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Football Betting Analyzer

v1.3.1

足彩分析助手 - 提供足球比赛数据分析、赔率分析、投注建议。支持基本面分析(球队战绩、伤停、对战历史)、赔率面分析(亚盘、欧赔、凯利指数)、投注策略建议。当用户需要分析足球比赛、获取投注建议、查询球队数据时使用。

1· 231·0 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 shenmeng/shenmeng-football-betting-analyzer.

Previewing Install & Setup.
Prompt PreviewInstall & Setup
Install the skill "Football Betting Analyzer" (shenmeng/shenmeng-football-betting-analyzer) from ClawHub.
Skill page: https://clawhub.ai/shenmeng/shenmeng-football-betting-analyzer
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 shenmeng-football-betting-analyzer

ClawHub CLI

Package manager switcher

npx clawhub@latest install shenmeng-football-betting-analyzer
Security Scan
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Purpose & Capability
The skill's code implements the advertised betting/odds analysis functionality and calls public football/odds APIs, which is coherent. However, the package also integrates an external billing system (SkillPay) with a hard-coded BILLING_API_KEY in payment.py and meta.json declaring payment envs, while the registry metadata at the top reports no required env vars — this is inconsistent and not proportional to a pure analysis tool.
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Instruction Scope
SKILL.md describes the feature set and notes SkillPay billing, but does not clearly declare required environment variables. The code (payment.py) reads SKILLPAY_USER_ID from the environment and will call external billing endpoints; analyzer.py reads FOOTBALL_API_KEY from FOOTBALL_API_KEY env if present. There are instructions/paths (14_matches_recommendation.py inserts '~/.openclaw/workspace/skills/...') that assume access to local skill workspace. The billing logic can cause network requests involving the user's ID and will attempt to charge via skillpay.me — this behavior is not fully declared in the top-level requirements.
Install Mechanism
No install spec (instruction-only in registry) but the skill bundle includes Python code and a requirements.txt. There are no remote downloads or extract steps in an install script. Risk arises from the included code itself (it will run network calls when executed), but there is no installer that fetches arbitrary remote archives.
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Credentials
The bundle and _meta.json indicate payment integration that expects SKILLPAY_USER_ID and an API key, yet the registry declares no required env vars. Worse, payment.py contains a hard-coded billing API key (BILLING_API_KEY) embedded in source — exposing a credential and granting the skill immediate ability to call the billing API. The credential usage and the sending of user_id to the billing endpoint are not justified solely by analytics functionality and are disproportionate unless the user explicitly consents to billing.
Persistence & Privilege
The skill does not request always:true, does not modify other skills, and does not request unusual system-wide privileges. It writes analysis outputs to a local outputs/ directory under the skill, which is expected for a local analyzer.
Scan Findings in Context
[hardcoded-secret:skillpay_billing_key] unexpected: payment.py contains a hard-coded BILLING_API_KEY value. A billing integration normally would use a server-side secret or require an operator-provided env var; embedding a secret in client-side skill code is a security and privacy concern.
What to consider before installing
What to consider before installing or running this skill: - The code includes an integrated billing system (SkillPay) that will call https://skillpay.me and attempt to charge users. The billing key is embedded in the code and the skill reads SKILLPAY_USER_ID from your environment — be careful: your user_id would be sent to the billing endpoint and a charge attempted. If you do not want any automatic billing or external charge attempts, do not run this skill. - The registry metadata and SKILL.md do not clearly declare the environment variables required for billing; ask the publisher to document required env vars and to remove any hard-coded keys. A proper design would require you to supply your own billing credentials (or have charges mediated by the platform), not ship with a secret in plain text. - If you still want to use the functionality: inspect payment.py and consider removing or disabling billing calls before running, or run the skill in a tightly sandboxed environment (no network) while you audit it. Prefer running analyzer.py with network disabled or with only the data API keys you control. - For privacy and financial safety: confirm who operates the skillpay.me endpoint and where funds go. Request proof the embedded key is intended for public use (if any) and ask for a safer implementation that uses server-side billing or explicit, documented prompts and consent before charging. - Additional technical notes: 14_matches_recommendation.py modifies sys.path to a user-specific workspace path — harmless but unusual and brittle. The skill uses external APIs (API-Football) and will read FOOTBALL_API_KEY if set; supply only keys you control. If you are not comfortable with potential automatic billing or with the hard-coded credential being present, do not install or run this skill. If you must use it, run it offline/locally after removing or stubbing out payment.py, or request a revised release that removes embedded secrets and clearly documents required environment variables and billing behavior.

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

Runtime requirements

Clawdis
latestvk978tv38jn2eta0hdtcgf0vf6983r1kn
231downloads
1stars
3versions
Updated 1mo ago
v1.3.1
MIT-0

Football Betting Analyzer 足彩分析助手

💰 本 Skill 已接入 SkillPay 付费系统

  • 每次调用费用:0.01 USDT
  • 支付方式:BNB Chain USDT
  • 请先确保账户有足够余额

专业的足球比赛数据分析和投注决策支持工具。

核心能力

  1. 基本面分析 — 球队战绩、伤停名单、主客场表现
  2. 赔率面分析 — 亚盘、欧赔、凯利指数、赔率变化趋势
  3. 历史数据 — 对战记录、近期状态、进球/失球统计
  4. 投注建议 — 胜平负预测、让球分析、大小球建议
  5. 资金管理 — 投注比例、风险控制、组合方案

适用场景

场景示例
赛前分析"分析今晚曼联vs利物浦的比赛"
赔率解读"这场比赛亚盘怎么看?"
投注建议"这场推荐怎么买?"
串关方案"今天有什么稳胆可以串?"
球队查询"曼城最近状态怎么样?"
联赛分析"英超争冠形势如何?"

分析维度

1. 基本面 (Fundamentals)

  • 联赛排名与积分差距
  • 近期5/10场比赛战绩
  • 主客场表现差异
  • 伤停名单影响评估
  • 战意分析(争冠/保级/欧战资格)
  • 历史对战记录

2. 赔率面 (Odds Analysis)

  • 亚盘: 初盘/即时盘、水位变化、盘口升降
  • 欧赔: 胜平负赔率、凯利指数、返还率
  • 大小球: 盘口、水位分析
  • 赔率趋势: 机构倾向判断

3. 数据模型

  • 预期进球 (xG)
  • 控球率与射门效率
  • 进攻/防守效率指数
  • 价值投注识别

使用方法

单场比赛分析

分析 [球队A] vs [球队B] 的比赛

赔率查询

查询 [比赛] 的亚盘/欧赔

投注建议

这场比赛推荐怎么买?

多场比赛对比

对比今天几场比赛的投注价值

数据来源

  • 免费API: API-Football、Football-Data.org
  • 赔率数据: OddsAPI、各博彩公司公开赔率
  • 新闻资讯: 球队官网、体育媒体

输出格式

分析报告包含:

  1. 比赛基本信息
  2. 基本面评估(★☆☆☆☆)
  3. 赔率解读
  4. 综合推荐
  5. 风险提示

注意事项

⚠️ 免责声明:

  • 本工具仅供数据分析参考,不构成投注建议
  • 足球比赛具有不确定性,请理性购彩
  • 请遵守当地法律法规,合法参与彩票活动

技术栈

  • Python 3.8+
  • 数据获取: requests / aiohttp
  • 数据分析: pandas / numpy
  • 可视化: matplotlib (可选)

文件结构

football-betting-analyzer/
├── SKILL.md                 # 本文件
├── config.json             # 配置信息
├── analyzer.py             # 主分析脚本
├── data_fetcher.py         # 数据获取模块
├── odds_analyzer.py        # 赔率分析模块
└── utils.py                # 工具函数

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