contentscoring
🥈SilverA Python-based content scoring model for marketing teams that analyzes performance of videos, blogs, and non-gated content to surface what works and what doesn't.
400Updated 1mo ago
Intermediate30min to implementmarketing
Saves ~30 min per use
Quick InstallView Source
git clone https://github.com/rh-marketingops/contentscoring.gitWorks with:
Claude
Overview
About This Skill
The contentscoring skill provides business logic for calculating and maintaining marketing content scores. Built by Red Hat's marketing operations team, it was designed to analyze the performance of videos, blogs, and non-gated content assets. The model surfaces insights about which content performs well or poorly, helping marketing teams prioritize creation and assessment efforts. It is intentionally designed as an analytical guide rather than a prescriptive tool, summarizing performance signals and prompting deeper investigation into the reasoning behind a specific piece's results. Marketing operations analysts and content strategists benefit most from this skill.
Use Cases
Score blog post performance to identify high- and low-performing content
Evaluate video content effectiveness using consistent scoring logic
Assess non-gated content assets to guide future content creation priorities
Maintain a running content performance score across a marketing content library
Tags
Setup & Installation
Quick Install
No install command available. Check the GitHub repository for manual installation instructions.
Alternative Install (Git Clone)
git clone https://github.com/rh-marketingops/contentscoringRequirements
- Claude Code or compatible AI agent
- Works with: Claude
Quick Start Guide
1
Install the Skill
Copy the install command above and run it in your terminal.
2
Open Your AI Agent
Launch Claude Code, Cursor, or your preferred AI coding agent.
3
Try It Out
Use the prompt template or examples below to test the skill.
4
Customize
Adapt the skill to your specific use case and workflow.
Usage Examples
Prompt Template
Create a content scoring system for [COMPANY] in the [INDUSTRY] sector. The score should evaluate content based on engagement metrics (e.g., time on page, bounce rate, shares), SEO performance (e.g., keyword rankings, backlinks), and conversion rates (e.g., click-through, lead generation). Provide a weighted scoring model and suggest improvements for low-scoring content.
Example Output
# Content Scoring System for [COMPANY] in [INDUSTRY] ## Scoring Model | Metric | Weight | Score Range | Weighted Score | |----------------------|--------|------------|----------------| | Engagement Metrics | 40% | 0-100 | [Engagement Score] * 0.4 | | SEO Performance | 30% | 0-100 | [SEO Score] * 0.3 | | Conversion Rates | 30% | 0-100 | [Conversion Score] * 0.3 | ## Suggested Improvements - **Engagement Metrics**: Increase interactivity by adding quizzes or polls to the content. - **SEO Performance**: Optimize meta descriptions and headers with target keywords. - **Conversion Rates**: Include clear and compelling calls-to-action (CTAs).
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