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Competitive Analysis

Community
yezannnnn
competitive-analysis

Analyze competitors and create competitive landscape documentation. Use when the user asks to analyze competitors, create competitive analysis, compare features with competitors, track competitive landscape, or understand competitive positioning.

Overview

Publisheryezannnnn
RepositoryagentGroup
Skill namecompetitive-analysis
Stars
149
Forks
49
Bundled files
Instructions only
LicenseMIT
Links
  • 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 yezannnnn on GitHub. Read the source before you install it.

Installation

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

1

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.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. 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.
2

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/yezannnnn/agentGroup.git /tmp/agentGroup
mkdir -p .claude/skills
cp -r /tmp/agentGroup/max/skills/pm-claude-skills/skills/competitive-analysis .claude/skills/competitive-analysis
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Competitive Analysis 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 Competitive Analysis 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 Competitive Analysis 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.

Competitive Analysis Skill

This skill creates structured competitive analyses for product decision-making.

Analysis Framework

1. Executive Summary

  • Market Position: Where we stand relative to competitors
  • Key Findings: Top 3-5 insights from analysis
  • Strategic Implications: What this means for our roadmap

2. Competitor Profiles

For each major competitor:

[Competitor Name]

  • Company Overview: Size, funding, market position
  • Target Customer: Who they serve
  • Value Proposition: Their core positioning
  • Business Model: How they make money
  • Strengths: What they do well
  • Weaknesses: Where they fall short
  • Recent Activity: Major updates, funding, announcements

3. Feature Comparison Matrix

FeatureUsCompetitor ACompetitor BCompetitor C
Core Feature 1✅ Full✅ Full⚠️ Limited❌ None
Core Feature 2✅ Full⚠️ Limited✅ Full✅ Full
Advanced Feature 1⚠️ Beta❌ None✅ Full❌ None

Legend:

  • ✅ Full: Complete, production-ready feature
  • ⚠️ Limited/Beta: Partial or in-development
  • ❌ None: Feature not available

Include notes on quality/implementation differences where significant.

4. Pricing Comparison

Plan TypeUsCompetitor ACompetitor BCompetitor C
Free/Trial$0$0$0N/A
Starter$29/mo$25/mo$39/mo$49/mo
Professional$79/mo$89/mo$79/mo$99/mo
EnterpriseCustomCustom$299/moCustom

Pricing Strategy Notes:

  • How our pricing compares
  • Value perception
  • Packaging differences

5. Strengths & Weaknesses Analysis

Our Competitive Advantages:

  1. [Strength] - [Why it matters]
  2. [Strength] - [Why it matters]
  3. [Strength] - [Why it matters]

Our Gaps vs. Competition:

  1. [Gap] - [Impact on customers]
  2. [Gap] - [Impact on customers]
  3. [Gap] - [Impact on customers]

6. Customer Perception Analysis

What Customers Say About Competitors (from reviews, G2, social media):

Competitor A:

  • Most Praised: [Common positive feedback]
  • Most Criticized: [Common complaints]
  • Typical User: [Who uses them]

Competitor B:

  • Most Praised: [Common positive feedback]
  • Most Criticized: [Common complaints]
  • Typical User: [Who uses them]

7. Market Positioning Map

Describe or diagram positioning on key dimensions:

  • Y-Axis: [e.g., Enterprise vs. SMB]
  • X-Axis: [e.g., Simple vs. Comprehensive]

Our Position: [Where we sit and why] Whitespace Opportunities: [Underserved segments]

8. Win/Loss Analysis

Why We Win Against Competitors:

  • Better at: [Specific capabilities]
  • Target customers that value: [What matters]

Why We Lose to Competitors:

  • When customers need: [Specific requirements]
  • When they prioritize: [What they value]

9. Strategic Implications & Recommendations

Immediate Actions (0-3 months):

  1. [Action] - [Rationale]
  2. [Action] - [Rationale]

Medium-term Strategy (3-12 months):

  1. [Action] - [Rationale]
  2. [Action] - [Rationale]

Long-term Positioning (12+ months):

  1. [Strategic direction] - [Rationale]

Analysis Best Practices

Data Sources:

  • Competitor websites and documentation
  • G2, Capterra, TrustRadius reviews
  • Customer interviews (especially win/loss)
  • Sales team feedback
  • Social media and community discussions
  • Industry analysts and reports
  • Competitor job postings (reveal strategy)

Quality Standards: ✅ Use recent data (within 3-6 months) ✅ Include sources for claims ✅ Focus on verifiable facts over assumptions ✅ Consider different customer segments ✅ Update regularly (at least quarterly)

❌ Don't rely solely on competitor marketing ❌ Don't ignore smaller/emerging competitors ❌ Don't assume features work well just because they exist ❌ Don't forget about indirect/substitute competitors

Ethical Guidelines:

  • Use only publicly available information
  • Don't misrepresent competitor capabilities
  • Be honest about their strengths
  • Don't disparage competitors personally

Monitoring Cadence

Weekly: Check for major announcements, funding, leadership changes Monthly: Review feature releases, pricing changes, marketing campaigns Quarterly: Comprehensive feature comparison, strategic assessment Annually: Market position analysis, long-term trend evaluation

Example Analysis Section

## Competitor Profile: DataSync Pro

**Company Overview**
- Founded 2019, 85 employees, $12M Series A (2023)
- Fast-growing in mid-market segment
- Strong presence in Europe

**Target Customer**
- Mid-market companies (100-1000 employees)
- Technical users comfortable with APIs
- Data-intensive operations

**Value Proposition**
"The fastest way to sync data across your entire stack"
- Focus on speed and reliability
- Developer-first approach

**Business Model**
- Freemium with generous free tier
- Usage-based pricing above free limits
- Professional services for enterprise

**Strengths**
- Superior sync speed (2-3x faster than alternatives)
- Best-in-class developer documentation
- Strong developer community (5k+ GitHub stars)
- Excellent uptime (99.97% vs industry 99.5%)
- Modern, intuitive API design

**Weaknesses**
- Limited no-code options (requires technical knowledge)
- Smaller integration library (45 vs our 120)
- No dedicated enterprise features
- Limited customization options
- Support can be slow (avg 8hr response time)

**Recent Activity**
- Jan 2026: Released real-time sync capabilities
- Dec 2025: Raised $12M Series A
- Nov 2025: Added webhooks and event streaming
- Hired ex-Stripe engineering lead as CTO

**Strategic Implications**
- Their focus on speed creates pressure on our performance
- Developer-first approach winning technical buyers
- Gaps in no-code and enterprise create opportunities
- Need to monitor their enterprise moves closely

Feature Comparison Best Practices

When comparing features:

  1. Group by Category

    • Core functionality
    • Integration capabilities
    • Analytics/reporting
    • Security/compliance
    • Collaboration features
  2. Note Quality Differences

    • Not all implementations are equal
    • Speed, reliability, UX matter
    • Example: "Both have API, but theirs has rate limits"
  3. Consider the Complete Experience

    • Onboarding process
    • Documentation quality
    • Support responsiveness
    • Mobile experience
  4. Identify Gaps That Matter

    • What customers actually care about
    • Not just feature count
    • Focus on differentiators

Win/Loss Analysis Template

When analyzing why you win or lose deals:

Win Against [Competitor]

  • Scenarios: When do we win?
  • Key Differentiators: What tips the decision?
  • Customer Quotes: What they tell us
  • Typical Profile: Who chooses us?

Loss Against [Competitor]

  • Scenarios: When do we lose?
  • Their Advantages: What tips the decision?
  • Customer Quotes: What they tell us
  • Typical Profile: Who chooses them?

Lessons Learned

  • What we need to improve
  • What we need to communicate better
  • Where we should compete differently

Frequently asked questions

What does the Competitive Analysis AI skill do?

Analyze competitors and create competitive landscape documentation. Use when the user asks to analyze competitors, create competitive analysis, compare features with competitors, track competitive landscape, or understand competitive positioning.

Why use Competitive Analysis on TypingMind?

Because you install it once and use it with any model. Competitive Analysis 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 Competitive Analysis in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/yezannnnn/agentGroup/tree/master/max/skills/pm-claude-skills/skills/competitive-analysis. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Competitive Analysis?

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 Competitive Analysis?

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

Is the Competitive Analysis AI skill free?

Yes. It is published on GitHub by yezannnnn 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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