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Install in OpenClaw
/install mars-clouds-clustering-pareto-optimization
Description
Multi-objective optimization with Pareto frontiers. Use when optimizing multiple conflicting objectives simultaneously, finding trade-off solutions, or compu...
Usage Guidance
This is an instruction-only, documentation-style skill for Pareto/frontier computations and appears coherent. Before running code: ensure the runtime has the Python packages referenced (paretoset, pandas, numpy, matplotlib) or be prepared to install them from trusted sources (e.g., PyPI). Be aware the examples write a local CSV and show plotting—verify you are comfortable saving outputs to the agent environment and do not feed sensitive data into the examples. If you need the skill to auto-install packages, require an install spec or inspect any installer before granting permission to download and run code.
Capability Analysis
Type: OpenClaw Skill
Name: mars-clouds-clustering-pareto-optimization
Version: 0.1.0
The skill bundle provides educational content and Python code examples for Pareto optimization and multi-objective trade-off analysis. The code in SKILL.md uses standard data science libraries (pandas, numpy, paretoset) and contains no indicators of malicious intent, data exfiltration, or prompt injection.
Capability Assessment
Purpose & Capability
Name and description match the SKILL.md content. The instructions use Python libraries (paretoset, pandas, numpy, matplotlib) but the skill declares no install steps or required binaries—this is plausible for an instruction-only skill but means the runtime must already provide those libraries.
Instruction Scope
Instructions stay on-topic: computing Pareto sets, example code, plotting, and saving a CSV. They do not instruct reading unrelated files, accessing environment variables, or transmitting data externally.
Install Mechanism
No install spec (instruction-only). That is the lowest-risk install model; however, users should note the examples assume Python packages are available in the execution environment.
Credentials
The skill requests no environment variables, credentials, or config paths—proportionate for a local computation/visualization helper.
Persistence & Privilege
always is false and there is no persistence or requests to modify other skills or system settings.
How to Use
- Make sure OpenClaw is installed (local or Docker)
- Run the install command in chat:
/install mars-clouds-clustering-pareto-optimization - After installation, invoke the skill by name or use
/mars-clouds-clustering-pareto-optimization - Provide required inputs per the skill's parameter spec and get structured output
Version History
v0.1.0
Bulk publish from all-task-skills-dedup
Metadata
Frequently Asked Questions
What is pareto-optimization?
Multi-objective optimization with Pareto frontiers. Use when optimizing multiple conflicting objectives simultaneously, finding trade-off solutions, or compu... It is an AI Agent Skill for Claude Code / OpenClaw, with 75 downloads so far.
How do I install pareto-optimization?
Run "/install mars-clouds-clustering-pareto-optimization" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.
Is pareto-optimization free?
Yes, pareto-optimization is completely free, licensed under MIT-0. You can download, install and use it at no cost.
Which platforms does pareto-optimization support?
pareto-optimization is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).
Who created pareto-optimization?
It is built and maintained by lnj22 (@lnj22); the current version is v0.1.0.
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