100/100 (Very Low)

OpenClaw： benign
VirusTotal： benign
StaticScan： clean

OpenClaw： benign

The skill's requested resources and runtime instructions are consistent with an advanced biostatistics/actuarial analysis helper — it asks the agent to design, run, and report Python-based analyses an...

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VirusTotal： benign VT 报告

静态扫描： clean

No suspicious patterns detected.

README 未提供

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        "_id": "k97acw5ydmqr0qrseag4hjqzgs83czs0",
        "changelog": "Initial release with comprehensive biostatistical and computational analytics capabilities:\n\n- Provides stochastic, chaos-theoretic, and propensity modeling frameworks for clinical data analysis.\n- Supports Bayesian analysis, Monte Carlo simulation, and classic statistical methods (e.g., survival analysis, mixed models).\n- Includes machine learning and deep learning tools for both structured and unstructured biomedical data.\n- Features robust multiple comparisons handling, actuarial modeling, and advanced health economics analytics.\n- Enforces rigorous statistical reporting standards (interval estimates, assumption checks, clinical relevance).\n- Python environment includes core data science and statistical libraries; PyMC installable if full Bayesian MCMC needed.",
        "changelogSource": "auto",
        "createdAt": 1774194514757,
        "version": "1.0.0"
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        "displayName": "CryptoReuMD",
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    "ownerHandle": "cryptoreumd",
    "skill": {
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        "_id": "kd7b1acdcgcb93ja1fdv3d8h3h83dnhs",
        "badges": [],
        "createdAt": 1774194514757,
        "displayName": "Biostatistics: Actuarial-Level Statistical Analysis",
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        "ownerUserId": "kn7ayqabdmtx703e35dav28n9183ac53",
        "slug": "biostatistics",
        "stats": {
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        "summary": "Provides advanced actuarial-level biostatistical analyses including Bayesian inference, Monte Carlo simulation, machine learning, survival models, and health...",
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