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data-interpreter

Use when the user wants plain-English interpretation of a dataset including patterns, surprises, and misleading aspects. Triggers include "analyze this data", "interpret these numbers", "what does this data mean".

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Install command

npx skills add https://github.com/codejunkie99/prompt-skills --skill data-interpreter

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Source

codejunkie99/prompt-skills

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UpdatedApril 26, 2026 at 10:50

SKILL.md

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name	data-interpreter
description	Use when the user wants plain-English interpretation of a dataset including patterns, surprises, and misleading aspects. Triggers include "analyze this data", "interpret these numbers", "what does this data mean".

Data Interpreter

When the user supplies a dataset, surface the key patterns, surprises, and risks of misinterpretation.

Variables

[PASTE DATA]
[WHO WILL READ THIS ANALYSIS AND THEIR TECHNICAL LEVEL]

Prompt Template

Analyze this data:

[PASTE DATA — CSV, table, numbers, survey results, etc.]

Provide:

Summary statistics (key numbers at a glance)
The 3 most important patterns or trends
2 surprising findings that are not immediately obvious
1 potentially misleading aspect of this data (what could be misinterpreted?)
3 questions this data raises that would require additional data to answer

Audience: [WHO WILL READ THIS ANALYSIS AND THEIR TECHNICAL LEVEL] Present findings in plain English first, then include the supporting numbers.

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Source

codejunkie99

codejunkie99/prompt-skills

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Useful forSOC

Data ScientistsComputer and Mathematical Occupations15-2051L4

name	data-interpreter
description	Use when the user wants plain-English interpretation of a dataset including patterns, surprises, and misleading aspects. Triggers include "analyze this data", "interpret these numbers", "what does this data mean".

Data Interpreter

When the user supplies a dataset, surface the key patterns, surprises, and risks of misinterpretation.

Variables

[PASTE DATA]
[WHO WILL READ THIS ANALYSIS AND THEIR TECHNICAL LEVEL]

Prompt Template

Analyze this data:

[PASTE DATA — CSV, table, numbers, survey results, etc.]

Provide:

Summary statistics (key numbers at a glance)
The 3 most important patterns or trends
2 surprising findings that are not immediately obvious
1 potentially misleading aspect of this data (what could be misinterpreted?)
3 questions this data raises that would require additional data to answer

Audience: [WHO WILL READ THIS ANALYSIS AND THEIR TECHNICAL LEVEL] Present findings in plain English first, then include the supporting numbers.