brycewang-stanford/Awesome-Journal-Skills

Prepare AAAI artifact packages (code, data, appendices) for reproducibility while maintaining double-blind submission rules. Avoid common mistakes that lead to summary rejection.

Helps draft AAAI author responses under strict rebuttal limits. Use it to prioritize factual corrections, handle AI-generated review points, and stay within AAAI rules on length, URLs, and new results.

Use when preparing an accepted AAAI paper for camera-ready submission. It covers page limits, template compliance, deanonymization, copyright transfer, registration, and final source-file checks.

Audit AAAI experiments for baselines, ablations, significance, robustness, human evaluation, and reproducibility checklist alignment, helping papers survive Phase-1 review by the broad-AI program committee.

Guides writing the related work section for AAAI papers by clearly positioning novelty against archival and contemporaneous work, while adhering to AAAI’s dual-submission and AI-as-source policies.

Audit an AAAI paper's reproducibility checklist, experimental traceability, seed/hyperparameter reporting, compute disclosure, dataset licensing, and code readiness to survive AAAI's Phase-1 rigor review.

Guides authors through AAAI's two-phase review process, including Phase 1 rejection risks, AI-assisted reviews, author feedback, and final decisions. Use this when planning submissions or crafting rebuttals for AAAI.

Audit an AAAI conference submission for compliance with OpenReview requirements, double-blind anonymity, page limits, reproducibility checklist, author limits, and AI-use policies to prevent desk rejection.

Organize supplementary material for AAAI paper submissions, ensuring main-paper-critical evidence is not hidden, maintaining double-blind and immutability requirements.

Helps researchers evaluate if a project is a strong AAAI submission, suggests reframing for dedicated tracks like AI for Social Impact, or routes to specialist venues such as IJCAI, NeurIPS, ICML, ICLR, and others.

Use when planning an AAAI project timeline from topic selection through abstract, OpenReview submission, two-phase review, rebuttal, decision, camera-ready, registration, presentation, and public artifact release.

Revises AAAI manuscripts for readability by a broad AI program committee, focusing on clear contribution statements, two-column readability, and alignment with reproducibility and ethics checklists.

Guides the packaging of multiagent code, game definitions, opponent sets, and logs for AAMAS artifact evaluation, ensuring reviewers can inspect and re-run interaction claims like emergent cooperation or convergence to equilibrium.

Guides drafting an AAMAS rebuttal to preliminary OpenReview reviews, ensuring compliance with double-blind and no-new-results constraints, and addressing game-theory, MARL, and systems reviewers to craft a concise acceptance rationale.

Use when preparing an accepted AAMAS paper for the IFAAMAS open-access camera-ready, covering author de-anonymization, proceedings metadata, two-column reflow of game figures and learning curves, resolving rebuttal-stage promises, registration, in-person presentation, and the public code and environment release for a multiagent paper.

Guides the design and audit of multi-agent experiments for AAMAS, focusing on interaction claims, opponent selection, equilibrium metrics, and reproducibility. Ensures experiments probe strategic interactions rather than single-agent performance.

Use this skill to audit the novelty and eligibility of an AAMAS submission. It checks cross-community literature coverage (AAMAS, AAAI, NeurIPS, EC, etc.) and helps craft a positioning that distinguishes interaction novelty from engineering improvements.

Audit and strengthen reproducibility evidence for multi-agent interaction claims in AAMAS papers, covering game definitions, opponent sets, seeds, uncertainty, and artifact consistency.

Explains the AAMAS peer review process, from submission to camera-ready, including rebuttal strategy and acceptance criteria for multiagent systems papers.

Audits an AAMAS paper submission for track selection, page limits, anonymity, supplementary files, dual-submission rules, and desk-reject triggers. Use before uploading to avoid silent rejections.

Guides on structuring supplementary material for AAMAS submissions, including proofs, game definitions, experiments, and code archives, while meeting double-blind and size constraints.

Evaluates whether a research project is a strong fit for the AAMAS conference versus AAAI, IJCAI, NeurIPS, ICML, EC, or JAAMAS, using interaction primitives and framing tests.

Manage the full lifecycle of an AAMAS conference paper submission, from venue fit and abstract to camera-ready, with backward planning and milestone tracking for game-theory-plus-experiments papers.

Provides guidelines and automated checks to ensure AAMAS papers clearly state the multiagent interaction contribution, name solution concepts, and pair claims with proofs or experiments. Ideal for revising AAMAS submissions to meet conference standards.

Use when packaging code, datasets, prompts, model outputs, or annotation materials for an ACL submission, covering anonymized supplements, Responsible NLP checklist items, licensing, data statements, and post-acceptance release.

ACL Author Response helps draft anonymous replies to ACL Rolling Review reviews in OpenReview before meta-review. It is used to decide what to address now, what to defer, and how to phrase corrections for the AC.

ACL Camera Ready helps prepare an accepted ACL or Findings paper for final submission, including the extra page, de-anonymization, AI-use disclosure, Anthology metadata, and required publication checks. Use it when converting a reviewed draft into the camera-ready version and presentation materials.

ACL Experiments helps design or audit experiments for ACL papers, including baselines, multi-dataset and multilingual evaluation, significance testing, human evaluation, contamination checks, ablations, and error analysis. Use it when preparing evidence for an NLP research claim.

