Claude Skills by thedixitjain

'Configure incremental load setup operations. Auto-activating skill for Data Pipelines. Triggers on: incremental load setup, incremental load setup Part of the Data Pipelines skill category. Use when working with incremental load setup functionality. Trigger with phrases like \"incremental load setup\", \"incremental setup\", \"incremental\". '

High-level technical SEO and site architecture auditor. Invoke to scan local or live environments for indexing, crawl budget, and structural errors.

Records Clean Room initialization preferences, separated artifact locations, model policy, schema profile, and clean-safe rule defaults before a clean-room run starts or resumes.

'Implement Instantly.ai lead data management, GDPR/CAN-SPAM compliance, and list operations. Use when handling lead imports, managing block lists, implementing unsubscribe flows, or ensuring compliance with email regulations. Trigger with phrases like \"instantly leads\", \"instantly data\", \"instantly GDPR\", \"instantly block list\", \"instantly lead management\", \"instantly unsubscribe\". '

'Configure Instantly.ai workspace access control, team management, and API key governance. Use when managing workspace members, setting up team permissions, or implementing API key governance for multi-user Instantly workspaces. Trigger with phrases like \"instantly team\", \"instantly permissions\", \"instantly workspace members\", \"instantly access control\", \"instantly rbac\". '

'Configure Instantly.ai across development, staging, and production environments. Use when setting up multi-workspace deployments, isolating test from production, or managing per-environment API keys and webhook endpoints. Trigger with phrases like \"instantly environments\", \"instantly staging\", \"instantly dev prod\", \"instantly multi-env\", \"instantly workspace isolation\". '

'Apply production-ready Instantly.ai API client patterns for TypeScript and Python. Use when building reusable API wrappers, implementing retry logic, or establishing coding standards for Instantly integrations. Trigger with phrases like \"instantly SDK patterns\", \"instantly best practices\", \"instantly client wrapper\", \"instantly code patterns\", \"idiomatic instantly\". '

'Implement Instantly.ai webhook event handling with real API v2 event types. Use when setting up webhook endpoints, processing email events, or building CRM sync pipelines from Instantly notifications. Trigger with phrases like \"instantly webhook\", \"instantly events\", \"instantly webhook handler\", \"handle instantly events\", \"instantly notifications\". '

'Manage Intercom contacts: create, search, update, merge leads into users. Use when building contact management features, syncing user data, or implementing contact search and segmentation against the Intercom REST API. Trigger with phrases like \"intercom contacts\", \"intercom users\", \"intercom leads\", \"create intercom contact\", \"search intercom contacts\", \"merge intercom lead\". '

'Optimize Intercom API costs through caching, request reduction, and usage monitoring. Use when analyzing Intercom API usage, reducing unnecessary requests, or implementing usage tracking and budget awareness. Trigger with phrases like \"intercom cost\", \"intercom billing\", \"reduce intercom requests\", \"intercom pricing\", \"intercom usage\", \"intercom budget\". '

'Implement Intercom data handling for GDPR, contact export, data retention, and PII. Use when handling sensitive Intercom contact data, fulfilling a data subject access or deletion request, redacting PII in logs, or setting retention policy for cached Intercom records. Trigger with phrases like \"intercom data\", \"intercom PII\", \"intercom GDPR\", \"intercom data retention\", \"intercom privacy\", \"intercom CCPA\", \"intercom data export\", \"intercom delete contact\". '

'Implement Intercom webhook handling and data event tracking. Use when setting up webhook endpoints, processing Intercom notifications, or submitting custom data events for contact activity tracking. Trigger with phrases like \"intercom webhook\", \"intercom events\", \"intercom webhook signature\", \"handle intercom events\", \"intercom data events\", \"track intercom events\". '

Use when targeting International Conference on Very Large Data Bases (VLDB) or deciding whether a computer-science manuscript fits this venue. Encodes conference fit, framing, evidence bar, submission-cycle checks, rebuttal posture, and desk-reject risks for database flagship.

Use when executing and reporting the empirical analysis (or the formal-model results) for an International Organization (IO) manuscript so it survives expert double-blind IR review and IO's pre-publication verification. The IO editorial staff re-run quantitative analyses and check formal proofs before final acceptance, and IR data raise distinctive estimation problems (dyadic dependence, selection into treaties/alliances/conflict, gravity structure). Guides analysis and reporting; it does not...

Use when preparing the replication/transparency materials for an International Organization (IO) manuscript. IO's signature requirement is verification BEFORE final acceptance — the editorial staff request data and code at conditional acceptance, IO staff re-run quantitative results and check proofs of formal models, and editors withhold final acceptance until all reported results are confirmed; materials then deposit to the IO Dataverse with a DOI and a Data Availability Statement. Prepares ...

