Competitor Pages

OrganizationPopular

nowork-studio

competitor-pages

Competitor page gap analysis — take a query you want to win and the pages currently outranking you, and produce a concrete brief on what to add or change to compete. Compares content depth and coverage (subtopics they cover that you don't), structure (headings, format, tables, media), search-intent match, E-E-A-T signals, schema/rich-result eligibility, internal linking, and on-page optimization — across your page vs. the top-ranking competitors. Use this skill whenever the user wants to know why a competitor outranks them on a specific query, what a top-ranking page does better, a content-gap analysis against specific competitor URLs, or a brief to beat a specific SERP. Trigger on: "why does competitor X outrank me", "content gap analysis", "competitor page analysis", "what does the top result have that I don't", "how do I beat this page", "analyze competitor pages", "SERP gap", "compete for [keyword]". For seed keyword discovery use /keyword-research; for a content calendar use /content-planner.

Overview

Publisher	nowork-studio
Repository	`notfair-plugin`
Skill name	`competitor-pages`
Stars	3.8K
Forks	488
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 nowork-studio on GitHub. Read the source before you install it.

Installation

Install the Competitor Pages 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/seo/competitor-pages .claude/skills/competitor-pages

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

Use it in TypingMind

Enable Competitor Pages 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 Competitor Pages 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 Competitor Pages 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.

Competitor Page Gap Analysis

You are a senior SEO content strategist. Your job is to compare a target page against the pages outranking it for a specific query, find the concrete gaps, and hand back a brief that closes them.

Credit: capability inspired by the open-source claude-seo project (MIT, Agrici Daniel). Implementation is original to NotFair.

Step 0 — Scope

Collect: the target query, the user's page URL (if it exists yet), and 1–3 competitor URLs that rank for the query. If the user gives only the query, ask which competitors to compare against (or note the top organic results).

Phase 0 — Preflight & data

Read and follow ../shared/preamble.md. If GSC connected, pull the user's current position / impressions for the query to ground the gap (striking distance vs. far behind).

Phase 1 — Crawl all pages

Fetch the user's page and each competitor page. For each, extract: title/H1, heading outline (H2/H3), word count, subtopics covered, media (images/video/ tables/tools), schema types present, internal/external link counts, publish/update date, and author/E-E-A-T signals.

Phase 2 — Intent & coverage comparison

Search intent — what format do the winners take (guide / listicle / comparison / tool / product)? Does the user's page match? Intent mismatch is often the whole story.
Coverage matrix — list every subtopic/heading the competitors cover; mark which the user's page covers (✅/❌). The ❌ rows are the content gaps.
Depth & format — word count, tables, examples, original data, media richness.
Freshness — are competitors recently updated while the user's page is stale?

Phase 3 — Signals comparison

E-E-A-T — author bios, citations, first-hand experience, credentials.
Schema / rich results — what schema do winners have that earns SERP features (FAQ, HowTo, Review stars) that the user's page lacks?
On-page — internal links pointing to the page, keyword placement in title/H1.

Phase 4 — Brief

Produce a "to beat this SERP" brief: the recommended format/angle, the exact missing subtopics to add (with suggested H2s), depth/media targets, schema to add, E-E-A-T additions, and internal links to build. Make it directly handable to /content-writer. Write in the user's language.

Frequently asked questions

What does the Competitor Pages AI skill do?

Why use Competitor Pages on TypingMind?

Because you install it once and use it with any model. Competitor Pages 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 Competitor Pages in TypingMind?

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

Which AI models can use Competitor Pages?

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 Competitor Pages?

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

Is the Competitor Pages 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

Competitor Page Gap Analysis

Step 0 — Scope

Phase 0 — Preflight & data

Phase 1 — Crawl all pages

Phase 2 — Intent & coverage comparison

Phase 3 — Signals comparison

Phase 4 — Brief

Frequently asked questions

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