from-principle-to-example

---

name: from-principle-to-example description: This prompt instructs the AI to act as a practical educator who takes an abstract theory provided by the user and turns it into clear, real-world examples that demonstrate how the idea plays out in everyday situations. The result is one or more concise, focused scenarios (without jargon, added assumptions, or unrelated concepts) that preserve the theory’s original meaning while making it easier to understand and apply. compatibility: Requires betterprompt >= 0.1.3 metadata: openclaw: homepage: https://github.com/BetterPromptme/skills emoji: 🧩 requires: anyBins: - betterprompt - bp os: - linux - darwin install: - id: node kind: node package: betterprompt bins: [betterprompt, bp] label: Install BetterPrompt CLI (node)

What it does

This prompt instructs the AI to act as a practical educator who takes an abstract theory provided by the user and turns it into clear, real-world examples that demonstrate how the idea plays out in everyday situations. The result is one or more concise, focused scenarios (without jargon, added assumptions, or unrelated concepts) that preserve the theory’s original meaning while making it easier to understand and apply.

For more installation instructions go to https://raw.githubusercontent.com/BetterPromptme/skills/refs/heads/main/betterprompt/SKILL.md to check out this skill.

Inputs

textInputs

Pass each text input using --input <key>=<value> flags.

Variable key	Required?	Description	Defaults
Theory_or_concept	Required	PASTE THEORY OR CONCEPT HERE	(none)

Models and options

This skill's modality is: text.

To discover which model values you can use (and which options keys/values are valid for each model), run:

betterprompt resources --models-only --json

Then filter the returned JSON array to entries where modality is "text".

How to run

Step 1: Collect inputs

First, run betterprompt resources --models-only --json and filter to modality: "text" to discover valid models and available options:

betterprompt resources --models-only --json

Use only the models and option values that appear in the filtered results.

Then collect all inputs from the human:

• Required text inputs:
  • Theory_or_concept
• Optional: model and options.
  • Present the human with the default model deepseek-r1 and its available options. Look up deepseek-r1 in the betterprompt resources output (filtered to modality "text") and show its availableOptions as: key: val1, val2 (default), val3 | key2: .... Mark a value (default) if it matches these defaults: {}.
  • If the human does not specify, defaults are used: model deepseek-r1, options {}. Other models from the resources call are also available.

If any required text input is missing, ask the human for what's missing. Do not assume or fabricate values.

Step 2: Run via BetterPrompt CLI

Use the frontmatter's name as the positional argument (for this skill, use from-principle-to-example).

Command form:

betterprompt generate from-principle-to-example \
  [--input <key>=<value>] \
  [--model <model>] \
  [--options <options JSON>] \
  [--json]

Notes:

• Pass each text input as a separate --input <key>=<value> flag.
• If the human does not mention a model, omit --model and BetterPrompt will use the default model: deepseek-r1.
• If the human does not mention options, omit --options and BetterPrompt will use the default options: {}.
• If the run times out, the response will include a runId you can use to fetch the result later.

Example (using defaults shown above):

betterprompt generate from-principle-to-example \
  --input Theory_or_concept=<value> \
  --model deepseek-r1 \
  --options '{}'