风险评分

94/100 (Very Low)

OpenClaw: benign
VirusTotal: benign
StaticScan: unknown

Ml Model Eval Benchmark

作者: Muhammad Mazhar Saeed
Slug:ml-model-eval-benchmark
版本:0.1.0
更新时间:2026-02-27 05:31:57
风险信息

OpenClaw: benign

查看 OpenClaw 分析摘要(前 200 字预览)
The skill is internally consistent with its stated purpose: it contains an instruction doc and a small, local script that reads a JSON payload, computes weighted scores, and writes a leaderboard — no ...

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原始 JSON 数据
{
    "latestVersion": {
        "_creationTime": 1772136624524,
        "_id": "k974k1bk96443h22v2asvcr1fh81xtdq",
        "changelog": "- Initial release of ml-model-eval-benchmark.\n- Supports weighted metric evaluation and deterministic model ranking.\n- Enables benchmark leaderboard generation and model promotion decisions.\n- Includes scripts and guides for consistent evaluation workflows.\n- Enforces standardized metric names, scales, and explicit weighting documentation.",
        "changelogSource": "auto",
        "createdAt": 1772136624524,
        "version": "0.1.0"
    },
    "owner": {
        "_creationTime": 0,
        "_id": "publishers:missing",
        "displayName": "Muhammad Mazhar Saeed",
        "handle": "0x-professor",
        "image": "https:\/\/avatars.githubusercontent.com\/u\/160357695?v=4",
        "kind": "user",
        "linkedUserId": "kn757hy9x0k6n9x9ck9v9j4ywd81we48"
    },
    "ownerHandle": "0x-professor",
    "skill": {
        "_creationTime": 1772136624524,
        "_id": "kd7a8rjspn5vvjypvqz8ghfc0981xagf",
        "badges": [],
        "createdAt": 1772136624524,
        "displayName": "Ml Model Eval Benchmark",
        "latestVersionId": "k974k1bk96443h22v2asvcr1fh81xtdq",
        "ownerUserId": "kn757hy9x0k6n9x9ck9v9j4ywd81we48",
        "slug": "ml-model-eval-benchmark",
        "stats": {
            "comments": 0,
            "downloads": 272,
            "installsAllTime": 2,
            "installsCurrent": 2,
            "stars": 0,
            "versions": 1
        },
        "summary": "Compare model candidates using weighted metrics and deterministic ranking outputs. Use for benchmark leaderboards and model promotion decisions.",
        "tags": {
            "latest": "k974k1bk96443h22v2asvcr1fh81xtdq"
        },
        "updatedAt": 1772141517798
    }
}