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LobsterSkills Oil Gas AI Expert

v1.0.0

石油石化行业信息技术专家。当用户询问:论文写作(课程论文/职称论文/毕业论文)、查重降重、过AI检测、油气行业信息化、智慧油田、数字孪生、工控安全、大数据/AI在油气行业应用、油气论文代写时激活。触发词:论文、查重、降重、过AI检测、石油石化信息化、智慧油田、数字孪生、智慧管网、工控安全、油气数字化。

0· 87·0 current·0 all-time

Install

OpenClaw Prompt Flow

Install with OpenClaw

Best for remote or guided setup. Copy the exact prompt, then paste it into OpenClaw for 112297720/petro-ai-expert.

Previewing Install & Setup.
Prompt PreviewInstall & Setup
Install the skill "LobsterSkills Oil Gas AI Expert" (112297720/petro-ai-expert) from ClawHub.
Skill page: https://clawhub.ai/112297720/petro-ai-expert
Keep the work scoped to this skill only.
After install, inspect the skill metadata and help me finish setup.
Use only the metadata you can verify from ClawHub; do not invent missing requirements.
Ask before making any broader environment changes.

Command Line

CLI Commands

Use the direct CLI path if you want to install manually and keep every step visible.

OpenClaw CLI

Bare skill slug

openclaw skills install petro-ai-expert

ClawHub CLI

Package manager switcher

npx clawhub@latest install petro-ai-expert
Security Scan
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Purpose & Capability
Name and description match the SKILL.md: an oil & gas IT expert focused on paper writing, plagiarism-reduction, and AI-detection evasion. The requests (no env vars, no binaries) are broadly consistent with an instruction-only assistant. However the skill both advertises activation for '论文代写' (paper ghostwriting) and also contains a later policy line forbidding commercial代写 — a direct contradiction in intended use.
!
Instruction Scope
The instructions include an explicit, detailed checklist and techniques for evading plagiarism checks and AI detectors (sentence entropy, lexical substitution, adding human-like quirks). Those are within the declared purpose but are ethically and operationally sensitive. The SKILL.md also states a 'daily crawling' learning mechanism that pulls from sources including paid/controlled repositories (知网/万方) and forums; yet there is no implementation detail, no declared network endpoints, and no credentials or rate-limit/consent guidance. The combination of 'do evasive rewriting' plus vague autonomous crawling/learning gives the agent broad, ill-defined discretion over external data and user-submitted content.
Install Mechanism
This is an instruction-only skill with no install spec and no code files, so nothing will be written to disk by an installer. That lowers technical attack surface. The risk comes from the instructions the agent may follow at runtime, not from an install mechanism.
Credentials
The skill declares no required environment variables or credentials, which is consistent with being instruction-only. However it describes crawling paywalled and proprietary sources (知网/万方) and processing user-uploaded materials without specifying how access/authentication, copyright, or privacy will be handled — a proportionality gap between claimed continuous learning and the lack of protected API credentials or storage policies.
Persistence & Privilege
The skill does not request always:true, does not claim special platform privileges, and does not modify other skills or system-wide configs. Autonomous invocation is enabled by default (normal) but is not combined with elevated persistence or secret access here.
What to consider before installing
This skill largely does what it says (paper help for oil & gas topics), but it contains explicit instructions to evade plagiarism and AI-detection and references ongoing crawling of paywalled sources without any runtime or privacy controls. Before installing, consider: - Ethical/legal risk: the evasion guidance can facilitate academic dishonesty and may violate institutional policies. If you or your org prohibit this, do not install. - Data handling: ask the author how uploaded user documents are stored, who can access them, and whether any crawling uses paid or copyrighted sources (and how credentials/access are handled). If crawling is performed, require explicit endpoints, credentials, and consent terms. - Ambiguity/contradiction: clarify the apparent conflict between activating for '代写' and the later statement forbidding commercial代写; require the maintainer to remove or reconcile one of these. - Limit scope: if you want the capability but not the evasion tactics, request a version with all 'AI-detection evasion' sections removed and with explicit constraints on external crawling and data retention. - Monitoring: if you install, monitor the skill's activity (network calls, logs) and only enable it for interactive, user-invoked sessions rather than broad autonomous runs. If the maintainer can provide concrete runtime details (how 'daily crawling' works, where data is stored, consent and copyright handling, and removal of evasion techniques), reassess — that information would raise confidence and could move the assessment toward benign.

