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Competitor Teardown

Organization
101-skills
competitor-teardown

Structured competitive analysis with feature matrices, SWOT, positioning maps, and UX review. Covers research frameworks, pricing comparison, review mining, and visual deliverables. Use for: market research, competitive intelligence, investor decks, product strategy, sales enablement. Triggers: competitor analysis, competitive analysis, competitor teardown, market research, competitive intelligence, swot analysis, competitor comparison, market landscape, competitor review, competitive landscape, feature comparison, market positioning

Overview

Publisher101-skills
Repositorysuperpowers
Skill namecompetitor-teardown
Stars
5
Forks
3
Bundled files
Instructions only
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 101-skills on GitHub. Read the source before you install it.

Installation

Install the Competitor Teardown 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.
    https://github.com/101-skills/superpowers/tree/main/guides/product/competitor-teardown
  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/101-skills/superpowers.git /tmp/superpowers
mkdir -p .claude/skills
cp -r /tmp/superpowers/guides/product/competitor-teardown .claude/skills/competitor-teardown
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Competitor Teardown 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 Teardown 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 Teardown 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.

Install the belt CLI skill: npx skills add belt-sh/cli

Competitor Teardown

Structured competitive analysis with research and screenshots via inference.sh CLI.

Quick Start

Requires inference.sh CLI (belt). Install instructions

bash
belt login

# Research competitor landscape
belt app run tavily/search-assistant --input '{
  "query": "top project management tools comparison 2024 market share"
}'

# Screenshot competitor's website
belt app run infsh/agent-browser --input '{
  "url": "https://competitor.com",
  "action": "screenshot"
}'

Teardown Framework

The 7-Layer Analysis

LayerWhat to AnalyzeData Source
1. ProductFeatures, UX, qualityScreenshots, free trial
2. PricingPlans, pricing model, hidden costsPricing page, sales call
3. PositioningMessaging, tagline, ICPWebsite, ads
4. TractionUsers, revenue, growthWeb search, press, funding
5. ReviewsStrengths, weaknesses from usersG2, Capterra, App Store
6. ContentBlog, social, SEO strategyWebsite, social profiles
7. TeamSize, key hires, backgroundLinkedIn, About page

Research Commands

Company Overview

bash
# General intelligence
belt app run tavily/search-assistant --input '{
  "query": "CompetitorX company overview funding team size 2024"
}'

# Funding and financials
belt app run exa/search --input '{
  "query": "CompetitorX funding round series valuation investors"
}'

# Recent news
belt app run tavily/search-assistant --input '{
  "query": "CompetitorX latest news announcements 2024"
}'

Product Analysis

bash
# Feature comparison
belt app run exa/search --input '{
  "query": "CompetitorX vs alternatives feature comparison review"
}'

# Pricing details
belt app run tavily/extract --input '{
  "urls": ["https://competitor.com/pricing"]
}'

# User reviews
belt app run tavily/search-assistant --input '{
  "query": "CompetitorX reviews G2 Capterra pros cons 2024"
}'

UX Screenshots

bash
# Homepage
belt app run infsh/agent-browser --input '{
  "url": "https://competitor.com",
  "action": "screenshot"
}'

# Pricing page
belt app run infsh/agent-browser --input '{
  "url": "https://competitor.com/pricing",
  "action": "screenshot"
}'

# Signup flow
belt app run infsh/agent-browser --input '{
  "url": "https://competitor.com/signup",
  "action": "screenshot"
}'

Feature Matrix

Structure

markdown
| Feature | Your Product | Competitor A | Competitor B | Competitor C |
|---------|:---:|:---:|:---:|:---:|
| Real-time collaboration | ✅ | ✅ | ❌ | ✅ |
| API access | ✅ | Paid only | ✅ | ❌ |
| SSO/SAML | ✅ | Enterprise | ✅ | Enterprise |
| Custom reports | ✅ | Limited | ✅ | ❌ |
| Mobile app | ✅ | iOS only | ✅ | ✅ |
| Free tier | ✅ (unlimited) | ✅ (3 users) | ❌ | ✅ (1 project) |
| Integrations | 50+ | 100+ | 30+ | 20+ |

