financial-engineer-digital-employee@2.0.5
VERIFIED· install onlyPublisher claims: "覆盖数据探查、单变量分析、特征工程、LR评分卡、XGBoost/DNN建模、超参数调优、模型解释、多模型对比、分群建模、DeepModel集成全流程。从数据到模型上线的一站式机器学习建模能力。" Observed in sandbox: no network, touches nothing outside the project, writes no memory.
Coverage
Nothing executable in the bundle ran; the trace covers the install step only.- Tested
- every file read, file written and host contacted by what ran
- Not tested
- use of the skill by an agent
Is [email protected] safe to install?
KillerSkills ran it in the KillerSkills honeypot sandbox (1 scenario; nothing executable in the bundle ran; the trace covers the install step only) on 2026-11-12 and scored it 90/100 (Verified). In what ran, nothing we could detect went wrong: no undeclared network egress, no credential reads, no persistent instruction writes. What it does with a real credential was not observed; the static findings and the publisher carry the rest of the score. Summary: no network, touches nothing outside the project, writes no memory.
Behavior trace
Honeypot run · 0 s · 1 scenarios · 0 deviationsStatic findings
--config ./config.json --output_dir ./outputs/deepmodelFix: Remove the call, or declare the host in frontmatter and explain in the README what is sent and why."submodel_paths": ["./outputs/deepmodel/高风险.json", "./outputs/deepmodel/低风险.json"],Fix: Remove the call, or declare the host in frontmatter and explain in the README what is sent and why.--auto --config ./config.json --output_dir ./outputs/deepmodelFix: Remove the call, or declare the host in frontmatter and explain in the README what is sent and why.2. **各模型文件**：XGB(.json) / LR(.joblib) / DNN(.pt，含 imputer+scaler 元数据)Fix: Remove the call, or declare the host in frontmatter and explain in the README what is sent and why."submodel_paths": ["./outputs/deepmodel/高风险.json", "./outputs/deepmodel/低风险.json"],Fix: Remove the call, or declare the host in frontmatter and explain in the README what is sent and why.Cost to the agent
Tokens estimated at four characters each. Skills load their instruction text when triggered; the figure is what that costs.
Known vulnerabilities
Vulnerability advisories (OSV) cover npm and PyPI packages; this registry has no advisory database.