Dataset Profiler

Community

oxbshw

dataset-profiler

Use when first encountering a new dataset — produces a structured profile (schema, missingness, distributions, outliers, gotchas) before any analysis.

Overview

Publisher	oxbshw
Repository	`LLM-Agents-Ecosystem-Handbook`
Skill name	`dataset-profiler`
Stars	552
Forks	93
Bundled files	1
License	MIT
Links	Skill source Repository

Markdown instructions
A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.
Works with any LLM
AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.
1 bundled files
Scripts, templates, and references the model can read while it works. Files are read-only and never executed.
Open source
Published by oxbshw on GitHub. Read the source before you install it.

Installation

Install the Dataset Profiler AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

Open the app and go to Plugins → Skills.
Choose "Install from GitHub".
Paste the skill folder URL below and confirm.
https://github.com/oxbshw/LLM-Agents-Ecosystem-Handbook/tree/main/skills/catalog/dataset-profiler
Enable the skill in any chat where you want it available.

Store

Installed

Skills

Add skills

Import one or more skills from a public GitHub folder or a local .skill or .zip archive, or SKILL.md file.

From GitHub URLFrom .skill, .zip, or SKILL.md

GitHub repo or folder

https://github.com/oxbshw/LLM-Agents-Ecosystem-Handbook/tree/main/skills/catalog/dataset-profiler

Points to a single skill folder, or any folder that contains multiple skills. Public repos only.

CancelContinue

Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills

git clone --depth 1 https://github.com/oxbshw/LLM-Agents-Ecosystem-Handbook.git /tmp/LLM-Agents-Ecosystem-Handbook
mkdir -p .claude/skills
cp -r /tmp/LLM-Agents-Ecosystem-Handbook/skills/catalog/dataset-profiler .claude/skills/dataset-profiler

Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Dataset Profiler in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Dataset Profiler on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Dataset Profiler is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

Loaded only when it is needed
The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.
Switch models mid-chat
Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Dataset Profiler

When to use

A new dataset arrives and you need to understand it before using it
Before reproducing an analysis that referenced a dataset
When data quality is suspect ("the chart looked wrong")

When NOT to use

Streaming / online data (this is point-in-time)
Sensitive PII without an explicit allow-list

Inputs

Name	Type	Required	Notes
`path`	path	yes	CSV / Parquet / JSONL
`target`	string	no	column of interest (gets extra distribution detail)

Outputs

profile.md with: Source, Schema, Missingness, Distributions, Outliers, Joins / keys, Gotchas, Open questions.

Workflow

Load with the right reader (extension-detected); record row count, file size
Schema: column → dtype → nullable → example value
Missingness: % per column, top columns by missingness
Distributions: numeric (min, p50, p95, max, std), categorical (top-k, cardinality)
Outliers: flag rows beyond p99 + 3·IQR for numerics
Identify potential keys (unique columns) and join candidates
Gotchas: timezone columns, mixed encodings, suspicious all-zero rows, magic values (-1, 9999-12-31)
Open questions: ambiguous columns / values that need owner input

References

references/profile-template.md

Success criteria

Every column appears in Schema + Missingness
Outliers section includes example rows
Gotchas section is non-empty (real datasets always have some)

Failure modes

File too large to read in memory → switch to streaming + sampled stats; flag prominently
Encoding fails → try common alternatives; if all fail, surface and stop

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

references/profile-template.md1 KB

Frequently asked questions

What does the Dataset Profiler AI skill do?

Use when first encountering a new dataset — produces a structured profile (schema, missingness, distributions, outliers, gotchas) before any analysis.

Why use Dataset Profiler on TypingMind?

Because you install it once and use it with any model. Dataset Profiler is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Dataset Profiler in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/oxbshw/LLM-Agents-Ecosystem-Handbook/tree/main/skills/catalog/dataset-profiler. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Dataset Profiler?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Dataset Profiler?

As many as you like. As long as a model supports skills, you can use Dataset Profiler with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Dataset Profiler AI skill free?

Yes. It is published on GitHub by oxbshw under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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Overview

Installation

Install in TypingMind

Install in another agent

Use it in TypingMind

Works with any AI model

Skill instructions

Dataset Profiler

When to use

When NOT to use

Inputs

Outputs

Workflow

References

Success criteria

Failure modes

Bundled files

Frequently asked questions

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