Blog Decay

CommunityPopular

AgriciDaniel

blog-decay

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".

Overview

Publisher	AgriciDaniel
Repository	`claude-blog`
Skill name	`blog-decay`
Stars	2.2K
Forks	362
Bundled files	Instructions only
License	MIT
Links	Skill source Repository Homepage

Markdown instructions
A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.
Works with any LLM
AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.
Self-contained
Everything the model needs lives in the instructions — no extra files to sync.
Open source
Published by AgriciDaniel on GitHub. Read the source before you install it.

Installation

Install the Blog Decay AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

Open the app and go to Plugins → Skills.
Choose "Install from GitHub".
Paste the skill folder URL below and confirm.
Enable the skill in any chat where you want it available.

Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills

git clone --depth 1 https://github.com/AgriciDaniel/claude-blog.git /tmp/claude-blog
mkdir -p .claude/skills
cp -r /tmp/claude-blog/skills/blog-decay .claude/skills/blog-decay

Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Blog Decay in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Blog Decay on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Blog Decay is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

Loaded only when it is needed
The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.
Switch models mid-chat
Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

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 default metric is clicks. Also review impressions, CTR, average position, query and page pairs, device, country, and search appearance deltas before choosing an action.

Severity:

Decline	Severity
20% to 39.9%	warning
40% to 59.9%	high
60% or more	critical

Dropped pages are previous-period pages missing from the current export only after confirming identical filters, sufficient row limits, matching dimensions, and URL inspection. Otherwise mark them as needs_validation, not dropped_out.

Recommended Actions

Use the action as the first triage path only after checking indexation, canonical status, query loss, internal links, backlinks, seasonality, and business value:

Action	Use when
refresh/update content	The page still has demand and likely needs freshness, title, internal link, or section updates.
investigate query shift	Clicks fell while impressions held up, suggesting CTR, rank, SERP, or query mix changes.
consolidate/redirect	The page dropped out or the loss is severe enough that merging into a stronger URL may recover value faster.
prune	The page had very low prior demand and may not justify rewrite effort.

Cross-references

Use blog-google to collect Search Console exports when live credentials are available. Use blog-rewrite after decay detection when the recommended action is refresh/update content and the page is worth improving.

Frequently asked questions

What does the Blog Decay AI skill do?

Why use Blog Decay on TypingMind?

Because you install it once and use it with any model. Blog Decay is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Blog Decay in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/AgriciDaniel/claude-blog/tree/main/skills/blog-decay. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Blog Decay?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Blog Decay?

As many as you like. As long as a model supports skills, you can use Blog Decay with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Blog Decay AI skill free?

Yes. It is published on GitHub by AgriciDaniel under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

View all

Tdd

mattpocock

CommunityPopular

Test-driven development. Use when the user wants to build features or fix bugs test-first, mentions "red-green-refactor", or wants integration tests.

To Spec

Turn the current conversation into a spec and publish it to the project issue tracker: no interview, just synthesis of what you've already discussed.

To Tickets

Break a plan, spec, or the current conversation into a set of tracer-bullet tickets, each declaring its blocking edges, published to the configured tracker (edges as text in one file per ticket…

Triage

Move issues and external PRs through a state machine of triage roles, categorise, verify, grill if needed, and write agent-ready briefs.

Overview

Installation

Install in TypingMind

Install in another agent

Use it in TypingMind

Works with any AI model

Skill instructions

Blog Decay

Default Offline Workflow

Optional Live GSC Export

Decay Model

Recommended Actions

Cross-references

Frequently asked questions

Related AI Skills

Set up your own AI workspace now