blog-decay

Detect quarter-over-quarter content decay by comparing Google Search Console page exports.

1|Updated Dec 24, 2021
One-click install
npx skills add https://github.com/arthur-fontaine/arthurfontaine.fr --skill blog-decay-arthur-fontaine
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: blog-decay
Source: https://github.com/arthur-fontaine/arthurfontaine.fr/tree/main/.agents/skills/blog-decay
Command: npx skills add https://github.com/arthur-fontaine/arthurfontaine.fr --skill blog-decay-arthur-fontaine

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) components.

What problem does it solve? Blog posts lose search traffic over time, but spotting which pages are declining requires manually comparing Google Search Console exports across periods. This Skill automates that comparison, flags pages with significant quarter-over-quarter drops, and recommends whether to refresh, consolidate, prune, or investigate each page. ## Core Features & Use Cases - Decay Detection: Compares current and previous GSC page exports and flags pages declining by 20% or more, with severity tiers (warning, high, critical). - Action Recommendations: Suggests refresh/update, query-shift investigation, consolidate/redirect, or prune actions based on the decline pattern. - Dropped Page Validation: Identifies pages missing from the current export and marks them as needs_validation until filters, row limits, and URL inspection are confirmed. - Use Case: A content marketer exports two quarters of GSC page data as JSON, runs the analyzer, and receives a markdown report listing declining posts with prioritized refresh actions. ## Quick Start Ask the assistant to run blog decay analysis on your current and previous GSC JSON exports to find pages with quarter-over-quarter traffic drops.

Frequently Asked Questions about blog-decay

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I detect content decay from Google Search Console data?▼

Export page-level GSC data for two comparable periods as JSON, then run the content_decay.py script with both files. It compares clicks or impressions per page and flags declines of 20% or more with severity levels and recommended actions.

How to compare quarter-over-quarter traffic drops for blog posts?▼

Use adjacent periods of similar length and run the analyzer with the default clicks metric. For seasonality checks, also run a year-over-year comparison using the same date length, filters, search type, device, and country.

What GSC export format does the decay analyzer accept?▼

The script accepts JSON lists of page rows containing page or url, clicks, and impressions fields. It also accepts the object shape with rows under a top-level rows key, as returned by the blog-google gsc_query command.

Can I change the decline threshold or metric for decay detection?▼

Yes, pass --threshold to change the default 20% decline cutoff, for example --threshold 0.30, and use --metric impressions to analyze impression declines instead of clicks. Output can be formatted as markdown with --format markdown.

Why are dropped pages marked as needs_validation instead of dropped_out?▼

A page missing from the current export may reflect filter mismatches, insufficient row limits, or dimension differences rather than true loss. Confirm identical filters, matching dimensions, and URL inspection before classifying it as dropped_out.