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在 OpenClaw 中安装
/install gbabyzs-sentiment-analysis
功能描述
Analyze social media sentiment related to stocks, providing sentiment scores, trend changes, discussion heat, and bot detection.
使用说明 (SKILL.md)
Sentiment Analysis - 情绪分析工具
功能说明
分析股票相关社交媒体情绪，包括股吧、雪球评论。
核心功能
情绪指标
- 情绪指数 (0-100)
- 看涨/看跌比例
- 情绪趋势变化
热度分析
- 讨论热度
- 关注度变化
- 舆情传播路径
水军识别
- 异常评论检测
- 机器人账号识别
- 真实情绪过滤
使用示例
from sentiment_analysis import analyze_stock_sentiment
# 分析情绪
sentiment = analyze_stock_sentiment(stock_code="300308")
安装依赖
pip install akshare pandas numpy jieba snownlp
安全使用建议
This package appears to be a stub: it documents crawling stock-discussion sites and bot-detection but the shipped code only returns simulated results and misses an exported function listed in skill.json. Before installing or using it, ask the author for a complete implementation or an explicit statement that this is a prototype. If you still want to run it, do not rely on its outputs for decisions (especially trading). Be cautious about running the pip installs in a production environment — consider using a sandbox or virtual environment, inspect third-party packages (e.g., akshare) yourself, and verify any network activity if/when the real scraping code is provided.
功能分析
Type: OpenClaw Skill
Name: gbabyzs-sentiment-analysis
Version: 1.0.0
The skill bundle is a placeholder for a stock sentiment analysis tool. The code in sentiment_analysis.py currently returns mock data using numpy and does not perform any actual web scraping or sensitive data access. There are no signs of malicious intent, data exfiltration, or prompt injection in SKILL.md or the Python logic.
能力评估
Purpose & Capability
The skill claims crawling股吧/雪球 comments, sentiment scoring, trend analysis, and bot detection, and lists dependencies (akshare, jieba, snownlp) appropriate for that purpose. However, the main Python file contains only a placeholder analyze_stock_sentiment that returns simulated random values and does not perform any scraping, NLP, or bot detection. The skill.json also claims to export calculate_sentiment_index which is not implemented. These inconsistencies mean the package does not actually deliver the stated capabilities.
Instruction Scope
SKILL.md describes the intended functionality and shows a usage example, and instructs the user to pip install akshare, pandas, numpy, jieba, snownlp. It does not direct the agent to read unrelated system files or credentials. However, the docs promise crawling and analysis while the code is a stub — the runtime instructions therefore over-promise relative to the actual implementation.
Install Mechanism
There is no install spec; this is instruction-only and asks users to pip install standard Python packages. That is a common pattern. There are no downloads from arbitrary URLs or archive extraction steps in the package itself.
Credentials
The skill requests no environment variables, credentials, or config paths. The declared dependencies are plausible for a sentiment analysis tool; no unrelated secrets are requested.
Persistence & Privilege
The skill does not request elevated persistence ('always' is false) and does not modify other skills or system-wide agent settings. It remains user-invocable and can be invoked autonomously per platform defaults (no additional privilege requested).
如何使用
- 确保已安装 OpenClaw（本地或 Docker 部署）
- 在对话框中输入安装命令：
/install gbabyzs-sentiment-analysis - 安装完成后，直接呼叫该 Skill 的名称或使用
/gbabyzs-sentiment-analysis触发 - 根据 Skill 的参数说明提供必要输入，即可获得结构化输出
版本历史
v1.0.0
Initial release: 股吧/雪球评论情感分析工具
元数据
常见问题
Sentiment Analysis 是什么？
Analyze social media sentiment related to stocks, providing sentiment scores, trend changes, discussion heat, and bot detection. 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件，目前累计下载 371 次。
如何安装 Sentiment Analysis？
在 OpenClaw 或 Claude Code 对话框中运行命令「/install gbabyzs-sentiment-analysis」即可一键安装，无需额外配置。
Sentiment Analysis 是免费的吗？
是的，Sentiment Analysis 完全免费，采用 MIT-0 许可证，可自由下载、安装和使用。
Sentiment Analysis 支持哪些平台？
Sentiment Analysis 跨平台运行，可在任意部署了 OpenClaw / Claude Code 的环境中使用（cross-platform）。
谁开发了 Sentiment Analysis？
由 GBABYZS（@gbabyzs）开发并维护，当前版本 v1.0.0。
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