Nsga2

Organization

Optima-CityU

nsga2

NSGA-II multi-objective evolutionary method skill. USE WHEN the user explicitly requests NSGA-II / Non-dominated Sorting Genetic Algorithm, or wants multi-objective optimization with non-dominated sorting and crowding distance selection.

Overview

Publisher	Optima-CityU
Repository	`LLM4AD_Next`
Skill name	`nsga2`
Stars	596
Forks	41
Bundled files	1
License	BSD-3-Clause
Links	Skill source Repository Homepage

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.
1 bundled files
Scripts, templates, and references the model can read while it works. Files are read-only and never executed.
Open source
Published by Optima-CityU on GitHub. Read the source before you install it.

Installation

Install the Nsga2 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/Optima-CityU/LLM4AD_Next/tree/main/skills/algo-design/nsga2
Enable the skill in any chat where you want it available.

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/Optima-CityU/LLM4AD_Next.git /tmp/LLM4AD_Next
mkdir -p .claude/skills
cp -r /tmp/LLM4AD_Next/skills/algo-design/nsga2 .claude/skills/nsga2

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

Use it in TypingMind

Enable Nsga2 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 Nsga2 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 Nsga2 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.

NSGA-II Skill

Paper: Deb et al., "A fast and elitist multiobjective genetic algorithm: NSGA-II", IEEE TEC 2002.

1. Method Essence

NSGA-II is a classic multi-objective GA with a two-step selection mechanism:

Non-dominated sorting: Divide the population into layers — Pareto front layer (not dominated by anyone), second layer (dominated only by front layer), etc.; earlier layers have higher priority for survival
Crowding distance: Within the same layer, sort by "neighbor sparsity" in objective space; sparse individuals are preserved first (maintains uniform front coverage)

Overall cycle: Generate offspring → merge parent-offspring → non-dominated sorting → truncate to pop_size by layer + crowding → next generation. LLM version uses LLM operators (E1/E2/M1/M2) instead of traditional genetic operators for offspring generation.

2. Recommended Parameters

See params.yaml in this directory for the recommended parameter configuration.

Note: The number of objectives is determined by the length of objective_metrics.

What Happens During Evolution

Population initialized; evaluate all individuals
Each generation:
- Generate offspring via LLM operators
- Merge parent + offspring populations
- Non-dominated sorting: classify into layers
- Crowding distance: within each layer, rank by sparsity
- Truncate to population_size by layer priority + crowding
Pareto front gradually expands and becomes more uniform
Final front represents optimal trade-offs between objectives

Common Pitfalls

Front not diverse → increase population_size or enable more operators
Convergence too slow → check if objectives are conflicting; reduce num_objs if possible
Single-objective dominance → verify num_objs matches your problem; check evaluator metrics

4. Acceptance Criteria

Non-dominated front visible in evolution log (Pareto front members identified)
Front covers multiple trade-off points (not clustered in one region)
Crowding distance prevents front collapse (uniform spread)
Final best individuals span the front from extreme to balanced solutions

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

params.yaml1 KB

Frequently asked questions

What does the Nsga2 AI skill do?

Why use Nsga2 on TypingMind?

Because you install it once and use it with any model. Nsga2 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 Nsga2 in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/Optima-CityU/LLM4AD_Next/tree/main/skills/algo-design/nsga2. 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 Nsga2?

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 Nsga2?

As many as you like. As long as a model supports skills, you can use Nsga2 with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Nsga2 AI skill free?

Yes. It is published on GitHub by Optima-CityU under the BSD-3-Clause 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

NSGA-II Skill

1. Method Essence

2. Recommended Parameters

What Happens During Evolution

Common Pitfalls

4. Acceptance Criteria

Bundled files

Frequently asked questions

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