Sql To Business Logic

Community

nimrodfisher

sql-to-business-logic

Translate SQL queries into plain language business logic. Use when documenting queries, explaining analysis to non-technical stakeholders, code reviewing for correctness, or building a query catalog.

Overview

Publisher	nimrodfisher
Repository	`data-analytics-skills`
Skill name	`sql-to-business-logic`
Stars	493
Forks	87
Bundled files	3
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.
3 bundled files
Scripts, templates, and references the model can read while it works. Files are read-only and never executed.
Open source
Published by nimrodfisher on GitHub. Read the source before you install it.

Installation

Install the Sql To Business Logic 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/nimrodfisher/data-analytics-skills/tree/main/02-documentation-knowledge/sql-to-business-logic
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/nimrodfisher/data-analytics-skills/tree/main/02-documentation-knowledge/sql-to-business-logic

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/nimrodfisher/data-analytics-skills.git /tmp/data-analytics-skills
mkdir -p .claude/skills
cp -r /tmp/data-analytics-skills/02-documentation-knowledge/sql-to-business-logic .claude/skills/sql-to-business-logic

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

Use it in TypingMind

Enable Sql To Business Logic 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 Sql To Business Logic 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 Sql To Business Logic 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.

SQL to Business Logic Translator

When to use

A stakeholder asks "what exactly does this query calculate?"
Documenting a query library or a dbt model for non-technical readers
Reviewing a query for correctness by comparing its logic to the business requirement
Onboarding new analysts to existing SQL patterns
Translating legacy undocumented queries before refactoring

Process

Receive the query and context — obtain the SQL and the business question it answers. Also collect any schema notes (what the key tables and columns represent in business terms).
Translate the FROM/JOIN structure — describe in plain language which data sources are combined and what type of join is used (inner keeps only matches; left keeps all rows from the left side). Note if the join type seems inconsistent with the stated purpose.
Translate WHERE filters — list each filter condition as a business rule in plain language (e.g., status = 'completed' → "only includes orders that have been paid and fulfilled").
Explain GROUP BY and aggregations — describe what each aggregation computes and at what grain. Use scripts/sql_explainer.py to automate a first-pass structural parse.
Summarise output columns — for each output column, state its business meaning and any edge cases (nulls, rounding, currency units).
Flag issues and write validation questions — identify potential problems (implicit null propagation, unexpected fan-out, hardcoded dates). Generate 3–5 questions the query author should confirm. Use assets/query_documentation_template.md to record the full translation.

Inputs the skill needs

The complete SQL query (SELECT through ORDER BY)
The business question the query is intended to answer
Table and column descriptions (or a data catalog entry)
Any business rules for key status values, date handling, or currency
The intended output: who reads the result and for what decision

Output

scripts/sql_explainer.py — parses a SQL query and generates a structured plain-language explanation
assets/query_documentation_template.md — completed translation covering purpose, step-by-step logic, output columns, business rules, and validation questions
Optionally: a flowchart representation of the query logic

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 Sql To Business Logic AI skill do?

Translate SQL queries into plain language business logic. Use when documenting queries, explaining analysis to non-technical stakeholders, code reviewing for correctness, or building a query catalog.

Why use Sql To Business Logic on TypingMind?

Because you install it once and use it with any model. Sql To Business Logic 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 Sql To Business Logic in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/nimrodfisher/data-analytics-skills/tree/main/02-documentation-knowledge/sql-to-business-logic. 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 Sql To Business Logic?

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 Sql To Business Logic?

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

Is the Sql To Business Logic AI skill free?

Yes. It is published on GitHub by nimrodfisher 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

SQL to Business Logic Translator

When to use

Process

Inputs the skill needs

Output

Bundled files

Frequently asked questions

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