Agent skill · Databases

data-analysis

Analyze Excel/CSV files with DuckDB SQL via bash.

HezaoHezaogithub.com/HezaoHezaoGitHub ↗
claude-codecan modify filesMIT
Install
npx skills add HezaoHezao/poirot --skill data-analysis --agent claude-code

Same command for any agent — swap --agent for codex, cursor, copilot.

Facts
Files in the skill folder: 1
SKILL.md size: 4 KB
Bundled scripts: none
Declared author: Adapted from deer-flow (Bytedance, MIT)
Allowed tools: -bash-read_file-write_file
Path: poirot/backend/agents/skill/builtin_skills/research/data-analysis/SKILL.md
Open the folder on GitHub →
Where it comes from
Stars: 139
Language: Python

Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.

From the SKILL.md

# Data Analysis ## Overview Analyzes user-provided Excel (.xlsx/.xls) or CSV files using DuckDB — an in-process analytical SQL engine. Supports schema inspection, SQL querying, statistical summaries, and result export. > **Poirot note:** The original deer-flow skill uses a bundled > `scripts/analyze.py` helper. Poirot doesn't bundle that script, so this > version uses `bash` with `python3` + `duckdb` directly. Install duckdb first: > `pip install duckdb`. ## When to Use - User uploads Excel/CSV files and wants analysis - User wants statistics, summaries, pivot tables, or SQL queries on data - User wants to filter, join, or aggregate structured data ## Prerequisites ```bash # Install duckdb if not present pip install duckdb openpyxl ``` ## Workflow ### Step 1: Inspect File Structure ```bash python3 -c " import duckdb con = duckdb.connect() # For CSV result = con.execute(\"DESCRIBE SELECT * FROM read_csv_auto('data.csv')\").fetchall() for col in result: print(f'{col[0]:30s} {col[1]}') # For Excel (each sheet = a table) result = con.execute(\"SELECT * FROM st_read('data.xlsx', layer='Sheet1') LIMIT 0\").fetchall() # Row count count = con.execute(\"SELECT COUNT(*) FROM read_csv_auto('d

What's inside
Steps it walks through
  1. Overview
  2. When to Use
  3. Prerequisites
  4. Workflow
  5. Step 1: Inspect File Structure
  6. Step 2: Statistical Summary
  7. Step 3: SQL Queries
  8. Step 4: Export Results
  9. Common Patterns
  10. Pivot table
  11. Percentiles
  12. Multi-sheet Excel
  13. Pitfalls
Commands it runs
Install duckdb if not present
pip install duckdb openpyxl
python3 -c "
import duckdb
con = duckdb.connect()
For CSV
result = con.execute(\"DESCRIBE SELECT * FROM read_csv_auto('data.csv')\").fetchall()
for col in result:
For Excel (each sheet = a table)
result = con.execute(\"SELECT * FROM st_read('data.xlsx', layer='Sheet1') LIMIT 0\").fetchall()
More from poirot
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About this skill
What does the data-analysis skill do?

Analyze Excel/CSV files with DuckDB SQL via bash.

How do I install it?

Run `npx skills add HezaoHezao/poirot --skill data-analysis --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.

Where does this skill come from?

From HezaoHezao/poirot, a repository with 139 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.

Is a popular skill a good skill?

Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.

Keep going