Browse Skills

Marginaleffects helps users interpret statistical models in R and Python via predictions, comparisons, slopes, and hypothesis tests, following the book Model to Meaning. Use it for marginal effects, treatment effects, causal inference, or function syntax.

PyFixest Reference provides a machine-readable API reference for the PyFixest Python package, covering feols, fepois, feglm, quantreg, clustered/robust standard errors, R-style formulas, and post-estimation. Use when writing or debugging fixed-effects regressions in Python.

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.

SSCI Polish polishes English academic papers for SSCI journal submission, checking grammar, improving readability, and enhancing academic tone. Use it when asked to polish, proofread, edit, or improve an academic manuscript targeting SSCI, SCI, or other international journals.

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.

Stop Slop removes predictable AI writing patterns from prose. Use it when drafting, editing, or reviewing text to eliminate filler phrases, formulaic structures, passive voice, and vague language.

Systematic Literature Review guides users through writing a systematic literature review following the PRISMA 2020 framework, producing a journal-format Word document, an annotated PRISMA flow diagram, and APA 7th edition references. Use it when drafting or auditing an SLR.

Ask delegates work to or requests information from another CCB-managed agent. Use it when the user asks to delegate, hand off, consult, or send work to a named CCB agent.

Ask CCB sends a request to a CCB agent using the `ask` command. Use it when delegation to another coding agent is requested or project memory instructs CCB collaboration.

Ask CCB sends a request to a CCB agent so Claude Code can delegate work and collaborate. Use it when the user asks to delegate with CCB or project memory says to use CCB ask for collaboration.