Highway Lifecycle
v1.0.1高速公路全生命周期智能化支持，涵盖规划设计、建设施工、运营管理、养护巡检四大阶段。使用当需要：(1) 桥梁/隧道设计图纸审查与规范符合性检查，(2) 交通事件检测与视频分析，(3) 道路病害识别与损害检测，(4) 隧道地质特征分析与围岩分级，(5) 多模态模型选型与评测指导，(6) 工程文档一致性审核。触发词：高...
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by@sxy799
MIT-0
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LicenseMIT-0 · Free to use, modify, and redistribute. No attribution required.
Security Scan
OpenClaw
Benign
high confidencePurpose & Capability
The name/description (planning, design review, event detection, damage detection, tunnel analysis, model selection) matches the included documentation and three utility scripts (evaluation, norm checking, road-damage reporting). One note: the skill recommends large vision/LLM models (Qwen3-VL-235B, InternVL-241B, GLM-4.5V etc.) and shows deployment examples, but does not declare any runtime dependencies or provide a deployment/install spec — this is reasonable for a guidance-oriented skill but means the user must supply model hosting/infrastructure separately.
Instruction Scope
SKILL.md and references focus on document review, image/video analysis, model evaluation and prompts. The runtime instructions and templates are narrowly scoped to the stated tasks (RAG/LLM-as-judge evaluation, metric calculation, file-based checks). There are no instructions to read unrelated system files, access credentials, or send data to unexpected external endpoints; curl examples point to localhost model servers for local deployment.
Install Mechanism
No install spec is provided (instruction-only with included Python scripts). That is the lowest-risk pattern: nothing will be downloaded or installed automatically by the skill. The included Python scripts are plain, self-contained utilities and do not perform network downloads or execute arbitrary remote code.
Credentials
The skill declares no required environment variables, no primary credential, and no config paths. The code does not reference external credentials or secrets. Model endpoints and GPU resource recommendations are documented but not requested as environment variables — users will need to provide/host models themselves if they want to run those workflows.
Persistence & Privilege
The skill does not request always:true and has no special persistence requirements. It will not modify other skills or system-wide settings based on the provided files/instructions.
Assessment
This skill appears coherent and documentation-rich, but review before use: (1) The scripts operate on files you supply — don't feed sensitive or regulated documents to external/remote models unless you control the endpoint. (2) The skill references large models and local server examples (vLLM, curl to localhost). It does not provide or install those models — you must host them and ensure adequate GPU/compute. (3) The Python scripts are readable and do not perform network calls or secret exfiltration, but always inspect and test scripts on non-sensitive sample data before running in production. (4) Keep your norms/knowledgebase up to date (SKILL.md notes that) and verify any automated decisions with domain experts for safety-critical engineering tasks.Like a lobster shell, security has layers — review code before you run it.
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License
MIT-0
Free to use, modify, and redistribute. No attribution required.