DAAF

Summary: What is DAAF?

LLM-based AI assistants are becoming increasingly capable, but they are always at risk of hallucination, sycophancy, over-confidence, and laziness. So can these flawed and non-deterministic tools ever be useful for conducting rigorous data analysis?

Yes -- but only with the right guidance, right guardrails, and in expert hands to direct all core decisions and verify all key outputs.

Enter DAAF, the Data Analyst Augmentation Framework. DAAF is a free and open-source instructions framework for Claude Code that helps skilled researchers deepen and extend their expertise across any domain of data analysis with AI assistance -- while enhancing the transparency, rigor, and reproducibility that good science demands. DAAF sits between you and Claude Code to automatically and consistently help Claude think more like a responsible and rigorous researcher by:

• Enforcing strict auditability and reproducibility standards for all work, thus allowing you to verify everything Claude does on your behalf
• Preventing potentially dangerous unintended file access and editing, by sandboxing Claude with strict protections and logging traces
• Setting high standards of care, rigor, and thoroughness in all data analysis, by forcing Claude to comment, verify, and review all analytic code before you ever see it
• Embedding best practices for a wide variety of research methodologies like causal inference and geospatial analysis, by providing rich Skills (reference manuals Claude loads on demand when a task calls for them) that extend Claude's base capabilities with real research and resources
• Collaborating with you, the human expert, directly on all key decisions, thus keeping you firmly in the driver's seat

Think of it as a force-multiplying exoskeleton for human researchers -- a tool explicitly designed to augment your hard-earned expertise, not replace it. The goal is to make it easy for researchers to use Claude Code effectively and responsibly. Importantly, DAAF is not and will never be perfect -- but it is already immensely useful, and this is the worst a tool like DAAF will ever be from now on with the help and support of the broader research community.

Install and begin using it in as little as 10 minutes from a fresh install with an Anthropic account, an OpenRouter API key, or an OpenAI account.

New to DAAF? Start with the Getting Started video below -- a full tutorial that walks you through the entire installation and gets you oriented to the whole environment, from the Docker setup and Claude Code to DAAF itself. Or read on for more information!

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Quick Start

If you're already comfortable with the Terminal and Claude Code, you can get started almost immediately using the Quick Start instructions below. Otherwise, I recommend starting with the full Installation Guide for beginner-friendly details, prerequisites, and troubleshooting.

Requirements: Docker Desktop (running) and an account with one of the supported AI providers:

• Anthropic subscription (Max at $100/mo or Ultra at $200/mo recommended; verified against Anthropic's pricing page on 2026-11-01) — flat-rate, best value for heavy use.
• Anthropic API key — pay-per-use; no subscription, but a full analysis can run $50+.
• OpenRouter — pay-per-token, no subscription; provides access to Anthropic models plus high-performing open-weight alternatives like GLM 5.2; a supported route that benefits from wider community testing.
• OpenAI API key or ChatGPT subscription — run DAAF on GPT models through DAAF's provider shim, a small translator built into DAAF (you turn it on in environment_settings.txt and restart the container); supported routes that benefit from wider community testing (see Option F in the Installation Guide).
• AWS Bedrock or Google Vertex AI — route through your organization's cloud platform; DAAF ships configuration templates, but these routes aren't maintainer-validated end-to-end (see Using DAAF with Sensitive or Regulated Data).

Open a terminal in your desired installation directory.

macOS / Linux (Terminal):

# Install DAAF (downloads Docker build files, builds image, clones repo into container)
curl -fsSL https://raw.githubusercontent.com/DAAF-Contribution-Community/daaf/main/scripts/host/install.sh | bash

# Enter the installation folder and open the DAAF Control Panel
cd daaf-docker
bash daaf.sh

Windows (PowerShell):

# Install DAAF (downloads Docker build files, builds image, clones repo into container)
irm https://raw.githubusercontent.com/DAAF-Contribution-Community/daaf/main/scripts/host/install.ps1 | iex

# Enter the installation folder and open the DAAF Control Panel
cd daaf-docker
.\daaf.ps1

This is the beginning of the README. Read the rest at the original. Read the full README ↗