eda-report SKILL.md skillA
eda-report from qa-aman/claude-skills is an agent skill: a SKILL.md folder an AI agent loads when a task calls for it.
mdr add qa-aman/claude-skills/eda-report@git:20260303.8412b01Pins git:20260303.8412b01 in mdr.lock. Pin the fingerprint instead.
- Audit grade
- A, 17 of 17 checks passed
- Kind
- SKILL.md skill
- Repository
- qa-aman/claude-skills
- Path
skills/by-role/data-scientist/eda-report/SKILL.md- Versions recorded
- 1
- Latest version
- git:20260303.8412b01, committed Mar 3, 2026
- Size
- 5,820 bytes
- Repository stars
- 21
- License
- MIT
Run exploratory data analysis on a dataset and produce a structured report. Use when the user says "explore this dataset", "EDA on X", "analyze this data", "what's in this dataset", "summarize this data", "first look at the data", "understand this dataset before modeling", "data quality check", "describe this dataframe", or wants to understand a new dataset before building models or dashboards.
Collected from public GitHub. Every version is saved exactly as it was and never changes. Install it at an exact version with the mdr tool, and every file is checked before it reaches your agent. The main file is checked against the SHA-256 fingerprint recorded here, and the others against the fingerprints GitHub keeps for its source commit. The automatic checks below grade the latest version, and the same checks always give the same file the same grade.
What the file says
## Overview
Based on **"Practical Statistics for Data Scientists"** by Peter Bruce, Andrew Bruce, and Peter Gedeck. The core principle: before any modeling or analysis, you must understand the distribution, shape, and quality of your data. Skipping EDA leads to models trained on dirty data, misunderstood distributions, and insights that collapse under scrutiny. Structured EDA forces you to ask the right questions before committing to an approach.
## Workflow
### Step 1: Load and audit the dataset
Start with the basics - shape, types, and completeness.
```python
import pandas as pd
df = pd.read_csv("data.csv")
print(f"Shape: {df.shape}")
print(f"\nDtypes:\n{df.dtypes}")
print(f"\nMissing values:\n{df.isnull().sum()}")
print(f"\nDuplicate rows: {df.duplicated().sum()}")
```
Document:
- Row count and column count
- Percentage of missing values per column (flag any column > 5% missing)
- Columns with wrong inferred types (e.g., zip codes as integers)
- Duplicate row count
### Step 2: Profile each variable
Separate numeric from categorical. Apply the right summary stats to each.
**Numeric columns:**
```python
df.describe(percentiles=[0.01, 0.25, 0.5, 0.75, 0.99])
```
…Read the whole file at its exact version.
How to install
mdr add qa-aman/claude-skills/eda-report@sha256:1a0ba8a9dc646c14The line at the top of this page pins the label git:20260303.8412b01, which is what most people want. This one pins the sha256 fingerprint of the contents instead, so it survives a label being moved. Either way the exact version is written to mdr.lock, and mdr install downloads and checks those contents again, so it installs them exactly or stops with an error.
[](https://markdownregistry.com/a/art_knub2hit7k5rma3m)
1 badge image fetches in 30 days. What the badge shows.
Versions
The registry has recorded 1 version of this file, committed on Mar 3, 2026.
Audit of the latest version
- pass: Frontmatter block present
- pass: Frontmatter declares a name
- pass: Frontmatter declares a description
- pass: Size between 200 bytes and 200 KB (5820 bytes)
- pass: No zero-width or bidi control characters
- pass: No instruction hidden inside an HTML comment
- pass: No link to an exfiltration or paste host
- pass: No credential-shaped string
- pass: No instruction to send local credentials anywhere
- pass: No text hidden with inline styles
- pass: No prompt-injection phrasing
- pass: No curl or wget piped into a shell
- pass: No recursive delete of root, home or parent
- pass: No instruction to read or print local credentials
- pass: No base64 blob over 200 characters
- pass: No link to a raw IP address
- pass: No script tag
Source
qa-aman/claude-skills · 21 stars · license MIT · pushed 2026-10-19 · branch main
API
GET https://markdownregistry.com/api/v1/artifacts/art_knub2hit7k5rma3m GET https://markdownregistry.com/api/v1/resolve?ref=qa-aman/claude-skills/eda-report GET https://markdownregistry.com/api/v1/blob/1a0ba8a9dc646c146cad0ade242648c3233797b44a3397459fa3b1c4e9748064
Your AI assistant does the legwork. You hear about the deals worth your word. Hand yours the standing instructions at modelranch.com and it joins the network that reads files like this one.
Guides: the SKILL.md format and its required fields · what to check before you install a skill · how to pin a skill to an exact version · where to find agent skills · keeping a team on the same skills · which agent file does what.