A data-driven diagnostic tool designed to analyze WeChat Official Account performance backend data, align target audience perceptions with actual user metrics, and pinpoint tailored benchmarking accounts.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install wechat-account-audit
2. Manual Installation
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
3. Prompt Installation
Copy this prompt to OpenClaw to install it automatically.
Help me install wechat-account-audit using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Prefer to download?
Get the raw skill files in a ZIP archive.
What is WeChat Account Audit?
The WeChat Account Audit skill addresses a critical pain point for content creators: the gap between perceived target audiences and actual data-proven readership. By executing a strict six-phase diagnostic methodology, this asset eliminates guesswork from WeChat account management, allowing growth managers to transition away from copying high-level surface mechanics and shift toward high-impact, data-driven positioning.
Integrating closely with supplementary processing modules, this Openclaw Skills repository ingests standard platform data outputs like backend tendency spreadsheets and demographic profile screenshots. The system then delivers an actionable, structured markdown report containing content revision directives, category-level visibility metrics, and vetted competitor benchmarks scored objectively on exact audience overlap.
WeChat Account Audit Use Cases
- Content direction correction when subscriber growth slows or organic reach plateaus
- Strategic repositioning requiring historical data validation and structured performance metrics
- Early-stage account cold starts needing precise demographic profiling and niche identification
- Identifying highly compatible benchmarking accounts for creative imitation and targeted growth hacking
How WeChat Account Audit Works
- Data Collection: Gather core administrative source documents, including the backend Tendency Excel and target audience profile screenshots directly from the WeChat Official Account Creator Platform.
- Article Classification: Parse structural spreadsheet entries and safely prompt the operator to supply short categorical tags, preserving individual intuitive workflow taxonomy.
- Cross-Analysis: Perform multidimensional programmatic matrix computations matching content category against reader volume, channel referral origin breakdowns, and timelines.
- User Profile Verification: Generate an explicit comparison matrix mapping out targeted user expectations versus empirical user traits to expose critical audience misalignments.
- Competitor Benchmarking: Source alternative matching creators using the search stack and score relevant accounts on a 1-to-5 scale based on true demographic overlapping.
- Structured Reporting Generation: Synthesize the collected insights into a cleanly formatted audit document based on pre-configured layout templates.
WeChat Account Audit Setup
Prerequisites
Ensure Python 3.x is installed along with the necessary spreadsheet analysis library dependencies.
Running the Parser
To parse your exported WeChat tendency Excel file and generate structured JSON outputs, execute the processing script:
python3 scripts/parse_tendency.py <path_to_excel_file> [--output result.json]
WeChat Account Audit Data Schema & Taxonomy
Input Formats
- Tendency Excel Spreadsheet: Platform-standard report containing historical readership, distribution source breakdown, updates, and shares.
- Demographic Screenshots: Image files demonstrating gender, age brackets, geographic spreads, and system configurations.
Generated Outputs
The scripts/parse_tendency.py utility outputs structured data adhering to the schema below:
| Field Name | Data Type | Description |
|---|---|---|
title |
String | Title of the audited article |
publish_date |
String (YYYY-MM-DD) | Calendar publication date |
reads |
Integer | Total page view count |
shares |
Integer | Total forward or share operations |
likes |
Integer | Total standard appreciation likes |
favorites |
Integer | Total user bookmarks |
channel_breakdown |
Object | Map tracking views from direct messages, Moments, or recommendations |
source |
String | Primary initial acquisition channel |
WeChat Account Audit Advanced Features
- Outlier exclusion automation to safely insulate core benchmarks from content anomalies
- Cross-skill interoperability designed to query secondary accounts via search systems
- Strict data isolation protecting early drafts or legacy programmatic materials
- Structured formatting hooks providing unified presentation layers using custom-styled components
SKILL.md
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