cf-analytics

Solid

Track content quality scores, pipeline timing, and compliance trends with insights and alerts.

AI & Automation 17 stars 6 forks Updated today MIT

Install

View on GitHub

Quality Score: 83/100

Stars 20%
42
Recency 20%
100
Frontmatter 20%
70
Documentation 15%
100
Issue Health 10%
50
License 10%
100
Description 5%
100

Skill Content

# Content Analytics Dashboard Track ContentForge production quality, pipeline timing, brand-specific patterns, and compliance trends over configurable time periods with automated insights and alert flags. ## When to Use Use `/contentforge:cf-analytics` when you need: - **Quality trend visibility** — Are scores improving or declining over time? - **Pipeline performance audit** — Which phases are slowest? Where are bottlenecks? - **Brand comparison** — Which brands consistently score highest/lowest? - **Content type analysis** — Are articles scoring better than whitepapers? - **Compliance monitoring** — Citation rates, brand adherence, loop frequency - **Capacity planning** — Average throughput for estimating batch timelines **For real-time batch monitoring**, use the Progress Tracker (built into `/contentforge:batch-process`). **For individual content production**, use [`/contentforge:create-content`](../../commands/create-content.md). ## What This Command Does Loads historical production data from the brand's configured tracking backend (Google Sheets, Airtable, or local — see `tracking.backend` in the brand profile), calculates aggregate metrics across configurable dimensions, identifies statistical outliers and concerning trends, generates an ASCII dashboard with actionable recommendations, and flags alerts when performance degrades. **Process Flow:** 1. **Load Data** — Read tracking records from the brand's tracking backend (Google Sheets / Airtable / local JSON) 2...

Details

Author
indranilbanerjee
Repository
indranilbanerjee/contentforge
Created
5 months ago
Last Updated
today
Language
Python
License
MIT

Integrates with

Similar Skills

Semantically similar based on skill content — not just same category