Rules

  • ✅ = Full support
  • ⚠️ or "Partial" = Limited or conditional
  • ❌ = Not available
  • Note conditions: "Paid only", "Enterprise tier", "Beta"
  • Lead with features where YOU win
  • Be honest about competitor strengths — credibility matters

Pricing Comparison

Structure

markdown
| | Your Product | Competitor A | Competitor B |
|---------|:---:|:---:|:---:|
| **Free tier** | Yes, 5 users | Yes, 3 users | No |
| **Starter** | $10/user/mo | $15/user/mo | $12/user/mo |
| **Pro** | $25/user/mo | $30/user/mo | $29/user/mo |
| **Enterprise** | Custom | Custom | $50/user/mo |
| **Billing** | Monthly/Annual | Annual only | Monthly/Annual |
| **Annual discount** | 20% | 15% | 25% |
| **Min seats** | 1 | 5 | 3 |
| **Hidden costs** | None | Setup fee $500 | API calls metered |

What to Look For

  • Minimum seat requirements
  • Annual-only billing (reduces flexibility)
  • Feature gating between tiers
  • Overage charges
  • Setup/onboarding fees
  • Contract lock-in periods

SWOT Analysis

Create a SWOT for each competitor:

markdown
### Competitor A — SWOT

| Strengths | Weaknesses |
|-----------|------------|
| • Strong brand recognition | • Slow feature development |
| • Large integration ecosystem | • Complex onboarding (30+ min) |
| • Enterprise sales team | • No free tier |

| Opportunities | Threats |
|--------------|---------|
| • AI features not yet shipped | • New AI-native competitors |
| • Expanding into mid-market | • Customer complaints about pricing |
| • International markets untapped | • Key engineer departures (LinkedIn) |

Positioning Map

A 2x2 matrix showing where competitors sit on two meaningful dimensions.

Choose Meaningful Axes

Good AxesBad Axes
Simple ↔ ComplexGood ↔ Bad
SMB ↔ EnterpriseCheap ↔ Expensive (too obvious)
Self-serve ↔ Sales-ledOld ↔ New
Specialized ↔ GeneralSmall ↔ Large
Opinionated ↔ Flexible—

Template

                    Enterprise
                        │
           Competitor C │  Competitor A
                ●       │       ●
                        │
  Simple ──────────────────────────── Complex
                        │
            You ●       │  Competitor B
                        │       ●
                        │
                      SMB

Generating the Visual

bash
# Create positioning map with Python
belt app run infsh/python-executor --input '{
  "code": "import matplotlib.pyplot as plt\nimport matplotlib\nmatplotlib.use(\"Agg\")\n\nfig, ax = plt.subplots(figsize=(10, 10))\n\n# Competitors\ncompetitors = {\n    \"You\": (-0.3, -0.3),\n    \"Competitor A\": (0.5, 0.6),\n    \"Competitor B\": (0.6, -0.4),\n    \"Competitor C\": (-0.4, 0.5)\n}\n\nfor name, (x, y) in competitors.items():\n    color = \"#22c55e\" if name == \"You\" else \"#6366f1\"\n    size = 200 if name == \"You\" else 150\n    ax.scatter(x, y, s=size, c=color, zorder=5)\n    ax.annotate(name, (x, y), textcoords=\"offset points\", xytext=(10, 10), fontsize=12, fontweight=\"bold\")\n\nax.axhline(y=0, color=\"grey\", linewidth=0.5)\nax.axvline(x=0, color=\"grey\", linewidth=0.5)\nax.set_xlim(-1, 1)\nax.set_ylim(-1, 1)\nax.set_xlabel(\"Simple ← → Complex\", fontsize=14)\nax.set_ylabel(\"SMB ← → Enterprise\", fontsize=14)\nax.set_title(\"Competitive Positioning Map\", fontsize=16, fontweight=\"bold\")\nax.grid(True, alpha=0.3)\nplt.tight_layout()\nplt.savefig(\"positioning-map.png\", dpi=150)\nprint(\"Saved\")"
}'

