Data Processing logo

Data Processing

Organization
aiskillstore
data-processing

Process JSON with jq and YAML/TOML with yq. Filter, transform, query structured data efficiently. Triggers on: parse JSON, extract from YAML, query config, Docker Compose, K8s manifests, GitHub Actions workflows, package.json, filter data.

Overview

Publisheraiskillstore
Repositorymarketplace
Skill namedata-processing
Stars
427
Forks
45
Bundled files
4
LicenseMIT
Links
  • 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.

  • 4 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by aiskillstore on GitHub. Read the source before you install it.

Installation

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

1

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.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

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/aiskillstore/marketplace.git /tmp/marketplace
mkdir -p .claude/skills
cp -r /tmp/marketplace/skills/0xdarkmatter/data-processing .claude/skills/data-processing
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Data Processing 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 Data Processing 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 Data Processing 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.

Data Processing

Query, filter, and transform structured data (JSON, YAML, TOML) efficiently from the command line.

Tools

ToolCommandUse For
jqjq '.key' file.jsonJSON processing
yqyq '.key' file.yamlYAML/TOML processing

jq Essentials

bash
# Extract single field
jq '.name' package.json

# Extract nested field
jq '.scripts.build' package.json

# Extract from array
jq '.dependencies[0]' package.json

# Extract multiple fields
jq '{name, version}' package.json

# Navigate deeply nested
jq '.data.users[0].profile.email' response.json

# Filter by condition
jq '.users[] | select(.active == true)' data.json

# Transform each element
jq '.users | map({id, name})' data.json

# Count elements
jq '.users | length' data.json

# Raw string output
jq -r '.name' package.json

yq Essentials

bash
# Extract field
yq '.name' config.yaml

# Extract nested
yq '.services.web.image' docker-compose.yml

# List all keys
yq 'keys' config.yaml

# List all service names (Docker Compose)
yq '.services | keys' docker-compose.yml

# Get container images (K8s)
yq '.spec.template.spec.containers[].image' deployment.yaml

# Update value (in-place)
yq -i '.version = "2.0.0"' config.yaml

# TOML to JSON
yq -p toml -o json '.' config.toml

Quick Reference

Taskjqyq
Get fieldjq '.key'yq '.key'
Array elementjq '.[0]'yq '.[0]'
Filter arrayjq '.[] | select(.x)'yq '.[] | select(.x)'
Transformjq 'map(.x)'yq 'map(.x)'
Countjq 'length'yq 'length'
Keysjq 'keys'yq 'keys'
Pretty printjq '.'yq '.'
Compactjq -cyq -o json -I0
Raw outputjq -ryq -r
In-place edit-yq -i

When to Use

  • Reading package.json dependencies
  • Parsing Docker Compose configurations
  • Analyzing Kubernetes manifests
  • Processing GitHub Actions workflows
  • Extracting data from API responses
  • Filtering large JSON datasets
  • Config file manipulation
  • Data format conversion

Additional Resources

For complete pattern libraries, load:

  • ./references/jq-patterns.md - Arrays, filtering, transformation, aggregation, output formatting
  • ./references/yq-patterns.md - Docker Compose, K8s, GitHub Actions, TOML, YAML modification
  • ./references/config-files.md - package.json, tsconfig, eslint/prettier patterns

Bundled files

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

Frequently asked questions

What does the Data Processing AI skill do?

Process JSON with jq and YAML/TOML with yq. Filter, transform, query structured data efficiently. Triggers on: parse JSON, extract from YAML, query config, Docker Compose, K8s manifests, GitHub Actions workflows, package.json, filter data.

Why use Data Processing on TypingMind?

Because you install it once and use it with any model. Data Processing 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 Data Processing in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/aiskillstore/marketplace/tree/main/skills/0xdarkmatter/data-processing. 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 Data Processing?

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 Data Processing?

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

Is the Data Processing AI skill free?

Yes. It is published on GitHub by aiskillstore 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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