multi-constraint-ladder-synthesiser

---

name: multi-constraint-ladder-synthesiser description: This prompt instructs the AI to act as an expert systems designer and produce a structured solution to a provided problem while satisfying multiple explicit constraints and stated assumptions. The expected outcome is a concise final plan within a word limit, a bullet-point mapping that demonstrates how each constraint is met by specific parts of the plan, and a short section outlining risks, trade-offs, or assumptions made to reconcile competing requirements. 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 an expert systems designer and produce a structured solution to a provided problem while satisfying multiple explicit constraints and stated assumptions. The expected outcome is a concise final plan within a word limit, a bullet-point mapping that demonstrates how each constraint is met by specific parts of the plan, and a short section outlining risks, trade-offs, or assumptions made to reconcile competing requirements.

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
problem	Required		(none)
Assumptions	Required		(none)
constraint1	Required		(none)
constraint2	Required		(none)
constraint3	Required		(none)
constraint4	Required		(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:
  • problem
  • Assumptions
  • constraint1
  • constraint2
  • constraint3
  • constraint4
• 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 multi-constraint-ladder-synthesiser).

Command form:

betterprompt generate multi-constraint-ladder-synthesiser \
  [--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 multi-constraint-ladder-synthesiser \
  --input problem=<value> \
  --input Assumptions=<value> \
  --input constraint1=<value> \
  --input constraint2=<value> \
  --input constraint3=<value> \
  --input constraint4=<value> \
  --model gpt-4.1-mini \
  --options '{}'