Seo Images logo

Seo Images

CommunityPopular
AgriciDaniel
seo-images

Image optimization analysis for SEO and performance. Checks alt text, file sizes, formats, responsive images, lazy loading, CLS prevention, image SERP rankings (via DataForSEO), and image file optimization (WebP/AVIF conversion, IPTC/XMP metadata injection). Use when user says "image optimization", "alt text", "image SEO", "image size", "image audit", "optimize images", "image metadata", "image SERP", "convert to webp", or "image file optimize".

Overview

PublisherAgriciDaniel
Repositoryclaude-seo
Skill nameseo-images
Stars
17.1K
Forks
2.5K
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 AgriciDaniel on GitHub. Read the source before you install it.

Installation

Install the Seo Images 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/AgriciDaniel/claude-seo.git /tmp/claude-seo
mkdir -p .claude/skills
cp -r /tmp/claude-seo/skills/seo-images .claude/skills/seo-images
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Seo Images 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 Seo Images 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 Seo Images 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.

Image Optimization Analysis

Checks

Alt Text

  • Present on all <img> elements (except decorative: role="presentation")
  • Descriptive: describes the image content, not "image.jpg" or "photo"
  • Includes relevant keywords where natural, not keyword-stuffed
  • Length: 10-125 characters

Good examples:

  • "Professional plumber repairing kitchen sink faucet"
  • "Red 2024 Toyota Camry sedan front view"
  • "Team meeting in modern office conference room"

Bad examples:

  • "image.jpg" (filename, not description)
  • "plumber plumbing plumber services" (keyword stuffing)
  • "Click here" (not descriptive)

File Size

Tiered thresholds by image category:

Image CategoryTargetWarningCritical
Thumbnails< 50KB> 100KB> 200KB
Content images< 100KB> 200KB> 500KB
Hero/banner images< 200KB> 300KB> 700KB

Recommend compression to target thresholds where possible without quality loss.

Format

FormatBrowser SupportUse Case
WebP97%+Default recommendation
AVIF92%+Best compression, newer
JPEG100%Fallback for photos
PNG100%Graphics with transparency
SVG100%Icons, logos, illustrations

Recommend WebP/AVIF over JPEG/PNG. Check for <picture> element with format fallbacks.

Recommended <picture> Element Pattern

Use progressive enhancement with the most efficient format first:

html
<picture>
  <source srcset="image.avif" type="image/avif">
  <source srcset="image.webp" type="image/webp">
  <img src="image.jpg" alt="Descriptive alt text" width="800" height="600" loading="lazy" decoding="async">
</picture>

The browser will use the first supported format. Current browser support: AVIF 93.8%, WebP 95.3%.

JPEG XL: Emerging Format

Third-party reporting and Wikipedia describe a Rust-based JPEG XL decoder as shipped in Chrome 145 stable (2026-02-10) behind the chrome://flags/#enable-jxl-image-format flag, not enabled by default; no Google-owned confirmation was retrieved in the fact pack. Because default support is not confirmed, it is not yet practical for production web delivery. Keep serving AVIF/WebP with JPEG fallback and monitor.

Responsive Images

  • srcset attribute for multiple sizes
  • sizes attribute matching layout breakpoints
  • Appropriate resolution for device pixel ratios
html
<img
  src="image-800.jpg"
  srcset="image-400.jpg 400w, image-800.jpg 800w, image-1200.jpg 1200w"
  sizes="(max-width: 600px) 400px, (max-width: 1200px) 800px, 1200px"
  alt="Description"
>

Lazy Loading

  • loading="lazy" on below-fold images
  • Do NOT lazy-load above-fold/hero images (hurts LCP)
  • Check for native vs JavaScript-based lazy loading
html
<!-- Below fold - lazy load -->
<img src="photo.jpg" loading="lazy" alt="Description">

<!-- Above fold - eager load (default) -->
<img src="hero.jpg" alt="Hero image">
Detected lazy-loader methods (lazy_method field)

"${CLAUDE_PLUGIN_ROOT}/scripts/claude-seo" run parse_html.py classifies each image's lazy-loading mechanism via the lazy_method field on every image entry. Five values:

lazy_methodSignal detectedCommon stack
nativeloading="lazy" HTML attributeModern browsers, plain HTML
perfmattersdata-perfmatters-src/-srcset OR class perfmatters-lazyWordPress + Perfmatters plugin
ewwwdata-ewww-src / data-eio OR class lazyload-eioWordPress + EWWW Image Optimizer
js-genericdata-src / data-lazy-src / data-original / data-srcset OR class lazyload/lazyloaded/lazyLazysizes, vanilla-lazyload, jQuery plugins
noneNeither attribute nor class signalPage is not lazy-loading this image

When auditing image SEO, report lazy_method alongside loading so users know whether their site is using a JS-driven lazy-loader (in which case the native loading="lazy" attribute is intentionally absent, that is not a regression).

fetchpriority="high" for LCP Images

Add fetchpriority="high" to your hero/LCP image to prioritize its download in the browser's network queue:

html
<img src="hero.webp" fetchpriority="high" alt="Hero image description" width="1200" height="630">