Review Mining

Where to Find Reviews

PlatformBest ForURL Pattern
G2B2B SaaSg2.com/products/[product]/reviews
CapterraBusiness softwarecapterra.com/software/[id]/reviews
App StoreiOS appsapps.apple.com
Google PlayAndroid appsplay.google.com
Product HuntLaunchesproducthunt.com/posts/[product]
RedditHonest opinionsreddit.com/r/[relevant-sub]

What to Extract

CategoryLook For
Most praisedWhat features do happy users mention most?
Most complainedWhat do unhappy users say? (= your opportunity)
Switching reasonsWhy do users leave? What triggers switching?
Feature requestsWhat's missing that users want?
Comparison mentionsWhen users compare, what do they say?
bash
# Mine G2 reviews
belt app run tavily/search-assistant --input '{
  "query": "CompetitorX G2 reviews complaints issues 2024"
}'

# Reddit sentiment
belt app run exa/search --input '{
  "query": "reddit CompetitorX alternative frustration switching"
}'

Deliverable Formats

Executive Summary (1 page)

markdown
## Competitive Landscape Summary

**Market:** [Category] — $[X]B market growing [Y]% annually

**Key competitors:** A (leader), B (challenger), C (niche)

**Our positioning:** [Where you sit and why it matters]

**Key insight:** [One sentence about the biggest opportunity]

| Metric | You | A | B | C |
|--------|-----|---|---|---|
| Users | X | Y | Z | W |
| Pricing (starter) | $X | $Y | $Z | $W |
| Rating (G2) | X.X | Y.Y | Z.Z | W.W |

Detailed Report (per competitor)

  1. Company overview (size, funding, team)
  2. Product analysis (features, UX screenshots)
  3. Pricing breakdown
  4. SWOT analysis
  5. Review analysis (top praised, top complained)
  6. Positioning vs. you
  7. Opportunity summary

Comparison Grid Visual

bash
# Stitch competitor screenshots into comparison
belt app run infsh/stitch-images --input '{
  "images": ["your-homepage.png", "competitorA-homepage.png", "competitorB-homepage.png"],
  "direction": "horizontal"
}'

Common Mistakes

MistakeProblemFix
Only looking at featuresMisses positioning, pricing, tractionUse the 7-layer framework
Biased analysisLoses credibilityBe honest about competitor strengths
Outdated dataWrong conclusionsDate all research, refresh quarterly
Too many competitorsAnalysis paralysisFocus on top 3-5 direct competitors
No "so what"Data without insightEnd each section with implications for you
Feature-only comparisonDoesn't show positioningInclude pricing, reviews, positioning map

Related Skills

bash
npx skills add inference-sh/skills@web-search
npx skills add inference-sh/skills@prompt-engineering

Browse all apps: belt app list

Frequently asked questions

What does the Competitor Teardown AI skill do?

Structured competitive analysis with feature matrices, SWOT, positioning maps, and UX review. Covers research frameworks, pricing comparison, review mining, and visual deliverables. Use for: market research, competitive intelligence, investor decks, product strategy, sales enablement. Triggers: competitor analysis, competitive analysis, competitor teardown, market research, competitive intelligence, swot analysis, competitor comparison, market landscape, competitor review, competitive landscape, feature comparison, market positioning

Why use Competitor Teardown on TypingMind?

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

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/101-skills/superpowers/tree/main/guides/product/competitor-teardown. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Competitor Teardown?

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 Teardown?

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

Is the Competitor Teardown AI skill free?

It is published on GitHub by 101-skills. 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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