이 프로젝트는 NICAR 2026 세션을 통해 AI "skills"를 사용하는 방법을 보여주는 모듈 식 자체 수집 된 명령 패키지는 도메인 별 작업에 대한 Claude / Codex의 기능을 확장합니다.

이 재포에는 6개의 기술이 포함되어 있습니다: fecfile] for Analyzing FEC Campaign Finance filings ( Matt Hodges), weather-forecast] for fetching 7일 예측, image-rotator for 자전 이미지, skill-creator for building new skills, state-county-rankings for grade Countyed demographics from local CSVs, and majority-minority-change Census snapshots. 함께, 도메인 별 데이터 분석에서 기술 시스템에 대한 메타 툴링에 대한 간단한 유틸리티를 수행 할 수있는 능력의 범위를 설명합니다.

Attendee 퀵스타트

Copy/paste 명령을 가진 단계별 튜토리얼을 보려면 다음을 참조하십시오.

• [T6]]
• 02_skills_learning_notes.md (제목, 운동, 문제 해결)
• 03_fecfile_examples.md (일제 FEC 서류)
• 04_build_a_skill_from_your_code.md ( 기존 R/Python 스크립트에서 기술 구축)
• `05 skill build example state county rankings.

NICAR 2026 Session on using “Skills”

This project accompanies the NICAR 2026 session showing how to use AI “skills”, the modular, self-contained instruction packages that extend Claude/Codex’s capabilities for domain-specific tasks.

This repo includes six skills: fecfile for analyzing FEC campaign finance filings (from Matt Hodges), weather-forecast for fetching 7-day forecasts, image-rotator for rotating images, skill-creator for building new skills, state-county-rankings for ranked county demographics from local CSVs, and majority-minority-change for threshold-crossing analysis between Census snapshots. Together they demonstrate the range of what skills can do, from domain-specific data analysis to simple utilities to meta-tooling for the skill system itself.

Attendee Quickstart

For a step-by-step tutorial with copy/paste commands, see:

• 01_quickstart_underlying_code.md
• 02_skills_learning_notes.md (session notes, exercises, and troubleshooting)
• 03_fecfile_examples.md (worked FEC filing examples)
• 04_build_a_skill_from_your_code.md (build a skill from existing R/Python scripts)
• 05_skill_build_example_state_county_rankings.md (rank counties within a state from local demographics CSVs)
• 06_skill_build_example_majority_minority_change.md (analyze threshold crossings between two Census snapshots)

What is a skill?

When you ask an AI assistant to help with data analysis, it has to figure out on the fly how to approach the problem: which fields exist, how to handle edge cases, what the right tool or library is. Without guidance, it may guess at field names, rewrite the same boilerplate code every session, or make different choices each time. A colleague asking the same question might get a different approach, different column names, different aggregation logic.

A skill solves this by giving Claude or Codex a standing set of instructions before the conversation begins, a documented, version-controlled playbook that the AI follows every time. A skill is just a folder containing a SKILL.md file (plain Markdown with a short YAML header) plus any helper scripts or reference documents the AI should use. You write it once, commit it to your repo, and every session (and every collaborator) gets the same behavior.

How skills get invoked

Skills can trigger in two ways: