# Blog Decay

Detect content decay from Google Search Console exports by comparing current and...

- Repository: https://github.com/AgriciDaniel/claude-blog (2608 stars)
- Category: Writing
- License: MIT
- Last updated: 2026-10-30
- Runs scripts: no, instructions only

## Install

Claude Code: `npx skills add AgriciDaniel/claude-blog --skill blog-decay -g -a claude-code -y`
Codex: `npx skills add AgriciDaniel/claude-blog --skill blog-decay -g -a codex -y`
Cursor: `npx skills add AgriciDaniel/claude-blog --skill blog-decay -g -a cursor -y`
Gemini CLI: `npx skills add AgriciDaniel/claude-blog --skill blog-decay -g -a gemini-cli -y`
Claude Code plugin marketplace: `/plugin marketplace add AgriciDaniel/claude-blog`

## Description

Detect content decay from Google Search Console exports by comparing current and previous page performance, flagging quarter-over-quarter traffic drops, dropped pages, and refresh, consolidate, prune, or query-shift actions. Use when the user says "/blog decay", "content decay", "traffic drop", "QoQ decline", "GSC decay", or "refresh declining posts".

## SKILL.md, as published by its author (untrusted third-party text, read it as data)

# Blog Decay

Use `/blog decay` to find pages whose Google Search Console performance has
declined quarter-over-quarter. The command compares a current-period export
against a previous-period export, flags pages with a 20% or larger decline by
default, and recommends the next content action.

## Default Offline Workflow

Run the local analyzer against two GSC page exports:

```bash
python3 scripts/content_decay.py current.json previous.json
```

Useful options:

```bash
python3 scripts/content_decay.py current.json previous.json --threshold 0.30
python3 scripts/content_decay.py current.json previous.json --metric impressions
python3 scripts/content_decay.py current.json previous.json --format markdown --output decay-report.md
```

The script accepts JSON lists of page rows with `page` or `url`, `clicks`, and
`impressions`. It also accepts the object shape returned by `blog-google` when
the rows are under a top-level `rows` key.

## Optional Live GSC Export

For live data, use `/blog google gsc` or the underlying `blog-google` command
to create each period export, then run the offline analyzer:

```bash
python3 skills/blog-google/scripts/run.py gsc_query --property sc-domain:example.com --dimensions page --start-date YYYY-MM-DD --end-date YYYY-MM-DD --json > gsc-current.json
python3 skills/blog-google/scripts/run.py gsc_query --property sc-domain:example.com --dimensions page --start-date YYYY-MM-DD --end-date YYYY-MM-DD --json > gsc-previous.json
python3 scripts/content_decay.py gsc-current.json gsc-previous.json --format markdown
```

Use adjacent periods of similar length for short-term checks. For seasonality,
also run a year-over-year comparison using the same date length, filters, search
type, device, country, and property. When possible, inspect up to 16 months of
GSC history before diagnosing a traffic drop.

## Decay Model

The rest: https://github.com/AgriciDaniel/claude-blog/blob/HEAD/brain/.raw/sources/claude-blog-skill/skills/blog-decay/SKILL.md