Borrowing it
Nothing to install: this file belongs to amkessler/nicar2026_skills_in_codex_claude. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/amkessler/nicar2026_skills_in_codex_claude/main/CLAUDE.mdgit clone --depth 1 https://github.com/amkessler/nicar2026_skills_in_codex_claudeWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/instructions/amkessler/nicar2026_skills_in_codex_claude/claude-md)<a href="https://agentmods.dev/instructions/amkessler/nicar2026_skills_in_codex_claude/claude-md"><img src="https://agentmods.dev/badge/instructions/amkessler/nicar2026_skills_in_codex_claude/claude-md/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/instructions/amkessler/nicar2026_skills_in_codex_claude/claude-md"><img src="https://agentmods.dev/badge/instructions/amkessler/nicar2026_skills_in_codex_claude/claude-md.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.01959 | $0.01959 |
| Opus 5 | $0.00979 | $0.00979 |
| Sonnet 5 | $0.00392 | $0.00392 |
| Haiku 4.5 | $0.00196 | $0.00196 |
Grade A, and why
nicar2026_skills_in_codex_claude CLAUDE.md scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 12d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 196 lines — stays where its author put it; the contents beside it link to each section on GitHub.
CLAUDE.md
This file provides guidance to Claude Code (claude.ai/code) when working with code in this repository.
Project Overview
Demo project for NICAR 2026 showing how to use AI "skills" — modular, self-contained instruction packages
that extend Claude/Codex's capabilities for domain-specific tasks. The repo includes six skills covering
FEC campaign finance, weather forecasts, image rotation, county-level demographic analysis, and skill creation.
The skills/ directory is the canonical session copy; numbered tutorial docs (01_*.md - 06_*.md)
walk through quickstart workflows, skill-building exercises, and worked Census examples.
Environment Setup
This project uses uv for Python dependency management (Python 3.12+ required):
uv sync # Install dependencies into .venv
uv run <script> # Run a script with dependencies auto-resolved
JupyterLab is the primary analysis environment:
uv run jupyter lab # Launch JupyterLab
Quarto renders notebooks/documents to data/html_reports/:
quarto render # Render all Quarto docs
quarto render <file.qmd> # Render a single file
The .env file sets JUPYTER_PATH, JUPYTER_CONFIG_DIR, and JUPYTER_RUNTIME_DIR to keep
Jupyter isolated inside .venv. This file is gitignored — do not commit it.
Skills Architecture
Skills are directories containing a SKILL.md (with YAML frontmatter) and optional bundled
resources (scripts/, references/, assets/). This repo has three skill locations:
skills/— session copy used in the NICAR conference session (canonical source).claude/skills/— active skills for Claude Code (auto-loaded when you open the project).agents/skills/— active repo-local skills for the Codex CLI
Six skills are present in all three locations:
fecfile— FEC campaign finance filing analysis (Python)weather-forecast— 7-day forecasts via Open-Meteo (Python)image-rotator— rotate images 90° (Python)skill-creator— guided workflow for building new skills (Python)state-county-rankings— ranked county metrics within a state (R, bundled CSV, no API key)majority-minority-change— county racial composition change between two Census snapshots (R, bundled CSVs, no API key)
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 12d ago First seen · 196 lines · 1,959 tokens per session scan A 75a497c43a91
nicar2026_skills_in_codex_claude CLAUDE.md is an instructions file published in the GitHub repository amkessler/nicar2026_skills_in_codex_claude (20 stars, last pushed 1mo ago), licensed Apache-2.0. It adds 1,959 tokens to every session, about $0.0098 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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