Research prediction-market events, venues, underliers, liquidity, and news context for Itô basket workflows. Use for read-only market intelligence, API-gated Itô exploration, and source-grounded prediction-market briefings without investment advice or live trading.

Use when running and reporting the empirical analysis for a Journal of Accounting and Economics (JAE) manuscript — building the archival sample, choosing fixed effects and clustered standard errors, executing the identification design, and demonstrating robustness for large-sample capital-markets/contracting/disclosure data. Executes and reports the analysis; it does not design the study (jae-methods) or frame the contribution (jae-contribution-framing).

Use when running and reporting the empirical core of a Journal of the Association for Information Systems (JAIS) manuscript — SEM measurement and structural models for behavioral IS, identification and robustness for economics-of-IS, artifact evaluation for design science, or trustworthiness for qualitative work — and assembling the data/matrix materials JAIS requires. Executes and reports the analysis; it does not design the study (jais-methods) or frame the contribution (jais-contribution-f...

Use when selecting and completing the EQUATOR-network reporting checklist and flow diagram for a JAMA manuscript (CONSORT, STROBE, PRISMA, STARD, and design-specific guidelines). Maps design to checklist; it does NOT design the study or write the statistics.

Use when running estimation and inference for a Journal of Applied Econometrics (JAE) manuscript so the analysis is reproducible and archive-ready — every table/figure regeneratable from plain-text data and programs you will deposit in the JAE Data Archive. Covers robust inference, master-script discipline, Monte Carlo evidence, and the archive's plain-ASCII/CSV format rule.

Use when assembling the mandatory JAE Data Archive deposit for an accepted Journal of Applied Econometrics paper — plain-ASCII/CSV data with a readme, the programs that replicate every result, and the confidential-data exception. Encodes the archive's actual format rules (no bare .dta/SAS) and its history (Queen's 1994–2022, now ZBW).

Use when assembling the reproducible data-and-code supplement for a Journal of Business & Economic Statistics (JBES) paper under the American Statistical Association (ASA) data-sharing and reproducibility policy. Builds the supplement; it does not run the analysis itself.

Use when preparing the required data statement, code archive, repository deposit/link, and proprietary-data documentation for a Journal of Banking & Finance manuscript under Elsevier Option C research-data expectations.

Use when preparing the data-availability statement and code/data archive for a Journal of Corporate Finance (JCF) submission under Elsevier \"Research Data\" Option C — stating data availability at submission and depositing or explaining why data cannot be shared. It builds the data/code deliverables; it is not a substitute for vendor-license compliance.

Use when analyzing experimental data for a Journal of Consumer Psychology (JCP) manuscript — ANOVA/regression on the effect, measured and experimental mediation, moderation and moderated mediation, measurement of the process, and the rigor-era reporting standards. Analyzes the studies; it does not design them (jcp-methods).

Use when estimation, heterogeneity, attrition, measurement, or inference choices need to meet Journal of Development Economics (JDE) empirical norms — clustered field data, survey measurement error, and treatment-effect heterogeneity in low- and middle-income settings. Covers the analysis itself, not the identifying design.

Use when assembling the data and code deposit for a Journal of Development Economics (JDE) submission or accepted paper — JDE's mandatory replication policy, Mendeley Data hosting, and the fact that data/code can be requested at the review stage. Builds the package; it does not run the analysis.

Use when assembling the data, code, and experimental-materials deposit for a Journal of Economic Behavior & Organization (JEBO) manuscript — z-Tree/oTree code, instructions, raw and analysis data, and an Elsevier Research Data / Mendeley Data statement. Builds a reproducible package; it does not run the analysis.

Use when analyzing and reporting results for a Journal of Educational Psychology manuscript. JEP expects analyses that respect nesting (multilevel/SEM/growth models), report educationally meaningful effect sizes with confidence intervals, test mechanisms (mediation/moderation), and follow JARS with full disclosure. Guides analysis norms; it does not fabricate results.

Use when assembling the data and code replication package for a Journal of the European Economic Association (JEEA) manuscript so it clears the JEEA Data Editor's pre-acceptance verification under the DCAS standard. Builds the package and README; it does not run the analysis.

Use when assembling the data and code deposit for a Journal of Environmental Economics and Management (JEEM) manuscript — meeting JEEM's data-availability/replication expectation, documenting monitoring/satellite/admin/restricted environmental data, and writing a README that reproduces every exhibit. Builds the package; it does not run the analysis or invent data.

Use when preparing Journal of Economic Growth (JEG) data availability statements, replication code, calibration files, digitized historical sources, GIS layers, and Springer Nature research-data documentation for empirical, quantitative, or theoretical growth and comparative-development papers.

Use when assembling data, code, and spatial-data documentation for a Journal of Economic Geography (JEG) manuscript. Builds a credible, shareable package under JEG's encouragement-based post-acceptance policy; it does not invent data.

