地动仪气候模型 Dizhenyi Climate Model
PassAudited by VirusTotal on May 5, 2026.
Overview
Type: OpenClaw Skill Name: dizhendongyi-climate Version: 3.0.0 The 'dizhendongyi-climate' skill bundle is a legitimate scientific modeling framework for orbital-scale climate prediction. The Python scripts (e.g., climate_predictor.py, febe_solver.py, orbital_forcing.py) implement mathematical models based on Milankovitch cycles and energy balance equations using standard libraries like numpy. There is no evidence of data exfiltration, malicious execution, or prompt injection; the code focuses entirely on climate simulations and writes results to local temporary files (/tmp/) for data persistence. The documentation in SKILL.md and README.md is consistent with the provided code logic.
Findings (0)
Artifact-based informational review of SKILL.md, metadata, install specs, static scan signals, and capability signals. ClawScan does not execute the skill or run runtime probes.
Installing dependencies could pull a different or compromised package version if the package source or environment is not trusted.
The dependency is unpinned. This is normal for a numpy-based climate calculation skill, but users rely on the package source and currently get whatever numpy version pip resolves.
numpy
Install in a virtual environment, use a trusted package index, and consider pinning numpy to a known-good version.
Using the skill means running local code on the user's machine and producing local output files.
The skill is designed to run included local Python scripts. This is expected for the stated modeling purpose, and the visible code is numerical/printing logic rather than network, credential, or destructive behavior.
python3 scripts/climate_predictor.py long
Review the scripts if desired and run them in a normal user account or virtual environment rather than a privileged shell.