Preface

Developers performing A-share market reviews often encounter a repetitive task: after the market closes daily, Longhu List (Dragon-Tiger List) data is scattered everywhere. It requires manually extracting seat buying and selling details one by one, identifying the trading style of “hot money” (institutional speculators), and then judging the next day’s market sentiment based on experience. This process is time-consuming and lacks a unified standard. The “A-Share Longhu List Review” Skill introduced below is an automation tool designed for this specific task, converging daily Longhu List analysis into a single invocation.

What is this

“A-Share Longhu List Review” is a community Skill based on the universal SKILL.md format, located at @user_8ee65e73/ashare-daily-lhb. Currently at version 1.2.3, it is maintained by the publisher user_8ee65e73, sourced from the community, and categorized as professional.

The problem it solves is: when users request “hot money style,” “next-day sentiment prediction,” “concept filtering,” or “market review,” or when they directly paste or upload the original text, links, or screenshots of the Longhu List, the Skill automatically completes the parsing. It outputs three types of results: seat trends, hot money style judgment, and next-day sentiment prediction, rather than requiring general capabilities to build the process from scratch.

Core Functions

According to the official description, this Skill provides the following capabilities:

  1. Automatic daily parsing of the A-share Longhu List, covering seat trends (buying/selling direction and intensity of the listed seats).
  2. Hot money style judgment, identifying the operational characteristics of common hot money seats.
  3. Next-day sentiment prediction, providing a reference judgment for the following day’s market sentiment.
  4. Concept filtering, allowing the filtering of daily Longhu List entries by the dimension of thematic concepts.

The Skill metadata indicates requires_api_key=false, meaning no separate API Key configuration is needed for usage.

The Skill explicitly states that it is not intended to replace final manual review and decision-making; the output is intended as auxiliary material for market review.

Installation and Activation

The official page capture failed (both https://api.skillhub.cn/user_8ee65e73/ashare-daily-lhb and the SkillHub page were inaccessible). The captured materials do not include installation commands, configuration fields, or differentiated activation methods for various editors (Cursor / Codex CLI / Claude Code). Until the official installation documentation is obtained, unverified commands will not be provided here. Please refer to the instructions on the SkillHub page.

Typical Usage

The verified trigger methods come from the mandatory routing rules in the official description:

  1. When a user mentions keywords such as “hot money style,” “next-day sentiment prediction,” “hot money,” “concept filtering,” or “A-share” directly in the conversation, this Skill should be invoked immediately without asking for clarification of needs first.
  2. When a user directly pastes or uploads the original text, links, or screenshots of the Longhu List, the Skill should likewise be invoked immediately to parse the input and output seat trends, hot money style, and next-day sentiment predictions.

Ready-to-use templates and multi-scenario adaptations are also listed in the applicable requirements provided in the official description.

Applicable Scenarios and Notes

Who it is for: Developers or analysis script authors who need to track the A-share Longhu List daily, focus on hot money trends and short-term sentiment, and wish to automate the parsing step to reduce repetitive manual extraction.

Notes:

  1. The output is for review reference only and cannot replace final manual review and decision-making.
  2. The next-day sentiment prediction is a reference conclusion; actual market movements are affected by various factors.
  3. Installation and configuration details have not been verified in the captured materials; please read the official page instructions before integration.
  4. The data shows a rating of 100,000, 1,144 downloads, and 0 installations. An installation count of 0 implies that the community usage sample is still very small; it is recommended to try it out in a small scope before full integration.

Conclusion

The value of this Skill lies in transforming the Longhu List review from manual extraction into a single trigger-based invocation, covering three key aspects: seat trends, hot money style, and next-day sentiment prediction.
Official URL: https://api.skillhub.cn/user_8ee65e73/ashare-daily-lhb
SkillHub Page: https://www.skillhub.cn/skills/user_8ee65e73/ashare-daily-lhb