Use when handling the Journal of Economic Theory (JET) data/code expectations — JET is theorem-proof oriented, but Elsevier Option C applies when research data exist: deposit/cite/link data in a repository or explain why sharing is not possible. Focuses on reproducible computation when a paper has any, plus generative-AI disclosure. Light by design.

Use when preparing the research-data materials a Journal of Financial Intermediation (JFI) submission expects under Elsevier Option C — deposited, cited, and linked research data where possible; an explanation where sharing is impossible; a Data Statement; [dataset]-tagged references; and a credible access route for restricted supervisory or credit-register data. It prepares the package; it does not deposit for you.

Use when building the code and data archive required by the Journal of Financial and Quantitative Analysis (JFQA) Code Sharing Policy — source code reproducing all findings, raw or pseudo datasets, and a read-me with an execution roadmap, deposited in the JFQA Dataverse at the Harvard University Dataverse. Use to prepare the mandatory archive for accepted post-2024 submissions and to request any exception at initial submission.

Use when assembling the data, code, and access documentation for a Journal of Health Economics (JHE) manuscript — where much health data is restricted (claims, administrative, EHR) and the journal's policy encourages rather than mandates deposit. Packages reproducibility and a credible restricted-data access path; it does not run the analysis.

Use when building or auditing Journal of Human Resources (JHR) empirical pipelines — sample construction, design-based causal estimates with correct clustering, robustness, comparative estimation against prior published work, online appendix material, and reproducible analysis.

Use when preparing Journal of Human Resources data and replication materials: archive plan footnote, public repository deposit, CC0 license, Data Availability Statement, read-me file, waiver requests, RCT pre-analysis-plan statements, and code package.

Use when building or auditing the empirical analysis for a Journal of International Economics (JIE) manuscript — constructing bilateral trade panels, estimating PPML gravity, running open-economy panels and local projections, calibrating/estimating structural models, and producing the robustness suite international-economics referees expect. Strengthens the analysis; it does not fabricate results.

Use when preparing the replication package for a Journal of International Economics (JIE) manuscript — JIE requires that all materials needed to replicate published papers (computer programs and data sets) be deposited in the journal's secure repository (Mendeley Data). Builds the deposit; it does not run your analysis.

Use when assembling the data and code package for a The Journal of Law and Economics (JLE) manuscript to satisfy the journal's replication policy — data, programs, and computation details available for replication before publication. Builds the deposit and README; it does not run the analysis or write the paper.

Use when assembling the data and code replication package for a Journal of Law, Economics, and Organization (JLEO) manuscript — building reproducible paths from institutional/organizational/political data sources (court records, contracts, legislative data, firm-boundary data) to every exhibit. Builds the package; it does not run new analysis.

Use when building or stress-testing the empirical/quantitative analysis for a Journal of Monetary Economics (JME) manuscript — VAR/SVAR, local projections, DSGE estimation, moment matching, IRFs, and FEVDs — to monetary-economics and macroeconomics norms. Covers estimation choices, inference, and robustness.

Use when assembling the supplementary-materials / replication deposit for a Journal of Monetary Economics (JME) manuscript — depositing data, code (Dynare/MATLAB/Stata/R), and appendices on ScienceDirect / Mendeley Data per JME's supplemental-materials policy, plus the Elsevier generative-AI declaration.

Use when executing and reporting the analysis for a Journal of Marriage and Family (JMF) manuscript so it survives expert double-blind review — honest uncertainty, robustness, attention to selection and non-independence, and correct handling of complex-survey, longitudinal, and dyadic data. Guides analysis norms; it does not fabricate results.

Use when preparing the reproducibility / replication and data-sharing materials for a Journal of Marriage and Family (JMF) manuscript. JMF asks for replication-level detail and Wiley applies a data-sharing policy with a data availability statement; many family datasets are restricted-use. Covers quantitative and qualitative transparency and the restricted-data path. Prepares the package; it does not waive requirements.

Use when estimation and results are the bottleneck for a Journal of Management (JOM) manuscript — SEM/CFA, HLM/multilevel, regression and interactions, mediation/moderation, and meta-analytic estimation with artifact corrections. Runs and validates the analysis; it does not design the study (jmgmt-methods) or frame the contribution (jmgmt-contribution-framing).

Use when the estimation, identification, construct validity, or modeling is the bottleneck for a Journal of Management Information Systems (JMIS) manuscript — econometrics on firm/platform data, SEM/PLS for behavioral constructs, analytical-model derivations, or ML/analytics evaluation. Executes and stress-tests the analysis the design (jmis-methods) chose; it does not redesign the study.

Use when the execution and credibility of the analysis is the bottleneck for a Journal of Management Studies (JMS) manuscript — regression/SEM and robustness for quantitative work, OR coding, abduction, and trustworthiness for qualitative work. Runs and defends the analysis; it does not design the study (jms-methods) or build exhibits (jms-tables-figures).