Testing patterns for PHPUnit and Playwright E2E tests. Use when writing tests, debugging test failures, setting up test coverage, or implementing test patterns for ActivityPub features.
日本語の概要は準備中です。原文の説明を表示しています。
Extracts and analyzes competitors' ads from ad libraries (Facebook, LinkedIn, etc.) to understand what messaging, problems, and creative approaches are working. Helps inspire and improve your own ad campaigns.
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This skill extracts your competitors' ads from ad libraries and analyzes what's working—the problems they're highlighting, use cases they're targeting, and copy/creative that's resonating.
Extract all current ads from [Competitor Name] on Facebook Ad Library
Scrape ads from [Company] and analyze their messaging
Get all ads from [Competitor] focusing on their messaging
about [specific problem]. What pain points are they highlighting?
Extract ads from these 5 competitors: [list].
Compare their approaches and tell me what's working.
Get LinkedIn ads from [Competitor] and analyze their
B2B positioning strategy
User: "Extract ads from Notion on Facebook Ad Library and tell me what messaging is working for them."
Process:
Accessing Facebook Ad Library...
Searching for: Notion
Found: 23 active ads
Extracting screenshots...
[████████████████████] 100%
Saved to: competitor-ads/notion/
- ad-001-collaboration.png
- ad-002-productivity.png
- ad-003-templates.png
...
Analyzing messaging...
Output:
# Notion Ad Analysis
## Overview
- Total Ads: 23 active
- Primary Themes: Productivity (35%), Collaboration (30%),
Templates (20%), AI Features (15%)
- Ad Formats: Static images (60%), Video (40%)
- CTA Patterns: "Try for free", "Get started"
## Key Problems They're Highlighting
1. **Scattered Information** (8 ads)
Copy: "Stop switching between 10 different tools"
Why it works: Direct pain point many teams face
2. **Meeting Overload** (5 ads)
Copy: "Replace unnecessary meetings with async updates"
Why it works: Post-COVID remote work pain point
3. **Lost Documentation** (4 ads)
Copy: "Never ask 'where is that doc?' again"
Why it works: Universal workplace frustration
## Successful Creative Patterns
### Pattern 1: Before/After Split
- Shows chaotic tool landscape → Clean Notion workspace
- Used in 6 high-performing ads
- Visual metaphor is immediately clear
### Pattern 2: Feature Showcase
- GIF of actual product usage
- Shows specific feature in 5 seconds
- Used for new features (AI, templates)
### Pattern 3: Social Proof
- "Join 20M users" messaging
- Customer logos
- Used in 4 ads targeting enterprise
## Copy That's Working
Best Headlines:
1. "Your team's knowledge, finally in one place"
→ Benefit-focused, addresses pain directly
2. "The all-in-one workspace"
→ Clear positioning, broad appeal
3. "AI that actually helps you work"
→ Addresses AI skepticism, practical angle
Best Body Copy Patterns:
- Short sentences (under 10 words)
- Focus on outcomes not features
- Include specific numbers ("Cut meetings by 50%")
## Audience Targeting Insights
Based on ad variations:
- Startup founders: Solo productivity angle
- Team leads: Collaboration and alignment
- Enterprise: Security and compliance mentions
- Students: Free plan, templates, organization
## Recommendations for Your Ads
1. **Test the "tool sprawl" pain point**
→ Strong resonance based on their ad frequency
2. **Use product screenshots over abstract visuals**
→ All their top ads show actual UI
3. **Lead with the problem, not the solution**
→ "Tired of X?" performs better than "Introducing Y"
4. **Keep copy under 100 characters**
→ Their shortest ads seem most frequent
5. **Test before/after visual formats**
→ Proven pattern in their creative
## Files Saved
- All ads: ~/competitor-ads/notion/
- Analysis: ~/competitor-ads/notion/analysis.md
- Best performers: ~/competitor-ads/notion/top-10/
Inspired by: Sumant Subrahmanya's use case from Lenny's Newsletter
✓ Only use for research and inspiration ✓ Don't copy ads directly ✓ Respect intellectual property ✓ Use insights to inform original creative ✗ Don't plagiarize copy or steal designs
Compare [Competitor]'s ads from Q1 vs Q2.
What messaging has changed?
Extract ads from [Company A], [Company B], [Company C].
What are the common patterns? Where do they differ?
Show me ad patterns across the top 10 project management
tools. What problems do they all focus on?
Analyze video ads vs static image ads from [Competitor].
Which gets more engagement? (if data available)
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概要と使いどころ
Testing patterns for PHPUnit and Playwright E2E tests. Use when writing tests, debugging test failures, setting up test coverage, or implementing test patterns for ActivityPub features.
日本語の概要は準備中です。原文の説明を表示しています。
Cloud laboratory platform for automated protein testing and validation. Use when designing proteins and needing experimental validation including binding assays, expression testing, thermostability measurements, enzyme activity assays, or protein sequence optimization. Also use for submitting experiments via API, tracking experiment status, downloading results, optimizing protein sequences for better expression using computational tools (NetSolP, SoluProt, SolubleMPNN, ESM), or managing protein design workflows with wet-lab validation.
日本語の概要は準備中です。原文の説明を表示しています。
Add unsigned integer (uint) type support to PyTorch operators by updating AT_DISPATCH macros. Use when adding support for uint16, uint32, uint64 types to operators, kernels, or when user mentions enabling unsigned types, barebones unsigned types, or uint support.
日本語の概要は準備中です。原文の説明を表示しています。
This skill should be used when the user asks to "create an agent", "add an agent", "write a subagent", "agent frontmatter", "when to use description", "agent examples", "agent tools", "agent colors", "autonomous agent", or needs guidance on agent structure, system prompts, triggering conditions, or agent development best practices for Claude Code plugins.
日本語の概要は準備中です。原文の説明を表示しています。
Master advanced AgentDB features including QUIC synchronization, multi-database management, custom distance metrics, hybrid search, and distributed systems integration. Use when building distributed AI systems, multi-agent coordination, or advanced vector search applications.
日本語の概要は準備中です。原文の説明を表示しています。
Create and train AI learning plugins with AgentDB's 9 reinforcement learning algorithms. Includes Decision Transformer, Q-Learning, SARSA, Actor-Critic, and more. Use when building self-learning agents, implementing RL, or optimizing agent behavior through experience.
日本語の概要は準備中です。原文の説明を表示しています。