ACL Related Work helps position an ACL submission against recent NLP literature and check citation hygiene. Use it to handle Anthology-versus-arXiv citations, concurrent preprints, self-citation, and resubmission overlap.

ACL Reproducibility helps strengthen an ACL/ARR paper’s reproducibility evidence by checking checklist responses, experiment reporting, contamination risks, variance, and consistency between the paper and supplement. Use it before submission or camera-ready to audit claims against the Responsible NLP checklist.

ACL Review Process models how an ACL paper moves through ARR, meta-review, and venue commitment. It is used to interpret reviews, understand who decides main conference vs. Findings, and plan resubmission or ethics escalation.

ACL Submission audits an ACL Rolling Review submission before deadline, checking page limits, Limitations, anonymity, preprint and dual-submission declarations, resubmission links, and desk-reject risks. Use it when preparing a paper for OpenReview and ACL commitment.

ACL Supplementary helps you split an ACL paper between the main body, required Limitations, optional ethics text, appendices, and software or data archives. Use it to keep decision-critical claims in the reviewed pages and package supplementary material correctly.

ACL Topic Selection helps decide whether an NLP project fits ACL, EMNLP, NAACL, EACL, TACL, Computational Linguistics, COLM, or an ML venue. It also guides contribution type, long-vs-short paper choice, theme-track fit, and framing before drafting.

ACM MM Author Response helps draft an anonymous ACM Multimedia rebuttal that prioritizes factual corrections, adds small confirmatory results, and makes calibrated concessions. It is used when responding to area chairs and reviewers within rebuttal policy limits.

Executes and reports qualitative or quantitative analysis for ASQ manuscripts, making the evidence-to-theory link transparent. Covers coding, data-to-theory tables, robustness checks, and mechanism evidence.

Acl Workflow plans ACL paper timing across ARR cycles, response windows, commitment decisions, and resubmission loops. Use it when scheduling an ACL submission and camera-ready path around conference deadlines.

Acl Writing Style helps revise ACL papers to match computational-linguistics house style. It focuses on task-first framing, scoped claims, evidence-backed examples, anonymity-safe wording, and concise 8-page or 4-page formatting.

Acm Mm Artifact Evaluation helps package ACM Multimedia code, models, datasets, or media for the right track and review process. It is used to choose blinding, licensing, and the separation between anonymous review and public release.

CCS Artifact Evaluation helps package accepted security research artifacts for ACM badges and committee review. It covers reproducible setup, turnkey attack or defense demos, safe handling, and justifying withheld files.

CCS Author Response helps draft anonymous ACM CCS rebuttals during the HotCRP author-response window. It focuses replies on decision-critical issues like threat models, adaptive attacks, ethics, disclosure, and evidence already in the submission.

CCS Camera Ready prepares an accepted ACM CCS paper for the final proceedings version. It covers de-anonymization, ACM sigconf formatting, rights forms, badge placement, and shepherd or minor-revision changes.

CCS Experiments helps audit ACM CCS attack and defense evaluations for claim-to-evidence fit, adaptive attackers, baselines, and measured overhead. Use it when preparing or reviewing experiments for a security paper submission.

CCS Related Work helps position an ACM CCS submission against the right security literature and prior disclosures. It is used to check novelty, related work, and archival-overlap risks before submission.

CCS Reproducibility helps authors document claims, artifacts, and measurement details for ACM CCS submissions. Use it to map attacks, defenses, and datasets to evidence and to state honest sharing limits.

CCS Review Process explains ACM CCS peer review, including HotCRP cycles, rebuttals, decision categories, ethics scrutiny, and proceedings outcomes. Use it when planning review-stage strategy or interpreting a CCS decision.

CCS Submission audits an ACM CCS paper for HotCRP registration, page limits, anonymization, ethics text, and dual-submission risks. Use it before submission to catch desk-reject issues and confirm final-week requirements.

CCS Supplementary helps assemble ACM CCS appendices and supporting files under the 12-page body, anonymity, and reviewer-discretion rules. It covers proofs, transcripts, measurements, ethics sections, and double-blind archives for security papers.

CCS Topic Selection helps decide whether a security project fits ACM CCS or a closer venue such as IEEE S&P, USENIX Security, NDSS, PETS, or a crypto/theory venue. It also helps name the contribution type and sharpen the threat model before writing.

CCS Workflow plans an ACM CCS submission across the dual review cycles, from abstract registration and full-paper upload through rebuttal, acceptance, artifact evaluation, camera-ready, and presentation. It is used to back-plan deadlines and track security-conference milestones.

CCS Writing Style helps revise ACM CCS papers for explicit threat models, calibrated claims, and double-blind wording. Use it when tightening a security paper to fit 12-page sigconf constraints and reviewer expectations.

Designs rigorous empirical evaluations for software engineering research papers, ensuring proper evidence matching, statistical analysis, and methodological transparency for conferences like ESEC/FSE.

Use when revising an IPSN paper to ensure it leads with a sensing problem, includes real-hardware evidence, energy/latency/accuracy budgets, honest deployment reporting, double-blind wording, and disciplined use of the ACM two-column page budget.