Tools for coding, teaching, and presentations with AI assistance.
This is a collection of tools, templates, and philosophies I've developed while using Claude Code for:
- Coding (data analysis scripts, replication code, automation)
- Teaching (course materials, lecture decks, pedagogical tools)
- Presentations (Beamer decks, slides for talks and seminars)
As I develop new approaches, I'll add them here. Anyone is free to use them.
Take everything with a grain of salt. These are workflows that work for me. Your mileage may vary.
Scott Cunningham — Professor of Economics at Baylor University
- Website: www.scunning.com
- Substack: causalinf.substack.com — I write regularly about causal inference, Claude Code, and random things
- Free book: Causal Inference: The Mixtape — available online
Location: workflow.md | Deck: presentations/examples/workflow_deck/
Before diving into specific tools, read my workflow document. It explains how I think about using Claude Code for empirical research—not just the tools, but the philosophy behind them.
Key concepts:
| Concept | What It Means |
|---|---|
| Thinking partner, not code monkey | Claude is a collaborator who reasons about problems, not just a code generator |
| External memory via markdown | Claude has amnesia between sessions; markdown files provide institutional memory |
| Cross-software replication | R = Stata = Python to 6 decimal places, or something is wrong |
| Adversarial review (Referee 2) | Fresh Claude instance audits your work; you can't grade your own homework |
| Verification through visualization | Trust pictures over numbers; errors become visible |
| Documentation as first-class output | If it's not documented, it didn't happen |
Everything else in this repo implements these principles.
Location: personas/referee2.md
The single most valuable practice I've developed. Referee 2 is a health inspector for empirical research—not a vague "be critical" persona, but a systematic audit protocol with five specific audits, cross-language replication, formal referee reports, and a revise & resubmit process.
The Five Audits:
| Audit | What It Does |
|---|---|
| Code Audit | Scrutinizes for coding errors, missing value handling, merge diagnostics, variable construction |
| Cross-Language Replication | Creates replication scripts in 2 other languages (R/Stata/Python), compares results to 6 decimal places |
| Directory Audit | Checks folder structure, relative paths, naming conventions—is this replication-package ready? |
| Output Automation Audit | Are tables and figures programmatically generated or manually created? |
| Econometrics Audit | Are specifications coherent? Standard errors correct? Identification plausible? |
Critical Rule: Referee 2 NEVER modifies author code. It only creates its own replication scripts. The author is the only one who modifies the author's code. This separation ensures the audit is truly independent.
Location: presentations/
My philosophy of slide design, plus a tested prompt for generating Beamer presentations. The key insight: aim for MB/MC equivalence across slides (smoothness), not maximum density.
Core principles:
- Beauty earns attention; attention enables communication
- Titles are assertions, not labels
- One idea per slide
- Bullets are defeat—find the structure hiding in your list
Location: claude/CLAUDE.md
A template for giving Claude persistent memory within a project. Copy it to your project root and fill in the specifics. Claude Code will automatically read it every session.
MixtapeTools/
├── README.md # You are here
├── workflow.md # How I use Claude Code for research (START HERE)
├── claude/ # Templates for working with Claude
│ ├── CLAUDE.md # Project context template (copy to your projects)
│ └── README.md
├── personas/ # Systematic audit & replication protocols
│ ├── referee2.md # The 5-audit protocol for empirical research
│ └── README.md
└── presentations/ # Everything about slide decks
├── rhetoric_of_decks.md # Practical principles (condensed)
├── rhetoric_of_decks_full_essay.md # Full intellectual framework (600+ lines)
├── deck_generation_prompt.md # The prompt + iterative workflow
├── README.md
└── examples/
├── workflow_deck/ # Visual presentation of the workflow
├── rhetoric_of_decks/ # The philosophy deck (45 slides)
└── gov2001_probability/ # A lecture deck
During estimation and analysis, focus entirely on whether the specification is correct. Results are meaningless until the "experiment" is designed on purpose. Don't get excited or worried about point estimates until the design is intentional.
AI makes confident mistakes. Cross-software replication (R = Stata = Python) catches bugs that single-language analysis misses. If results aren't identical to 6+ decimal places across implementations, something is wrong.
If you ask the same Claude that wrote code to review it, you're asking a student to grade their own exam. True adversarial review requires a new terminal with fresh context and no prior commitments.
The audit must be independent. Referee 2 creates its own replication scripts but never touches the author's code. Only the author modifies the author's code. This separation ensures the audit is truly external.
Checklists beat intuition. The Referee 2 protocol works because it specifies exactly what to check, requires concrete deliverables (replication scripts, comparison tables, referee reports), and creates a paper trail.
If it's not documented, it didn't happen. Every audit produces a dated referee report filed in correspondence/. Every response is documented. Replication scripts are permanent artifacts. Future you (or your collaborators) can reconstruct exactly what happened.
Start with workflow.md to understand the philosophy.
Copy claude/CLAUDE.md to your project root. Fill in your project specifics.
Work with Claude as a thinking partner, not a code generator. Ask it to explain its understanding. Verify outputs visually. Document as you go.
When you have results worth checking:
- Open a new terminal (fresh context is essential)
- Paste the contents of
personas/referee2.md - Say: "Please audit and replicate the project at [path]. Primary language is [R/Stata/Python]."
- Respond to the referee report (fix or justify each concern)
- Iterate until verdict is Accept
For the Referee 2 workflow to function properly, your research projects should include:
your_project/
├── CLAUDE.md # Project context for Claude
├── correspondence/
│ └── referee2/
│ ├── 2026-02-01_round1_report.md # Detailed written report
│ ├── 2026-02-01_round1_deck.pdf # Visual presentation of findings
│ ├── 2026-02-02_round1_response.md # Author response
│ └── ...
├── code/
│ ├── R/ # Author's code (ONLY author modifies)
│ ├── stata/
│ ├── python/
│ └── replication/ # Referee 2's replication scripts
├── data/
│ ├── raw/
│ └── clean/
└── output/
├── tables/
└── figures/
Have improvements or additions? PRs welcome. I'm particularly interested in:
- Additional audit protocols (security reviewer, pedagogy reviewer, etc.)
- Examples showing the Referee 2 workflow catching real bugs
- Tools for other aspects of coding and teaching
Inspired by Boris Cherny's ChernyCode template for AI coding best practices.
Use freely. Attribution appreciated but not required.
Last updated: February 2026