# dr-profile

> Claude/Codex skill by [@datarails](https://omgskills.com/library/datarails/index.md) · 3 stars · Updated 2026-09-22

Profile Datarails Finance OS table fields — how is a field distributed? Per-field statistics over the table's whole history — ranges, approximate percentiles, null rates, cardinality interpretation, and range-outlier flags — no severity ranking, no period scope. The MCP tools return baseline aggregates (SUM/AVG/MIN/MAX/COUNT for numeric, distinct-value samples for categorical); this skill derives the statistics client-side. For severity-ranked data-quality findings scoped to the latest fiscal year, use the anomalies skill.

## Install

```sh
git clone https://github.com/Datarails/dr-claude-code-plugins-re /tmp/dr-claude-code-plugins-re && ln -s /tmp/dr-claude-code-plugins-re/skills/profile ~/.claude/skills/dr-profile
```

## From README

Datarails Table Profiling Field-level statistics for Finance OS tables. The MCP profile tools are thin — they return only the basic aggregates listed below. Everything richer (percentiles, std dev, outlier flags, null rates, cardinality interpretation) is computed by this skill, not the tool. State the provenance of every number you present.

## Links

- HTML page: https://omgskills.com/library/datarails/dr-claude-code-plugins-re/skills/profile/
- GitHub: https://github.com/Datarails/dr-claude-code-plugins-re
- Author: [@datarails](https://omgskills.com/library/datarails/index.md)

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