Search Console

OrganizationPopular

nowork-studio

search-console

Query and operate connected Google Search Console properties through NotFair MCP. Use for live GSC query or page performance, clicks, impressions, CTR, position, traffic changes, indexing status, URL inspection, sitemap reads or approved sitemap submission/removal, and Search Console MCP setup. Route full-site SEO audits to seo-analysis.

Overview

Publisher	nowork-studio
Repository	`notfair-plugin`
Skill name	`search-console`
Stars	3.8K
Forks	488
Bundled files	2
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.
2 bundled files
Scripts, templates, and references the model can read while it works. Files are read-only and never executed.
Open source
Published by nowork-studio on GitHub. Read the source before you install it.

Installation

Install the Search Console 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/nowork-studio/notfair-plugin.git /tmp/notfair-plugin
mkdir -p .claude/skills
cp -r /tmp/notfair-plugin/analytics/search-console .claude/skills/search-console

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

Use it in TypingMind

Enable Search Console 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 Search Console 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 Search Console 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.

Google Search Console

Read ../shared/operating-contract.md. Use the live connector's instructions and schemas to choose tools for the task. For a full-site SEO audit that also needs crawling and on-page analysis, hand off to /notfair:seo-analysis after confirming access.

Select the exact property

Resolve ~~search-console to the actual Search Console connector and inspect its current tools. Use live property information to identify the intended site.
Use the exact verified property form returned by the connector: sc-domain:example.com and https://example.com/ are different properties.
Define the search type, complete date window, comparison window, dimensions, and business question. If the platform is missing or unauthorized, direct the user to reconnect the universal NotFair plugin and stop before claiming live data.

Analyze organic performance

Correlate totals, queries, pages, countries, and devices as needed for the question. Choose available reporting capabilities; batch related reads when supported and useful, and use a narrow read for a single property, URL, or sitemap.

Query totals without the query dimension when reconciling property-level clicks and impressions. Anonymized low-volume queries make query rows incomplete by design.
Finalized data normally lags recent dates; label fresh all data as provisional.
Show clicks, impressions, CTR, and average position with their exact dimensions and period. Do not average already-aggregated CTR or position rows naively.
Respect row and historical coverage limits reported by the connector. State when the result is top rows rather than a complete export.
Use URL inspection selectively because its quota is tighter than Search Analytics. Inspection reports index state; it does not request indexing.
Treat ranking movement as evidence, not proof of a specific algorithmic cause.

Lead with the largest material gain or loss, affected queries/pages, evidence-backed hypothesis, confidence, and the next SEO action. Route content rewrites, technical remediation, or full audits to the corresponding SEO skill.

Manage sitemaps safely

Submit or remove a sitemap through a supported capability only after showing the exact verified property and sitemap URL and obtaining approval. Confirm the sitemap belongs to the selected property and is fetchable before submission when possible.

Submission and deletion are reversible counterparts, but deleting a submitted sitemap does not remove its URLs from Google's index. Never describe sitemap submission as an indexing guarantee. Confirm the resulting sitemap state from returned before/after evidence or a fresh list.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

agents/openai.yaml1 KB
evals/evals.json2 KB

Frequently asked questions

What does the Search Console AI skill do?

Why use Search Console on TypingMind?

Because you install it once and use it with any model. Search Console 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 Search Console in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/nowork-studio/notfair-plugin/tree/main/analytics/search-console. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Search Console?

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 Search Console?

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

Is the Search Console AI skill free?

Yes. It is published on GitHub by nowork-studio 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.

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Overview

Installation

Install in TypingMind

Install in another agent

Use it in TypingMind

Works with any AI model

Skill instructions

Google Search Console

Select the exact property

Analyze organic performance

Manage sitemaps safely

Bundled files

Frequently asked questions

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