Browse reusable Agent Skills, each with a clear purpose and practical guidance.
Use when interpreting Review of Finance desk screening, Screen Reports, double-blind review, top-three-finance-journal referee standards, two-round decision philosophy, Fast-Track timing, and sanctions for undisclosed resubmission or dual submission.
Use when an empirical analysis should be RUN and audited, not just advised — DiD, IV, RDD, synthetic control, DML, multiple-testing, sensitivity. Maps the design to the concrete StatsPAI / Stata MCP tools in this environment and reports the fitted, audited number. Defers result placement and house style to the target journal's pack.
Use when positioning a SenSys paper against the sensing, embedded, IoT, and on-device-AI literature — sweeping the right venue lanes after the SenSys/IPSN/IoTDI merger, proving each citation's venue via dblp/ACM DL against the MobiCom/NSDI/IPSN traps, distinguishing your mechanism from the nearest prior system, and self-citing blind-safely.
Use to understand how Social Forces (SF) evaluates a manuscript — double-anonymized review via ScholarOne, what expert reviewers weigh (rigor, general significance, theoretical grounding), the typical decision categories, and the journal's reported review timeline. Sets expectations and shapes the paper to survive review; it does not contact editors.
Use when deciding whether a project fits Social Forces (SF) and how to frame it. SF is a general social-science journal (centered on sociology) that prizes methodological rigor and a theoretically grounded contribution of interest to a broad audience. Helps frame the question and judge fit; it does not collect data.
Use when positioning an ACM SIGCOMM submission against the networking literature — sweeping SIGCOMM, NSDI, MobiCom, CoNEXT, IMC, and SIGMETRICS plus journals, proving each placement via dblp and the ACM Digital Library, distinguishing main-track papers from CCR editorials, handling concurrent work, and keeping self-citation double-blind-safe.
Use when building the real-data empirical illustration for a Sociological Methods & Research (SMR) paper — a demonstration that the method changes a substantive conclusion, not a decorative example. Designs the illustration; does not derive properties or design the Monte Carlo.
Use to build a sociological problem consciousness (问题意识) for 《社会学研究》 (Sociological Studies) — turning a variable relationship or a pile of fieldwork into a question about how a social mechanism, structure, or process works. Use when the manuscript still reads as "X affects Y" without a sociological stake.
Use when reasoning about how a SOSP submission is evaluated — double-blind HotCRP reviewing, staged review rounds, PC-chair-audited conflicts, the pre-PC-meeting author response, the single-track PC meeting where every decision is argued live, notification, and shepherded acceptance outcomes.
Use when choosing or sharpening a research question for a The Accounting Review (TAR) manuscript — testing whether the question is contribution-driven, identifiable with accounting data, and a fit for TAR versus JAR/JAE or a specialist AAA section journal. Selects and scopes the question; it does not build the model (tar-theory-development) or design identification (tar-methods).