and reproducibility, and the long revision cycles typical of a model-driven journal. Use when stress-testing a paper before submission or interpreting a decision letter. Sets expectations and shapes the paper to survive review; it does not contact editors.

Use when designing the experiments for a Cognitive Psychology (Elsevier) manuscript so they tightly control confounds, discriminate competing models, and have adequate power across a multi-experiment program. Hardens stimulus construction, counterbalancing, design logic, and sample-size justification; it does not write analysis or modeling code.

Use when running the final pre-submission preflight for Cognitive Psychology (Elsevier) via Editorial Manager — scope/length fit, abstract and keywords, APA-style reporting, model-comparison completeness, reproducible model/analysis code, and the Elsevier research-data and competing-interest declarations. Final checks; it does not draft content. Verify volatile specifics on the official guide for authors.

Use when building tables and figures for a Cognitive Psychology (Elsevier) manuscript. Exhibits here carry the experiment-to-model-fit argument — they should overlay model predictions on data, show distributions and uncertainty, and report parameter estimates, not just bars of means. Designs exhibits; it does not run the analysis or fit the model.

Use when stating the theory, formalizing the model, and deriving predictions for a Cognitive Psychology (Elsevier) manuscript. The journal rewards a formal/computational account whose parameters mean something and whose predictions discriminate it from rivals. Structures the theory and the model that the experiments test; it does not fit the model or run analyses.

Use when deciding whether a cognition project fits Cognitive Psychology (Elsevier) and what contribution shape to target. The journal favors longer, integrative, model-driven work that produces a substantial theoretical advance — not a single isolated effect. Frames the question and the model-or-theory payoff; it does not collect data.

Use when starting or navigating any Cognitive Psychology (Elsevier) manuscript and you are unsure which sub-skill applies. Use when choosing among manuscript types or returning with a decision letter. Routes by lifecycle stage and contribution type (multi-experiment empirical, experiment-plus-model, modeling-led, theoretical/review), and flags the journal's long-form, model-driven house style and code-transparency expectations. It dispatches; it does not draft content.

Use when drafting or polishing a Cognitive Psychology (Elsevier) manuscript — a long-form, integrative article that must weave multiple experiments and a formal model into one continuous theoretical argument. Tightens structure, the experiment-to-model narrative, and APA-style reporting; it does not invent content. Verify the journal's current length and format guidance on the official page.

Use when executing and reporting the analysis for a Communication Research (CR) manuscript so it survives expert, double-anonymized review — ANOVA/regression/SEM, mediation/moderation with honest uncertainty, reliability, and APA statistical reporting. Guides analysis norms; it does not fabricate results.

Use when positioning a Communication Research (CR) manuscript against the literature so it reads as a cumulative, theory-testing contribution to communication science. CR reviewers expect engagement with the empirical communication literature and the rival accounts your hypotheses adjudicate. Stakes the contribution; it does not write the lit review.