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sungaoxiang-backend
sungaoxiang-backendCOMMUNITY
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evidence-wechat-chat-handler

Extract WeChat chat screenshots into grouped card_features by contact remark.

Updated Jul 20, 2025
Search Tags:#compliance#evidence#wechat#data-extraction#grouping#multi-image#card_features
One-click install
npx skills add https://github.com/sungaoxiang-backend/intelligent-evidence-platform --skill evidence-wechat-chat-handler
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: evidence-wechat-chat-handler
Source: https://github.com/sungaoxiang-backend/intelligent-evidence-platform/tree/main/app/agentic/skills/evidence-wechat-chat-handler
Command: npx skills add https://github.com/sungaoxiang-backend/intelligent-evidence-platform --skill evidence-wechat-chat-handler

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Processing multiple WeChat chat screenshots to identify and group by contact remarks, then generate structured card_features that summarize key information for evidence management.

Core Features & Use Cases

  • Group-by-contact: Cluster multi-image screenshots by WeChat remark names into a single card feature per contact.
  • Nested card features: Produce card_features with image sequences and sub_features that capture important details per group.
  • Modes: Default rule mode extracts predefined slots (欠款金额, 欠款合意, 催款记录); enhanced mode surfaces additional insights such as 还款态度分析 when present.

Quick Start

Process the provided WeChat chat screenshots to generate grouped card_features by contact.

Frequently Asked Questions about evidence-wechat-chat-handler

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I organize multiple WeChat chat screenshots into evidence by contact?▼

Grouping WeChat chat screenshots by contact is handled by clustering multi-image screenshots under WeChat remark names. This Skill automatically generates nested card features with image sequences and sub features to summarize key evidence details per contact.

What predefined slots are extracted from WeChat chat evidence for debt disputes?▼

Predefined slots extracted from WeChat chat evidence include 欠款金额, 欠款合意, and 催款记录. The default rule mode automatically fills these slots within the structured card features generated for each contact group.

Can I analyze repayment attitude from WeChat chat screenshots?▼

Analyzing repayment attitude from WeChat chat screenshots is supported through the enhanced mode. Beyond the default predefined slots, this mode surfaces additional insights such as 还款态度分析 when present in the multi-image evidence.

How does grouping multi-image WeChat evidence by contact remark name work?▼

Grouping multi-image WeChat evidence by contact remark name works by clustering all screenshots associated with the same WeChat remark into a single card feature. It produces nested feature structures containing image sequences and sub features suitable for evidence summaries.

What is the best way to structure WeChat chat screenshots for legal evidence summaries?▼

Structuring WeChat chat screenshots for legal evidence summaries is best done by generating grouped card features per contact. This approach enforces predefined slots like 欠款金额 and produces nested feature structures capturing important details for compliance and evidence workflows.

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