Data

Python Economic Computing provides best practices for macroeconomic modeling (DSGE/HANK), causal inference, and quantitative data analysis in Python. Use it when writing Python code for DSGE models, HANK models, numerical economic computation, causal inference, or quantitative economic data analysis.

Stata Accounting Research provides tested STATA code patterns from 126 peer-reviewed Journal of Accounting Research replication files (2017–2025) for empirical archival accounting methods such as entropy balancing, PSM, DiD, RDD, IV, event studies, and Fama-MacBeth regressions. Use it when a user asks procedural questions like 'How do I implement [method]?' or 'Show me code for [technique]'.

Stata Empirical Analysis provides a complete 8-step pipeline for econometric and causal inference in Stata, covering data cleaning, variable construction, diagnostics, estimation (DID, IV, RD, matching), robustness checks, and publication-ready tables and figures. Use it when you need reproducible .do-file workflows for academic empirical papers.

StatsPAI runs full empirical and causal analysis pipelines in Python, including AER-style DID/RD/IV/SCM/DML tables, epidemiological target-trial emulation, ML causal inference, and decomposition methods. Use it when the user asks for applied micro, public health, or causal ML results with paper-ready Word/Excel/LaTeX outputs.

Amazon Ads Planning plans and reviews Amazon Ads with margin-aware ACoS, product, and search-term guardrails. Use for Amazon advertising, Sponsored Products, Sponsored Brands, Sponsored Display, ASIN targeting, Amazon ACoS, or Amazon Ads performance exports.

Google Ads Audit diagnoses Google Ads account health, computes waste, demand captured, and CPA pulse metrics, and persists business context for downstream ad skills. Use it when onboarding a new account, responding to 'audit my ads', or when other ads skills detect missing business-context.json.

Google Analytics analyzes connected Google Analytics 4 traffic, acquisition, engagement, landing pages, ecommerce, events, and conversions through NotFair MCP. Use it to diagnose traffic or conversion drops, channel attribution, realtime activity, report requests, and measurement configuration.

Meta Ads provides frameworks for analyzing and optimizing Meta Ads (Facebook and Instagram) performance, including ROAS, CPM, frequency, audience overlap, learning phase, and creative fatigue. Use it when you need to audit campaigns, spot waste, or make budget, pause, enable, or rename changes through the Meta MCP server.

Meta Ads Audit diagnoses the health of a Meta (Facebook and Instagram) ad account, pulls campaign/ad set/ad performance data, and persists business context for downstream Meta ads skills. Use it before running fixes or when onboarding a new Meta account.

Paid Ads Review produces a read-only, evidence-based paid-media performance review across connected platforms or supplied exports. Use it for weekly or monthly reports, scorecards, CPA, ROAS, CTR, spend trends, pacing, or conversion-tracking health.

Agent Analytics adds analytics tracking, A/B experiments, funnels, and retention analysis to projects via CLI. Use it when an AI agent needs to track traffic, conversions, and growth without dashboard-only workflows.

Work Status reads WORK-LIST.md and PROGRESS.md files to report current WORK and TASK progress. Use it when the user asks about work lists, task status, or pipeline status.