
amkessler/nicar2026_skills_in_codex_claude
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Materials for NICAR 2026 session on using "skills" to aid in more reliable, reproducible analysis tasks when using Codex and Claude Code
概要
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. 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.
README
以下は原文 README の抜粋です。原文を見る。
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.md02_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:
推奨ツール
別のキーワードを試すか、フィルタを外してください。
インストール
npx skillfish add amkessler/nicar2026_skills_in_codex_claude