Competitor Scan

Community

Mehdibargach

competitor-scan

Quick competitive landscape scan for any product or market. Takes a product/market description and returns a competitive map with positioning, gaps, and opportunities.

Overview

Publisher	Mehdibargach
Repository	`claude-code-pm-skills`
Skill name	`competitor-scan`
Stars	97
Forks	38
Bundled files	Instructions only
Links	Skill source Repository

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 Mehdibargach on GitHub. Read the source before you install it.

Installation

Install the Competitor Scan 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.
https://github.com/Mehdibargach/claude-code-pm-skills/tree/main/skills/competitor-scan
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/Mehdibargach/claude-code-pm-skills.git /tmp/claude-code-pm-skills
mkdir -p .claude/skills
cp -r /tmp/claude-code-pm-skills/skills/competitor-scan .claude/skills/competitor-scan

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

Use it in TypingMind

Enable Competitor Scan 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 Scan 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 Scan 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 Scan

Perform a rapid competitive landscape analysis. The goal is to give a PM a clear picture of who's playing in a space, how they're positioned, and where the openings are.

Process

Parse the input — Extract the core market/product being analyzed. Identify the category, target customer, and key value proposition.
Research competitors — Use WebSearch to find direct competitors (same category, same customer) and indirect competitors (different approach, same job-to-be-done). Aim for 5-8 competitors. Check product pages, pricing pages, and recent coverage via WebFetch when needed.
Analyze positioning — For each competitor, determine: who they target, what they lead with, how they price, and what users complain about.
Map the landscape — Identify the two most differentiating axes in this market (e.g., self-serve vs. enterprise, horizontal vs. vertical). Describe where each player sits.
Find gaps — Look for underserved segments, missing features that keep coming up in reviews, or pricing tiers nobody covers.
Synthesize — Write a tight competitive brief.

Output Format

Market Overview

One paragraph: what this market is, estimated maturity (emerging / growing / mature / declining), and the dominant business model.

Competitor Table

Competitor	Positioning	Target Customer	Strengths	Weaknesses	Pricing Model
...	...	...	...	...	...

Positioning Map

Describe the two axes chosen and where each competitor falls. Use a text-based 2x2 if it helps clarity.

White Space Opportunities

Bullet list of 3-5 gaps or underserved areas with a one-line explanation each.

Key Takeaway

One paragraph: the single most important insight a PM should walk away with.

Rules

Prioritize direct competitors over tangential ones. If in doubt, include them but flag as indirect.
Always check pricing pages — "Contact us" is valid data, note it as enterprise/opaque pricing.
Do not invent data. If you cannot find reliable info on a competitor, say so explicitly.
Keep the entire output under 2 pages. Density over length.
Write in English.
Be opinionated: rank competitors by threat level, call out who is winning and why.
If the market has fewer than 3 competitors, flag it as a blue ocean and shift focus to adjacent markets and substitutes.

Frequently asked questions

What does the Competitor Scan AI skill do?

Quick competitive landscape scan for any product or market. Takes a product/market description and returns a competitive map with positioning, gaps, and opportunities.

Why use Competitor Scan on TypingMind?

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

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

Which AI models can use Competitor Scan?

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 Scan?

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

Is the Competitor Scan AI skill free?

It is published on GitHub by Mehdibargach. Check the repository for licensing terms. 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 Scan

Process

Output Format

Market Overview

Competitor Table

Positioning Map

White Space Opportunities

Key Takeaway

Rules

Frequently asked questions

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