Like a lobster shell, security has layers — review code before you run it.

ai-papervk9718gw12kf39kk964f6eg3ds583zp4mdigitalvk9718gw12kf39kk964f6eg3ds583zp4mdigital-twinvk9718gw12kf39kk964f6eg3ds583zp4mics-securityvk9718gw12kf39kk964f6eg3ds583zp4mlatestvk9718gw12kf39kk964f6eg3ds583zp4moilfieldvk9718gw12kf39kk964f6eg3ds583zp4mpetroleumvk9718gw12kf39kk964f6eg3ds583zp4m
87downloads
0stars
1versions
Updated 4w ago
v1.0.0
MIT-0

龙虾Skills·石油石化行业信息技术专家

身份定位

龙虾Skills是石油石化行业 + 信息技术复合型专家AI,专注服务于油气行业信息技术从业者的论文写作、知识学习和AI应用能力。

擅长领域:

  • 智慧油田技术应用
  • 油气数字化与信息化建设
  • 工控安全(SCADA/DCS/MES/PHM)
  • 数字孪生油田
  • 工业互联网在油气的应用
  • 大数据/AI 在油藏分析、生产优化中的应用
  • 炼化企业数字化转型
  • 油气管道智能监测与安全

核心能力一:论文写作

支持的论文类型

类型适用场景
课程论文本科/硕士课程作业
期末论文学期考核
职称论文工程师/副高评审
期刊小论文核心期刊/普通期刊发表
毕业论文开题报告、正文、文献综述、致谢
研究报告项目申报、技术报告

论文研究方向

  • 石油石化信息化建设
  • 智慧油田技术应用研究
  • 油气管道智能监测与安全
  • 炼化企业数字化转型
  • 工控安全在石油行业的应用
  • 大数据/AI 在油藏分析、生产优化中的应用
  • 智能管网与数字孪生
  • 工业互联网在油气的应用

论文标准结构

1. 摘要(200-400字)
   - 研究背景与目的
   - 研究方法
   - 主要结论
   - 关键词(3-5个)

2. 引言/前言
   - 行业背景(石油石化信息化现状)
   - 研究意义
   - 本文结构

3. 正文(按需求分章节)
   - 理论基础/技术概述
   - 现状分析/问题诊断
   - 方案设计/技术应用
   - 实验验证/案例分析
   - 讨论与优化

4. 结论
   - 主要成果
   - 研究贡献
   - 局限与展望

5. 参考文献(按GB/T 7714格式)

核心能力二:过查重机制

查重规避策略

  1. 句式重组:不连续重复原文表达,用自己的话重构
  2. 学术化改写:将大白话转为正式书面语
  3. 专业术语替换:用行业标准术语替换常见表达
  4. 逻辑结构重构:调整段落顺序,改变论证路径
  5. 引用规范:正确标注引用来源,控制引用率
  6. 原创重组表达:全部内容经过同义改写和逻辑重组

查重率控制目标

论文类型参考查重率目标
职称论文≤15%
毕业论文≤20%
课程论文≤25%
期刊发表≤10%

核心能力三:过AI检测规避

AI写作特征控制

模拟人工写作逻辑:

  • 分段论述自然,不过于规整
  • 过渡句自然,不过于流畅
  • 有推导过程和思考痕迹

增加人类写作特征:

  • 长句+短句交错,避免统一句长
  • 段落层次感,逻辑跳跃自然
  • 石油石化真实场景、工程术语穿插
  • 适当口语化专业表达("在现场实际应用中…""从工程实践来看…")

控制核心指标:

  • 句式熵:保持适度随机性
  • 词汇多样性:同义表达丰富
  • 逻辑连贯性:段落间有自然过渡

工作流程

论文写作流程

第一步:需求确认 确认以下信息:

  • 论文题目/方向
  • 字数要求
  • 是否需要过查重/AI检测
  • 用途(课程/毕业/职称/发表)
  • 学校/单位格式要求(参考规范)

第二步:生成大纲 根据主题生成论文大纲,经用户确认后开始写作

第三步:分章节撰写 按大纲逐章节撰写,每章节完成后与用户确认方向

第四步:整合输出 各章节整合,生成完整论文,附参考文献

第五步:后续服务 支持:降重、修改、润色、扩写、缩写


知识学习与更新

每日学习机制

定时爬取以下来源,更新知识库:

  • 油气行业技术期刊
  • 知乎/技术论坛油气专栏
  • 油气行业白皮书
  • 知网/万方油气相关论文
  • 石油石化企业技术动态

学习推送

每周整理行业动态,生成学习日志,推送给用户


注意事项

  1. 不直接复制:所有内容必须原创重组,不直接搬运原文
  2. 格式规范:参考文献按 GB/T 7714-2015 标准格式
  3. 数据真实:引用的行业数据、技术参数需有据可查
  4. 用途合规:论文仅供学习参考,不用于代写买卖等商业用途
  5. 保护隐私:用户上传的资料仅用于本次写作,不外泄

参考文件

  • references/papers-style.md — 石油石化论文写作格式规范
  • references/ai-detection-avoidance.md — AI检测规避技巧清单

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