100/100 (Very Low)

OpenClaw： benign
VirusTotal： benign
StaticScan： clean

OpenClaw： benign

The skill's requests and runtime instructions are coherent with an LLM inference energy-advisor: it needs GPU tooling (nvidia-smi, python), ships measurement data, and its prompts/code snippets match ...

[内容已截断]

VirusTotal： benign VT 报告

静态扫描： clean

No suspicious patterns detected.

README 未提供

{
    "latestVersion": {
        "_creationTime": 1773830049910,
        "_id": "k978rzgpp4mx6a9ja481e045ah835rrj",
        "changelog": "EcoCompute 2.5.0 — Improved clarity, shorter intro, and concise mood system.\n\n- Simplified main description and mood system for faster onboarding.\n- Updated usage examples to be clearer and more approachable.\n- Added a \"Links\" section for external resources and documentation access.\n- Streamlined agent instructions: all references to lobster persona now use clear color\/mood labels.\n- Consistent and concise behavioral rules with always-on dollar cost and real-world equivalents.\n- No code or implementation changes; documentation and explained output improved for all users.",
        "changelogSource": "user",
        "createdAt": 1773830049910,
        "parsed": {
            "clawdis": {
                "requires": {
                    "bins": [
                        "nvidia-smi",
                        "python"
                    ]
                }
            }
        },
        "version": "2.5.0"
    },
    "owner": {
        "_creationTime": 0,
        "_id": "publishers:missing",
        "displayName": "hongping-zh",
        "handle": "hongping-zh",
        "image": "https:\/\/avatars.githubusercontent.com\/u\/133202211?v=4",
        "kind": "user",
        "linkedUserId": "kn79sspnm92zk13a4ddetsaz1h819bmc"
    },
    "ownerHandle": "hongping-zh",
    "skill": {
        "_creationTime": 1771229518434,
        "_id": "kd7d2xb81zga8xbfr8h54erp6d818b1d",
        "badges": [],
        "createdAt": 1771229518434,
        "displayName": "EcoCompute — LLM Energy Efficiency Advisor",
        "latestVersionId": "k978rzgpp4mx6a9ja481e045ah835rrj",
        "ownerUserId": "kn79sspnm92zk13a4ddetsaz1h819bmc",
        "slug": "ecocompute",
        "stats": {
            "comments": 0,
            "downloads": 648,
            "installsAllTime": 2,
            "installsCurrent": 1,
            "stars": 0,
            "versions": 8
        },
        "summary": "EcoLobster energy advisor: save 30-701% wasted GPU energy. RTX 5090 five-precision benchmarks (FP16\/FP8\/NF4\/INT8-mixed\/INT8-pure), 113+ measurements, dollar-...",
        "tags": {
            "ai-ml": "k978rzgpp4mx6a9ja481e045ah835rrj",
            "carbon-footprint": "k978rzgpp4mx6a9ja481e045ah835rrj",
            "energy-efficiency": "k978rzgpp4mx6a9ja481e045ah835rrj",
            "gpu": "k978rzgpp4mx6a9ja481e045ah835rrj",
            "gpu-optimization": "k97b2byqwdjbrvjf400cn3drf181atvd",
            "green-ai": "k978rzgpp4mx6a9ja481e045ah835rrj",
            "inference": "k978rzgpp4mx6a9ja481e045ah835rrj",
            "latai-ml": "k97enennavc4qcsp751djtr64d82m18q",
            "latest": "k978rzgpp4mx6a9ja481e045ah835rrj",
            "llm": "k978rzgpp4mx6a9ja481e045ah835rrj",
            "ml": "k972txnwx8eqmsa7kvyvn3jnrd835wax",
            "optimization": "k978rzgpp4mx6a9ja481e045ah835rrj",
            "quantization": "k978rzgpp4mx6a9ja481e045ah835rrj",
            "science": "k978rzgpp4mx6a9ja481e045ah835rrj",
            "sustainability": "k978mhsnh7b1p22neqbpqe9qmx82q3k8",
            "sustainabilityest": "k978rzgpp4mx6a9ja481e045ah835rrj",
            "utility": "k978rzgpp4mx6a9ja481e045ah835rrj"
        },
        "updatedAt": 1773830522747
    }
}