Data-team toolkit for building, interacting with, and improving data projects with coding agents
Project description
dt-ai-toolkit
A data-team toolkit for building, interacting with, and improving data projects with coding agents. One install (uv) gets a teammate a Claude-ready project, curated Agent Skills, runnable agent flows, and a PDF report pipeline.
# no install needed — run it straight from PyPI
uvx dt-ai-toolkit --help
Quickstart
mkdir my-project && cd my-project
uvx dt-ai-toolkit setup # folders + gitignore + installs Claude Code & omnigent
uvx dt-ai-toolkit doctor # verify the environment
uvx dt-ai-toolkit docs # interactive docs browser
Commands
| command | what it does |
|---|---|
setup |
Scaffold a data project (data/, reports/, sandbox/, managed .gitignore block) and install tooling. Customizable via a dt-setup.toml profile (setup config init). |
skills |
Install Agent Skills into .claude/skills/ from the bundled set, a local folder, or a git repo. list / install / update with provenance tracking. |
agent |
Run agent flows via the Claude Agent SDK: bundled sourcing-report and project-review, or your own frontmatter-markdown agent files. |
report |
Scaffold the React TSX → HTML/PDF report pipeline (report new <name>). |
doctor |
Check the environment: uv, git, claude CLI, omnigent, auth, bun, playwright. |
docs |
Browse documentation — a Textual TUI, or --plain / show <topic> / export for non-interactive use. |
Bundled skills
- interrogate-data — structured protocol for profiling and stress-testing a dataset before trusting it
- critique-talking-points — adversarial claim-by-claim review of narratives before they ship
- critique-visualization — chart-honesty review, including re-deriving plotted values from source data
- tsx-report-generator — walks Claude through the full TSX → HTML/PDF report pipeline
- dt-setup-config — helps Claude build a custom
dt-setup.tomlfor your team - dt-ai-toolkit — meta skill teaching Claude how to call this CLI itself (
uvx dt-ai-toolkit ...) - grill-me — Socratic quiz rounds that test your understanding of a dataset, pipeline, or report before someone else does
uvx dt-ai-toolkit skills list --available
uvx dt-ai-toolkit skills install interrogate-data
uvx dt-ai-toolkit skills install https://github.com/your-org/team-skills.git --all
Custom agent flows
Agents are markdown files with YAML frontmatter — config on top, prompt below,
{placeholders} filled from the command line:
---
name: data-audit
description: Audit a dataset for quality issues
allowed_tools: [Read, Glob, Grep, Bash]
args:
data_path: {required: true}
---
Audit the dataset at {data_path}. Cite the query behind every finding.
dt-ai-toolkit agent run data-audit.md --arg data_path=data/sales.csv
dt-ai-toolkit agent run sourcing-report --arg topic="Q3 readmissions" --dry-run
Development
uv sync
uv run pytest
uv run dt-ai-toolkit --help
See CLAUDE.md for architecture conventions.
Project details
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