SepineTam

Fix Python implementation issues identified by verify-command. Reads the verification report, analyzes discrepancies, applies fixes, and re-runs verification. Use when a verify-command report shows mismatches, or user says "fix report for XXX" or "patch XXX based on report".

Black-box usability testing from a user's perspective. Use when you want to test a module/function by writing code as a real user would — no peeking at source code, signatures, or docs. The tester only knows the basic import path and writes code purely from intuition and naming hints.

Learn and document a Stata command for Python econometric implementation reference. Use when user says "learn stata command XXX" or wants to understand a Stata command's internals for replicating in Python. Workflow: fetch help via Stata-MCP, write demo do-file, run it, and produce a command breakdown doc.

Cross-validate a Stata command against its Python implementation by running identical parameter combinations in both environments and comparing results. Use when user says "verify command XXX" or "validate XXX" or wants to check that Python output matches Stata output for a specific command.

Run a local smoke test for the Stata-MCP server.

A packaged Stata Runner skill via official MCP-for-Stata server including stata_do, ado_package_install, help, read_log and get_data_info tools. Use it when (1) need to execute Stata do-file; (2) missing ado-packages; (3) find code error caused by syntax in Stata; (4) want to read smcl and text format log file with rich text output; (5) first encounter a data file and want to understand its structure and content.

Generate RFC and IMPL documents from a user-provided feature/fix description. Use when the user says something like "I want to add a feature with codex", "Implement this", "Write an RFC for...", or provides a short idea that needs to be formalized into the ai-driven/rfc + ai-driven/impl pipeline.

Use this skill when the user needs to search NBER working papers, inspect NBER paper metadata, download NBER paper PDFs, run NBER-CLI commands, or configure NBER-CLI as an MCP server.

Analyze writing style from user-provided example documents (PDF, DOCX, TXT, MD) and generate personalized writing rules. Use when the user wants to: (1) Learn or extract writing style from example papers/articles, (2) Create personalized writing rules for Claude to follow, (3) Build a writing-style preference profile from sample documents, (4) Apply a specific academic/professional writing style consistently. Triggers on keywords: "writing style", "learn style", "style analysis", "preference file", "writing rules", "write like", "模仿风格".