Report-gama for Openclaw

Report-gama is a professional market intelligence system that automates the generation of 15-chapter research reports with real-time data and PDF export capabilities.

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v1.0.0
Apr 6, 2026
0
509
0

Install & Download

1. ClawHub CLI

The fastest way to install a skill directly from the registry.

npx clawhub@latest install reportgama

2. Manual Installation

Copy the skill folder to one of these locations

Global
~/.openclaw/skills/
Workspace
<project>/skills/

Priority: Workspace > Local > Bundled

3. Prompt Installation

Copy this prompt to OpenClaw to install it automatically.

Help me install reportgama 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 Report-gama?

Report-gama is a sophisticated market research engine designed to provide granular insights into specific countries and product categories. By integrating Openclaw Skills, it automates the collection of multi-source data including news, competitor strategies, e-commerce pricing, and government tenders. This tool is particularly powerful for industries like medical devices, where regulatory and pricing data is critical.

The system synthesizes information from diverse sources such as Yandex, Google, and social platforms like Telegram and VK. It transforms raw data into a structured 15-chapter professional report, complete with charts and reliability ratings, making it a premier choice for those seeking actionable market intelligence through Openclaw Skills.

Report-gama Use Cases

  • Generating comprehensive market entry reports for medical equipment in international markets like Russia or Kazakhstan.
  • Tracking competitor product lines and pricing strategies across global e-commerce platforms such as Wildberries and Ozon.
  • Monitoring 30-day industry news cycles and policy changes to stay ahead of regulatory shifts.
  • Analyzing import and export trends using customs data and HS code mapping for specific goods.

How Report-gama Works

  1. Analyzes the user input to extract the target country, category, language, and research depth.
  2. Triggers concurrent data collection across 13 specialized modules including news monitoring, ad research, and customs scraping.
  3. Performs data cleaning and structural organization, assigning reliability scores (High, Medium, Low) to each data point.
  4. Synthesizes the gathered intelligence into a long-form Markdown report following a standard 15-chapter template.
  5. Generates visual data representations like market share pie charts and price distribution box plots using Matplotlib.
  6. Compiles the final deliverable into a professionally formatted PDF report for the end user.

Report-gama Setup

To utilize these Openclaw Skills, ensure you have python3 and pip3 installed on your system. Follow these steps to set up the environment:

# Install the required Python dependencies
pip3 install requests beautifulsoup4 lxml fake-useragent python-dateutil matplotlib reportlab pillow

# Run a standard market report generation
python3 scripts/master.py --country "Russia" --category "medical devices" --lang ru --pdf

Report-gama Data Schema & Taxonomy

The skill maintains a structured file hierarchy to ensure data integrity and ease of access:

Component Description
scripts/ Contains the execution logic for 13 modules like customs_data.py and news_monitor.py.
references/ Stores metadata libraries including HS codes and industry-specific keywords.
output/ The default directory for generated Markdown, HTML, and PDF reports.
config.py Centralized configuration for search engines and platform parameters.
_meta.json Skill metadata used for integration with other Openclaw Skills.

Report-gama Advanced Features

  • Multilingual keyword expansion that automatically translates search terms between English, Russian, and local languages.
  • High-concurrency execution allowing 13 different intelligence modules to run simultaneously for rapid report generation.
  • Automated data reliability grading that weights government and official sources higher than social media data.
  • Cross-validation logic that requires key data points to be verified by at least two independent sources before being marked as high-confidence.

SKILL.md


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