serp-analysis
SERP analysis techniques for intent classification, feature identification, and competitive intelligence. Use when analyzing search results for content strategy.
Installation
Details
Usage
After installing, this skill will be available to your AI coding assistant.
Verify installation:
skills listSkill Instructions
name: serp-analysis description: SERP analysis techniques for intent classification, feature identification, and competitive intelligence. Use when analyzing search results for content strategy.
SERP Analysis
When to Use
- Analyzing search results for a keyword
- Classifying search intent
- Identifying SERP feature opportunities
- Competitive intelligence gathering
Intent Classification
Intent Types
| Intent | SERP Signals | User Goal | Content Format |
|---|---|---|---|
| Informational | Wikipedia, knowledge panels, "what is" queries | Learn something | Guide, tutorial, explainer |
| Commercial | Reviews, comparisons, "best X" queries | Compare options | Comparison, listicle, review |
| Transactional | Product pages, shopping results, "buy X" | Purchase something | Product page, pricing |
| Navigational | Brand homepage, login pages | Find specific site | Homepage, login page |
Classification Process
- Search the keyword using WebSearch
- Analyze result types:
- All informational = Informational intent
- Mix of reviews/comparisons = Commercial intent
- Product pages dominant = Transactional intent
- Single brand dominant = Navigational intent
- Check for mixed intent (common for broad keywords)
- Note confidence level (% of results supporting classification)
SERP Features
Feature Identification
| Feature | How to Identify | Optimization Strategy |
|---|---|---|
| Featured Snippet | Box at top with answer | Direct answer in first 100 words |
| People Also Ask | Expandable question boxes | FAQ section, answer common questions |
| Image Pack | Row of images | High-quality images with alt text |
| Video Results | YouTube thumbnails | Create video content |
| Local Pack | Map with business listings | GMB optimization, location pages |
| Knowledge Panel | Right sidebar info box | Schema markup, Wikipedia presence |
| Sitelinks | Sub-links under main result | Clear site structure, internal linking |
Featured Snippet Types
| Type | Format | How to Optimize |
|---|---|---|
| Paragraph | Text block | 40-60 word direct answer |
| List | Numbered/bulleted list | Use ordered/unordered lists |
| Table | Data table | Use HTML tables |
| Video | YouTube embed | Create relevant video content |
Competitive Analysis
Competitor Data to Collect
For each top 10 result, note:
- Domain authority (relative, not exact)
- Content format (guide, listicle, comparison, etc.)
- Word count (approximate)
- Heading structure (H2 topics covered)
- Unique angle (what makes them different)
- Content gaps (what they miss)
Competitor Matrix Template
| Rank | Domain | Format | Words | Unique Angle | Gap |
|---|---|---|---|---|---|
| 1 | {domain} | {format} | {count} | {angle} | {gap} |
| 2 | {domain} | {format} | {count} | {angle} | {gap} |
| ... |
Output Format
## SERP Analysis: {keyword}
### Search Intent
- **Primary Intent**: {Informational | Commercial | Transactional | Navigational}
- **Confidence**: {percentage}%
- **Secondary Intent**: {if mixed}
### SERP Features Present
- [ ] Featured Snippet ({type})
- [ ] People Also Ask
- [ ] Image Pack
- [ ] Video Results
- [ ] Local Pack
- [ ] Knowledge Panel
- [ ] Sitelinks
### Competitor Analysis
| Rank | Domain | Format | Words | Unique Angle |
|------|--------|--------|-------|--------------|
| 1 | {domain} | {format} | {count} | {angle} |
...
### Content Gaps Identified
1. {gap} - {which competitors miss this}
2. {gap} - {which competitors miss this}
### Recommendations
1. **Content Format**: {recommended format based on SERP}
2. **Word Count**: {recommended based on competitors + 20%}
3. **Featured Snippet**: {opportunity and how to capture}
4. **Differentiator**: {unique angle to stand out}
More by MadAppGang
View allChoose optimal external AI models for code analysis, bug investigation, and architectural decisions. Use when consulting multiple LLMs via claudish, comparing model perspectives, or investigating complex Go/LSP/transpiler issues. Provides empirically validated model rankings (91/100 for MiniMax M2, 83/100 for Grok Code Fast) and proven consultation strategies based on real-world testing.
CRITICAL - Guide for using Claudish CLI ONLY through sub-agents to run Claude Code with OpenRouter models (Grok, GPT-5, Gemini, MiniMax). NEVER run Claudish directly in main context unless user explicitly requests it. Use when user mentions external AI models, Claudish, OpenRouter, or alternative models. Includes mandatory sub-agent delegation patterns, agent selection guide, file-based instructions, and strict rules to prevent context window pollution.
MANDATORY tracking protocol for multi-model validation. Creates structured tracking tables BEFORE launching models, tracks progress during execution, and ensures complete results presentation. Use when running 2+ external AI models in parallel. Trigger keywords - "multi-model", "parallel review", "external models", "consensus", "model tracking".
XML tag structure patterns for Claude Code agents and commands. Use when designing or implementing agents to ensure proper XML structure following Anthropic best practices.