Web Analytics

Web Analytics Skill

This skill allows the agent to pull and analyze traffic data from Google and Bing to provide deep SEO insights.

Environment Preparation

The necessary scripts are located in the scripts/ directory relative to this SKILL.md file. Ensure the following dependencies are installed:

python3 -m pip install -r scripts/gsc-requirements.txt

Credentials Required & How to Obtain Them

Before executing this skill, ensure the environment is configured. If the user does not have the required credentials, the Agent should instruct the user to obtain them using the following steps:

1. Google OAuth Client Secret (client_secret.json)

The agent requires a Desktop OAuth 2.0 Client ID to access Google APIs. Instructions for the User:

1. Go to the Google Cloud Console.
2. Create a new project or select an existing one.
3. Navigate to APIs & Services > Library and enable Google Search Console API and Google Analytics Data API.
4. Navigate to APIs & Services > OAuth consent screen and configure it (you can set user type to "External" and add your own email as a test user).
5. Navigate to APIs & Services > Credentials. Click Create Credentials > OAuth client ID.
6. Select Desktop app as the application type.
7. Click Create, then download the JSON file. Rename it to client_secret.json and place it in the scripts/ directory of this skill.

2. Google OAuth Tokens (token.json, google_analytics_token.json)

These are generated automatically by the script.

• Agent Instruction: If the script output says Opening browser for authorization, tell the user to check their computer for a newly opened browser window and complete the Google OAuth login. The script will automatically save the tokens locally once login is successful.

3. Bing API Key

Instructions for the User:

1. Go to Bing Webmaster Tools.
2. Select your verified website.
3. Click on the Settings gear icon in the top right corner.
4. Go to API Access -> API Key.
5. Click Generate API Key (or copy the existing one).
6. Paste it into the .env file as BING_API_KEY=your_key_here.

Execution Steps

1. Gather Google Search Console (GSC) Data

Run the GSC analysis script to get clicks, impressions, CTR, and average position:

cd scripts && python3 analyze_gsc.py

2. Gather Google Analytics 4 (GA4) Data

Run the GA4 script to analyze user sessions, traffic sources, and pageviews:

cd scripts && python3 ga4_both.py

3. Gather Bing Webmaster Tools Data

Run the Bing script to compare Bing search performance against Google:

export BING_API_KEY=$(grep BING_API_KEY ../../.env | cut -d '=' -f2)
cd scripts && python3 bing_webmaster.py

4. Synthesize Insights

Analyze the combined output and report:

1. Trend Analysis: Is overall traffic growing or dropping based on the 14-day view?
2. Platform Ratio: What is the proportion of Bing traffic compared to Google?
3. Keyword & Page Opportunities: Highlight keywords with high impressions but low CTR, or pages performing well on Bing but not Google.

Provide the final summary to the user using clean Markdown.