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Agent skill

Data Exploration Tool

by Dbxstudio in Dbxstudio/dbx-studio

Systematic database and table profiling for DBX Studio. An agent skill from Dbxstudio/dbx-studio.

Apache-2.0Auto-check passedData & Analytics

Install Data Exploration Tool

skills CLI
$ npx skills add Dbxstudio/dbx-studio --skill data-exploration-tool -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install Dbxstudio/dbx-studio data-exploration-tool --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/Dbxstudio/dbx-studio.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/data-exploration .claude/skills/data-exploration-tool && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
data-exploration-tool
GitHub stars
103
Used in
1 other repo
Token cost
~460 tokens
SKILL.md length
133 words
Files
1
Skills in repo
5
Repo updated
First seen
Licence
Apache-2.0

At a glance

Systematic database and table profiling for DBX Studio. An agent skill from Dbxstudio/dbx-studio.

  • Works in 3 steps: Schema Discovery → Table Profiling → Relationship Discovery
  • A user wants to understand their data
  • SKILL.md covers Exploration Workflow, Quality Scoring, Common Exploration Queries and Output Format
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Data Exploration Tool is an agent skill from Dbxstudio/dbx-studio. Systematic database and table profiling for DBX Studio. Use when a user wants to understand their data, explore schema structure, or profile a dataset.

Its SKILL.md is about 460 tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in Data & Analytics, covering Data analysis. The repository describes itself as: Free Open-source AI SQL client that helps developers and data teams explore databases using natural language. The licence is Apache-2.0.

When your agent uses it

  • A user wants to understand their data
  • Explore schema structure
  • Profile a dataset

Example prompts

  • “/data-exploration-tool”

Workflow steps

3 steps, taken from the step headings in SKILL.md.

  1. Schema Discovery
  2. Table Profiling
  3. Relationship Discovery

What it can do on your machine

Read from SKILL.md and the folder at commit 9592eb7. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md (its code samples are sql).

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Data Exploration Tool loads about 460 tokens when it runs. Until then it costs about 43 tokens; SKILL.md has 133 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~43
When it runs · the whole SKILL.md, loaded when a task matches
~460

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from Dbxstudio/dbx-studio at commit 9592eb7, republished under its Apache-2.0 licence (© Dbxstudio). 133 words, ~460 tokens.

Download SKILL.mdSave it as .claude/skills/data-exploration-tool/SKILL.md (or your agent's skills folder).
name
data-exploration-tool
description
Systematic database and table profiling for DBX Studio. Use when a user wants to understand their data, explore schema structure, or profile a dataset.

Data Exploration — DBX Studio

Exploration Workflow

Phase 1: Schema Discovery

Start with read_schema to list all tables, then describe_table for each table of interest.

1. read_schema(schema_name: "public")
2. describe_table(table_name: "<each table>")
3. get_table_stats(table_name: "<table>")
Phase 2: Table Profiling

For each table, gather:

  • Row count
  • Column names and types
  • Sample data via get_table_data
  • Null counts and distributions
Phase 3: Relationship Discovery

Look for foreign key patterns:

  • Columns named *_id linking to other tables
  • Common join patterns: users.id → orders.user_id

Quality Scoring

ScoreCompleteness
Green> 95% populated
Yellow80–95% populated
Orange50–80% populated
Red< 50% populated

Common Exploration Queries

Row count
sql
SELECT COUNT(*) AS row_count FROM "public"."table_name";
Column null rates
sql
SELECT
  COUNT(*) AS total,
  COUNT(column_name) AS non_null,
  ROUND(100.0 * COUNT(column_name) / COUNT(*), 2) AS pct_filled
FROM "public"."table_name";
Distinct values
sql
SELECT column_name, COUNT(*) AS frequency
FROM "public"."table_name"
GROUP BY 1
ORDER BY 2 DESC
LIMIT 20;
Date range
sql
SELECT MIN(created_at), MAX(created_at) FROM "public"."table_name";

Output Format

After exploration, present a structured summary:

  • Tables: list with row counts
  • Key relationships: how tables connect
  • Data quality flags: any columns with high null rates
  • Suggested next queries: what the user might want to know next

© Dbxstudio, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in skills/data-exploration of Dbxstudio/dbx-studio.

Open the folder on GitHubat commit 9592eb7

Used in 1 other repository

We found 3 copies of this SKILL.md (exact, near-identical or edited) in other folders, from 1 other GitHub owner. This page covers the copy in Dbxstudio/dbx-studio, which our catalogue first saw on October 7, 2026.

Compare with similar skills

Data Exploration Tool next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Data Exploration Tool compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Data Exploration Tool this skillDbxstudio/dbx-studio1031 repos~460Automated safety check: PassApache-2.0
Exploratory Data Analysisspacering-net/codeg3.8k15 repos~3.6kAutomated safety check: PassMIT
Excel and CSV Data Analysisbytedance/deer-flow83k4 repos~2.2kAutomated safety check: PassMIT
Exploratory Data AnalysisOleafly/Oleafly2052 repos~3.4kAutomated safety check: NotesMIT
Python Executorcortega26/chile-hub1132 repos~1.5kAutomated safety check: PassMIT
Agentic Kaggle WorkflowFrankS-IntelLab/agentic-kaggle-skill188—~4kAutomated safety check: PassMIT

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Categories

Questions about Data Exploration Tool

What does Data Exploration Tool do?

Systematic database and table profiling for DBX Studio. An agent skill from Dbxstudio/dbx-studio. Data Exploration Tool is an agent skill from Dbxstudio/dbx-studio. Systematic database and table profiling for DBX Studio.

When should I use Data Exploration Tool?

Data Exploration Tool fits situations like: A user wants to understand their data; explore schema structure; profile a dataset.

How do I install Data Exploration Tool in Claude Code?

Run `npx skills add Dbxstudio/dbx-studio --skill data-exploration-tool -a claude-code`. Or copy the skill folder (skills/data-exploration in Dbxstudio/dbx-studio) into .claude/skills/data-exploration-tool in your project. Claude Code loads it when a task matches its description.

How do I install Data Exploration Tool in Codex?

Run `npx skills add Dbxstudio/dbx-studio --skill data-exploration-tool -a codex`. Or copy the skill folder (skills/data-exploration in Dbxstudio/dbx-studio) into .agents/skills/data-exploration-tool in your project. Codex loads it when a task matches its description.

Can I use Data Exploration Tool in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add Dbxstudio/dbx-studio --skill data-exploration-tool -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/data-exploration-tool, .gemini/skills/data-exploration-tool, .github/skills/data-exploration-tool and .opencode/skills/data-exploration-tool in your project.

What does Data Exploration Tool need to run?

SKILL.md names no scripts, command-line tools or credentials: Data Exploration Tool is instructions for the agent only.

Does Data Exploration Tool access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Data Exploration Tool safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Data Exploration Tool use?

Data Exploration Tool is published under the Apache-2.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Data Exploration Tool use?

About 460 tokens (SKILL.md is roughly 1.8k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Data Exploration Tool?

Skills that share tags, products or a category with Data Exploration Tool: Exploratory Data Analysis (spacering-net/codeg, 3.8k stars), Excel and CSV Data Analysis (bytedance/deer-flow, 83k stars), Exploratory Data Analysis (Oleafly/Oleafly, 205 stars) and Python Executor (cortega26/chile-hub, 113 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Data Exploration Tool?

Dbxstudio (a GitHub organization) maintains it in Dbxstudio/dbx-studio, which has 103 GitHub stars. The repository holds 5 skills in this directory. The repository was last updated on August 3, 2026.

Source: Dbxstudio/dbx-studio on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.