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데이터 및 연구 · SKILL.md

step-by-step-math-solver-with-hints-and-practice

step-by-step-math-solver-with-hints-and-practice

This prompt instructs the AI to act as a patient math tutor and solution checker by taking a user-specified math context (subject, topic, audience, language, notation) and a fully defined problem (statement, data, constraints, goal) and producing a structured, step-by-step solution with formulas, brief justifications, intermediate results, domain checks, an…

Independent GitHub snapshot · Automated classification · Original documentation governs

Skill 문서

GitHub

name: step-by-step-math-solver-with-hints-and-practice description: This prompt instructs the AI to act as a patient math tutor and solution checker by taking a user-specified math context (subject, topic, audience, language, notation) and a fully defined problem (statement, data, constraints, goal) and producing a structured, step-by-step solution with formulas, brief justifications, intermediate results, domain checks, and a final verified answer. It also requires specific presentation elements—goal summary, numbered steps, verification, boxed final result with units, optional alternate methods, key takeaways, and a set of practice problems with short answers—while avoiding disallowed methods, following tool and rounding rules, warning about common mistakes, and stating assumptions if the problem is ambiguous. 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 patient math tutor and solution checker by taking a user-specified math context (subject, topic, audience, language, notation) and a fully defined problem (statement, data, constraints, goal) and producing a structured, step-by-step solution with formulas, brief justifications, intermediate results, domain checks, and a final verified answer. It also requires specific presentation elements—goal summary, numbered steps, verification, boxed final result with units, optional alternate methods, key takeaways, and a set of practice problems with short answers—while avoiding disallowed methods, following tool and rounding rules, warning about common mistakes, and stating assumptions if the problem is ambiguous.

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 keyRequired?DescriptionDefaults
GoalRequired(none)
NumberRequired(none)
Yes_or_NoRequired(none)
Given_dataRequired(none)
Allowed_toolsRequired(none)
Audience_levelRequired(none)
Formula_formatRequired(none)
Specific_topicRequired(none)
Tone_and_styleRequired(none)
Common_mistakesRequired(none)
Output_languageRequired(none)
Methods_to_avoidRequired(none)
Subject_or_fieldRequired(none)
Number_of_methodsRequired(none)
Problem_statementRequired(none)
Step_detail_levelRequired(none)
Rounding_and_unitsRequired(none)
Notation_conventionRequired(none)
Domain_and_constraintsRequired(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:
    • Goal
    • Number
    • Yes_or_No
    • Given_data
    • Allowed_tools
    • Audience_level
    • Formula_format
    • Specific_topic
    • Tone_and_style
    • Common_mistakes
    • Output_language
    • Methods_to_avoid
    • Subject_or_field
    • Number_of_methods
    • Problem_statement
    • Step_detail_level
    • Rounding_and_units
    • Notation_convention
    • Domain_and_constraints
  • Optional: model and options.
    • Present the human with the default model gpt-4.1-mini and its available options. Look up gpt-4.1-mini 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 gpt-4.1-mini, 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 step-by-step-math-solver-with-hints-and-practice).

Command form:

betterprompt generate step-by-step-math-solver-with-hints-and-practice \
  [--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: gpt-4.1-mini.
  • 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 step-by-step-math-solver-with-hints-and-practice \
  --input Goal=<value> \
  --input Number=<value> \
  --input Yes_or_No=<value> \
  --input Given_data=<value> \
  --input Allowed_tools=<value> \
  --input Audience_level=<value> \
  --input Formula_format=<value> \
  --input Specific_topic=<value> \
  --input Tone_and_style=<value> \
  --input Common_mistakes=<value> \
  --input Output_language=<value> \
  --input Methods_to_avoid=<value> \
  --input Subject_or_field=<value> \
  --input Number_of_methods=<value> \
  --input Problem_statement=<value> \
  --input Step_detail_level=<value> \
  --input Rounding_and_units=<value> \
  --input Notation_convention=<value> \
  --input Domain_and_constraints=<value> \
  --model gpt-4.1-mini \
  --options '{}'
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