serp-analysis

SERP analysis techniques for intent classification, feature identification, and competitive intelligence. Use when analyzing search results for content strategy.

248 stars

Best use case

serp-analysis is best used when you need a repeatable AI agent workflow instead of a one-off prompt.

SERP analysis techniques for intent classification, feature identification, and competitive intelligence. Use when analyzing search results for content strategy.

Teams using serp-analysis should expect a more consistent output, faster repeated execution, less prompt rewriting.

When to use this skill

  • You want a reusable workflow that can be run more than once with consistent structure.

When not to use this skill

  • You only need a quick one-off answer and do not need a reusable workflow.
  • You cannot install or maintain the underlying files, dependencies, or repository context.

Installation

Claude Code / Cursor / Codex

$curl -o ~/.claude/skills/serp-analysis/SKILL.md --create-dirs "https://raw.githubusercontent.com/MadAppGang/claude-code/main/plugins/seo/skills/serp-analysis/SKILL.md"

Manual Installation

  1. Download SKILL.md from GitHub
  2. Place it in .claude/skills/serp-analysis/SKILL.md inside your project
  3. Restart your AI agent — it will auto-discover the skill

How serp-analysis Compares

Feature / Agentserp-analysisStandard Approach
Platform SupportNot specifiedLimited / Varies
Context Awareness High Baseline
Installation ComplexityUnknownN/A

Frequently Asked Questions

What does this skill do?

SERP analysis techniques for intent classification, feature identification, and competitive intelligence. Use when analyzing search results for content strategy.

Where can I find the source code?

You can find the source code on GitHub using the link provided at the top of the page.

Related Guides

SKILL.md Source

plugin: seo
updated: 2026-01-20

# 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

1. **Search the keyword** using WebSearch
2. **Analyze result types**:
   - All informational = Informational intent
   - Mix of reviews/comparisons = Commercial intent
   - Product pages dominant = Transactional intent
   - Single brand dominant = Navigational intent
3. **Check for mixed intent** (common for broad keywords)
4. **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:

1. **Domain authority** (relative, not exact)
2. **Content format** (guide, listicle, comparison, etc.)
3. **Word count** (approximate)
4. **Heading structure** (H2 topics covered)
5. **Unique angle** (what makes them different)
6. **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

```markdown
## 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}
```

Related Skills

deep-analysis

248
from MadAppGang/claude-code

⚡ PRIMARY SKILL for: 'how does X work', 'investigate', 'analyze architecture', 'trace flow', 'find implementations'. PREREQUISITE: code-search-selector must validate tool choice. Launches codebase-detective with claudemem INDEXED MEMORY.

test-skill

248
from MadAppGang/claude-code

A test skill for validation testing. Use when testing skill parsing and validation logic.

bad-skill

248
from MadAppGang/claude-code

This skill has invalid YAML in frontmatter

release

248
from MadAppGang/claude-code

Plugin release process for MAG Claude Plugins marketplace. Covers version bumping, marketplace.json updates, git tagging, and common mistakes. Use when releasing new plugin versions or troubleshooting update issues.

openrouter-trending-models

248
from MadAppGang/claude-code

Fetch trending programming models from OpenRouter rankings. Use when selecting models for multi-model review, updating model recommendations, or researching current AI coding trends. Provides model IDs, context windows, pricing, and usage statistics from the most recent week.

Claudish Integration Skill

248
from MadAppGang/claude-code

**Version:** 1.0.0

transcription

248
from MadAppGang/claude-code

Audio/video transcription using OpenAI Whisper. Covers installation, model selection, transcript formats (SRT, VTT, JSON), timing synchronization, and speaker diarization. Use when transcribing media or generating subtitles.

final-cut-pro

248
from MadAppGang/claude-code

Apple Final Cut Pro FCPXML format reference. Covers project structure, timeline creation, clip references, effects, and transitions. Use when generating FCP projects or understanding FCPXML structure.

ffmpeg-core

248
from MadAppGang/claude-code

FFmpeg fundamentals for video/audio manipulation. Covers common operations (trim, concat, convert, extract), codec selection, filter chains, and performance optimization. Use when planning or executing video processing tasks.

statusline-customization

248
from MadAppGang/claude-code

Configuration reference and troubleshooting for the statusline plugin — sections, themes, bar widths, and script architecture

technical-audit

248
from MadAppGang/claude-code

Technical SEO audit methodology including crawlability, indexability, and Core Web Vitals analysis. Use when auditing pages or sites for technical SEO issues.

schema-markup

248
from MadAppGang/claude-code

Schema.org markup implementation patterns for rich results. Use when adding structured data to content for enhanced SERP appearances.