Evaluate WeChat Mini Program concepts instantly with automated market research, WeChat Index analysis, and professional HTML feasibility reports.
The fastest way to install a skill directly from the registry.
npx clawhub@latest install miniprogram-decision
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
Copy this prompt to OpenClaw to install it automatically.
Help me install miniprogram-decision using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Get the raw skill files in a ZIP archive.
The miniprogram-decision skill is an intelligent decision-making assistant tailored for developers, product managers, and startups looking to launch applications within the WeChat ecosystem. By simply providing a product name and direction, this agent automatically conducts comprehensive market research, evaluates search popularity trends, performs competitor landscape analysis, and assesses monetization viability. Leveraging Openclaw Skills, it completely automates the tedious early-stage product validation phase, ensuring you save development resources before writing code.
Built to execute high-performance web search and fetching capabilities, the skill systematically evaluates industry market sizes, growth trends, traffic potentials, business models, and technical requirements. Users receive action-oriented strategic insights, suggested technical stacks, cost estimations, and warning flags regarding strict WeChat auditing guidelines. It is an indispensable asset for evaluating frontend-web-dev initiatives efficiently.
Ensure Python is installed on your local system, and configure your agent with Openclaw Skills execution permissions.
To generate feasibility reports programmatically, invoke the generator script from your shell:
python ./scripts/report_generator.py \
--name "Your Product Name" \
--direction "Brief Description/Direction" \
--output "feasibility_report.html" \
--wechat-index '{"score": 80, "trend": "rising", "detail": "..."}' \
--competitors '{"count": 12, "top3": [], "detail": "..."}' \
--industry '{"market_size": "...", "growth": "...", "detail": "..."}' \
--business-model '{"recommend": [], "detail": "..."}' \
--promotion '{"strategies": [], "detail": "..."}' \
--development '{"tech_stack": "uni-app", "cost": "...", "tips": [], "detail": "..."}'
Alternatively, import and run the module inside your Python environment:
import sys
sys.path.insert(0, './scripts')
from report_generator import generate_report
data = {
"name": "Fishing Community",
"direction": "Social platform for fishing enthusiasts",
"wechat_index": {"score": 75, "trend": "rising", "detail": "WeChat index showing 30% YoY growth"},
"competitors": {"count": 45, "top3": [], "detail": "Fragmented competitive landscape"},
"industry": {"market_size": "Medium", "growth": "15%", "detail": "Steady expansion"},
"business_model": {"recommend": ["Ads", "SaaS"], "detail": "Dual-revenue strategy recommended"},
"promotion": {"strategies": ["KOL partnerships", "WeChat groups"], "detail": "Focus on organic social loops"},
"development": {"tech_stack": "Taro / Cloud Development", "cost": "Low", "tips": ["Verify registration certificates early"], "detail": "Low technical complexity but high policy sensitivity"}
}
html = generate_report(data)
with open('report.html', 'w', encoding='utf-8') as f:
f.write(html)
The decision report is scored out of 100 points based on a weighted multi-dimensional model:
| Dimension | Weight | Evaluation Criteria |
|---|---|---|
| WeChat Popularity (微信热度) | 25% | WeChat index search volumes and core keyword popularity trends. |
| Competitor Landscape (竞争格局) | 20% | Number of direct/indirect competitor mini-programs and top player dominance. |
| Market Potential (市场前景) | 20% | Industry overall market size, annual compound growth rate, and policy climate. |
| Monetization (变现能力) | 15% | Clarity of the revenue model and average revenue per user (ARPU) potential. |
| Development Feasibility (开发可行性) | 10% | Tech stack complexity, estimated development cost, and WeChat audit policy risks. |
| Traffic Acquisition (流量获取) | 10% | Organic search visibility, WeChat SEO opportunities, and viral loop potential. |
Loading
An interactive discovery skill that interviews users to map out, structure, and document complex workflows before any automation or building begins.

An AI coding agent skill designed to generate polished, self-contained HTML slide decks complete with embedded CSS and responsive, keyboard-navigable slide transitions.

A dedicated text editing utility that rewrites stiff, robotic, or AI-generated copy into natural, credible, and context-aware human writing.

An advanced fact-checking and claim verification skill for AI agents to review drafts, articles, and product copy before publication.

A live, read-only lookup skill to verify Australian businesses, ABNs, ACNs, and GST registration status directly via the official Australian Business Register.

An AI-powered nutrition consultant that simplifies meal logging and dietary analysis using natural language and the Chinese Dietary Guidelines (DRIs 2024).








































