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Agent skill

Nsga2

by Optima-CityU in Optima-CityU/LLM4AD_Next

NSGA-II multi-objective evolutionary method skill. An agent skill from Optima-CityU/LLM4AD_Next.

BSD-3-ClauseAuto-check passed

Install Nsga2

skills CLI
$ npx skills add Optima-CityU/LLM4AD_Next --skill nsga2 -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install Optima-CityU/LLM4AD_Next nsga2 --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/Optima-CityU/LLM4AD_Next.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/algo-design/nsga2 .claude/skills/nsga2 && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
nsga2
GitHub stars
574
Token cost
~629 tokens
SKILL.md length
272 words
Files
2
Skills in repo
24
Repo updated
First seen
Licence
BSD-3-Clause

At a glance

NSGA-II multi-objective evolutionary method skill. An agent skill from Optima-CityU/LLM4AD_Next.

  • Works in 3 steps: Method Essence → Recommended Parameters → Acceptance Criteria
  • The user explicitly requests NSGA-II / Non-dominated Sorting Genetic Algorithm
  • SKILL.md covers 1. Method Essence, 2. Recommended Parameters and 4. Acceptance Criteria
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Nsga2 is an agent skill from Optima-CityU/LLM4AD_Next. 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.

Its SKILL.md is about 630 tokens, which your agent loads only when the skill is triggered. The skill folder holds 1 other file (for example `params.yaml`).

The repository describes itself as: A next-generation automatic algorithm design platform, making automated algorithm design more accessible and easier to use. The licence is BSD-3-Clause.

When your agent uses it

  • The user explicitly requests NSGA-II / Non-dominated Sorting Genetic Algorithm
  • Wants multi-objective optimization with non-dominated sorting and crowding distance selection

Example prompts

  • “/nsga2”

Workflow steps

3 steps, taken from the step headings in SKILL.md.

  1. Method Essence
  2. Recommended Parameters
  3. Acceptance Criteria

What it can do on your machine

Read from SKILL.md and the folder at commit e3d3f7b. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md.

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Nsga2 loads about 629 tokens when it runs. Until then it costs about 61 tokens; SKILL.md has 272 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~61
When it runs · the whole SKILL.md, loaded when a task matches
~629

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from Optima-CityU/LLM4AD_Next at commit e3d3f7b, republished under its BSD-3-Clause licence (© Optima-CityU). 272 words, ~629 tokens.

Download SKILL.mdSave it as .claude/skills/nsga2/SKILL.md (or your agent's skills folder). This skill also uses 1 other file; get the full folder from GitHub.
name
nsga2
description
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.
triggers
nsga2, nsga-ii, non-dominated sorting, pareto front optimization

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:

  1. 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
  2. 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.

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
  1. Population initialized; evaluate all individuals
  2. 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
  3. Pareto front gradually expands and becomes more uniform
  4. 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

© Optima-CityU, BSD-3-Clause. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 1 other file in skills/algo-design/nsga2 of Optima-CityU/LLM4AD_Next.

  • SKILL.md
  • params.yaml

Open the folder on GitHubat commit e3d3f7b

Compare with similar skills

Nsga2 next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Nsga2 compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Nsga2 this skillOptima-CityU/LLM4AD_Next574—~629Automated safety check: PassBSD-3-Clause
Modern Array Methodsthedaviddias/Front-End-Checklist74k—~494Automated safety check: PassMIT
Object Altthedaviddias/Front-End-Checklist74k—~429Automated safety check: PassMIT
Santa Methodaffaan-m/ECC276k3 repos~3.1kAutomated safety check: PassMIT
Santa Methodaffaan-m/ECC276k—~2.1kAutomated safety check: PassMIT
Santa Methodaffaan-m/ECC276k—~1.9kAutomated safety check: PassMIT

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Questions about Nsga2

What does Nsga2 do?

NSGA-II multi-objective evolutionary method skill. An agent skill from Optima-CityU/LLM4AD_Next. Nsga2 is an agent skill from Optima-CityU/LLM4AD_Next. NSGA-II multi-objective evolutionary method skill.

When should I use Nsga2?

Nsga2 fits situations like: the user explicitly requests NSGA-II / Non-dominated Sorting Genetic Algorithm; wants multi-objective optimization with non-dominated sorting and crowding distance selection.

How do I install Nsga2 in Claude Code?

Run `npx skills add Optima-CityU/LLM4AD_Next --skill nsga2 -a claude-code`. Or copy the skill folder (skills/algo-design/nsga2 in Optima-CityU/LLM4AD_Next) into .claude/skills/nsga2 in your project. Claude Code loads it when a task matches its description.

How do I install Nsga2 in Codex?

Run `npx skills add Optima-CityU/LLM4AD_Next --skill nsga2 -a codex`. Or copy the skill folder (skills/algo-design/nsga2 in Optima-CityU/LLM4AD_Next) into .agents/skills/nsga2 in your project. Codex loads it when a task matches its description.

Can I use Nsga2 in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add Optima-CityU/LLM4AD_Next --skill nsga2 -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/nsga2, .gemini/skills/nsga2, .github/skills/nsga2 and .opencode/skills/nsga2 in your project.

What does Nsga2 need to run?

SKILL.md names no scripts, command-line tools or credentials: Nsga2 is instructions for the agent only.

Does Nsga2 access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Nsga2 safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Nsga2 use?

Nsga2 is published under the BSD-3-Clause licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Nsga2 use?

About 629 tokens (SKILL.md is roughly 2.5k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Nsga2?

Skills that share tags, products or a category with Nsga2: Modern Array Methods (thedaviddias/Front-End-Checklist, 74k stars), Object Alt (thedaviddias/Front-End-Checklist, 74k stars), Santa Method (affaan-m/ECC, 276k stars) and Santa Method (affaan-m/ECC, 276k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Nsga2?

Optima-CityU (a GitHub organization) maintains it in Optima-CityU/LLM4AD_Next, which has 574 GitHub stars. The repository holds 24 skills in this directory. The repository was last updated on October 9, 2026.

Source: Optima-CityU/LLM4AD_Next on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.