nsga2 SKILL.md skillA
nsga2 from optima-cityu/llm4ad_next is an agent skill: a SKILL.md folder an AI agent loads when a task calls for it.
mdr add optima-cityu/llm4ad_next/nsga2@git:20260825.2005c66Pins git:20260825.2005c66 in mdr.lock. Pin the fingerprint instead.
- Audit grade
- A, 17 of 17 checks passed
- Kind
- SKILL.md skill
- Repository
- optima-cityu/llm4ad_next
- Path
skills/algo-design/nsga2/SKILL.md- Versions recorded
- 1
- Latest version
- git:20260825.2005c66, committed Aug 25, 2026
- Size
- 2,529 bytes
- Repository stars
- 674
- License
- BSD-3-Clause
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.
Collected from public GitHub. Every version is saved exactly as it was and never changes. Install it at an exact version with the mdr tool, and every file is checked before it reaches your agent. The main file is checked against the SHA-256 fingerprint recorded here, and the others against the fingerprints GitHub keeps for its source commit. The automatic checks below grade the latest version, and the same checks always give the same file the same grade.
What the file says
# 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. ## 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 1. Population initialized; evaluate all individuals 2. Each generation: …
Read the whole file at its exact version.
How to install
mdr add optima-cityu/llm4ad_next/nsga2@sha256:fa985c1b6f75b920The line at the top of this page pins the label git:20260825.2005c66, which is what most people want. This one pins the sha256 fingerprint of the contents instead, so it survives a label being moved. Either way the exact version is written to mdr.lock, and mdr install downloads and checks those contents again, so it installs them exactly or stops with an error.
[](https://markdownregistry.com/a/art_dzo7igukxcpzuesf)
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Versions
The registry has recorded 1 version of this file, committed on Aug 25, 2026.
Audit of the latest version
- pass: Frontmatter block present
- pass: Frontmatter declares a name
- pass: Frontmatter declares a description
- pass: Size between 200 bytes and 200 KB (2529 bytes)
- pass: No zero-width or bidi control characters
- pass: No instruction hidden inside an HTML comment
- pass: No link to an exfiltration or paste host
- pass: No credential-shaped string
- pass: No instruction to send local credentials anywhere
- pass: No text hidden with inline styles
- pass: No prompt-injection phrasing
- pass: No curl or wget piped into a shell
- pass: No recursive delete of root, home or parent
- pass: No instruction to read or print local credentials
- pass: No base64 blob over 200 characters
- pass: No link to a raw IP address
- pass: No script tag
Source
optima-cityu/llm4ad_next · 674 stars · license BSD-3-Clause · pushed 2026-10-22 · branch main
API
GET https://markdownregistry.com/api/v1/artifacts/art_dzo7igukxcpzuesf GET https://markdownregistry.com/api/v1/resolve?ref=optima-cityu/llm4ad_next/nsga2 GET https://markdownregistry.com/api/v1/blob/fa985c1b6f75b920a8dab8d8642509d5840832373c6bd5376c62393a2437b660
Your AI assistant does the legwork. You hear about the deals worth your word. Hand yours the standing instructions at modelranch.com and it joins the network that reads files like this one.
Guides: the SKILL.md format and its required fields · what to check before you install a skill · how to pin a skill to an exact version · where to find agent skills · keeping a team on the same skills · which agent file does what.