Critical: Do NOT lazy-load above-the-fold/LCP images. Using loading="lazy" on LCP images directly harms LCP scores. Reserve loading="lazy" for below-the-fold images only.

decoding="async" for Non-LCP Images

Add decoding="async" to non-LCP images to prevent image decoding from blocking the main thread:

html
<img src="photo.webp" alt="Description" width="600" height="400" loading="lazy" decoding="async">

CLS Prevention

  • width and height attributes set on all <img> elements
  • aspect-ratio CSS as alternative
  • Flag images without dimensions
html
<!-- Good - dimensions set -->
<img src="photo.jpg" width="800" height="600" alt="Description">

<!-- Good - CSS aspect ratio -->
<img src="photo.jpg" style="aspect-ratio: 4/3" alt="Description">

<!-- Bad - no dimensions -->
<img src="photo.jpg" alt="Description">

File Names

  • Descriptive: blue-running-shoes.webp not IMG_1234.jpg
  • Hyphenated, lowercase, no special characters
  • Include relevant keywords

CDN Usage

  • Check if images served from CDN (different domain, CDN headers)
  • Recommend CDN for image-heavy sites
  • Check for edge caching headers

Output

Image Audit Summary

MetricStatusCount
Total Images-XX
Missing Alt TextXX
Oversized (>200KB)⚠️XX
Wrong Format⚠️XX
No Dimensions⚠️XX
Not Lazy Loaded⚠️XX

Prioritized Optimization List

Sorted by file size impact (largest savings first):

ImageCurrent SizeFormatIssuesEst. Savings
...............

Recommendations

  1. Convert X images to WebP format (est. XX KB savings)
  2. Add alt text to X images
  3. Add dimensions to X images
  4. Enable lazy loading on X below-fold images
  5. Compress X oversized images

Image SERP Analysis

When DataForSEO MCP is available, enhance the image audit with competitive data.

/seo images serp <keyword>

Cross-reference on-page images with Google Images SERP rankings.

Workflow:

  1. Fetch Google Images results via serp_google_images_live_advanced (depth=100)
  2. Extract: top domains, image types, alt text patterns
  3. Output competitor image SERP landscape

Output:

RankDomainTitle/AltImage URLPage URL
1example.com"Blue running shoes...".../shoes.webp/products/...

Analysis includes:

  • Domain dominance: which sites own the most image positions (top 10 by count)
  • Alt text patterns: common title/alt patterns in top-ranking images
  • Format distribution: WebP vs JPEG vs PNG in top results
  • Opportunity score: keywords where you have page rankings but no image presence

If DataForSEO MCP is not available, inform user and suggest installing the extension.


Image File Optimization

Optimize image files for SEO: format conversion, metadata injection, compression.

/seo images optimize <path>

Optimize image file(s) for web and SEO. Converts to WebP/AVIF, injects IPTC metadata, compresses, and generates responsive variants.

Tools used (in order of preference):

  • exiftool -- EXIF/IPTC/XMP read/write (install: sudo apt install libimage-exiftool-perl)
  • cwebp -- WebP conversion (install: sudo apt install webp)
  • ImageMagick convert -- Format conversion, resizing (pre-installed on most systems)
  • FFmpeg -- Fallback for format conversion (pre-installed)

Before running: Check which tools are available with which exiftool cwebp convert ffmpeg.

Format Conversion

Convert images to modern formats with metadata preservation:

bash
# WebP (recommended default) - with metadata preserved
cwebp -q 82 -metadata all input.jpg -o output.webp

# WebP via ImageMagick (fallback if cwebp not installed)
convert input.jpg -quality 82 output.webp

# AVIF via FFmpeg (slower encode, best compression)
ffmpeg -i input.jpg -c:v libaom-av1 -crf 30 -still-picture 1 output.avif

# Responsive variants (400w, 800w, 1200w)
convert input.jpg -resize 400x -quality 82 image-400.webp
convert input.jpg -resize 800x -quality 82 image-800.webp
convert input.jpg -resize 1200x -quality 82 image-1200.webp

Metadata Injection (IPTC for Google Images Display)

Google Images displays IPTC Creator, Credit Line, and Copyright in search results. This is NOT a ranking factor but can improve Google Images display and brand attribution.

With exiftool (preferred):

bash
# Read all metadata
exiftool image.jpg

# Inject IPTC + XMP metadata for Google Images rich results
exiftool \
  -IPTC:ObjectName="Product Photo Description" \
  -IPTC:Caption-Abstract="Detailed image description" \
  -IPTC:By-line="Brand Name Photography" \
  -IPTC:Credit="Brand Name" \
  -IPTC:CopyrightNotice="Copyright 2026 Brand Name" \
  -IPTC:Source="brandname.com" \
  -XMP:Title="Product Photo Description" \
  -XMP:Description="Detailed image description" \
  -XMP:Creator="Brand Name Photography" \
  -XMP:Rights="Copyright 2026 Brand Name" \
  image.jpg

# Batch inject to all images in directory
exiftool -overwrite_original \
  -IPTC:By-line="Brand Name" \
  -IPTC:CopyrightNotice="Copyright 2026 Brand Name" \
  *.jpg *.webp *.png

With ImageMagick (fallback):

bash
identify -verbose image.jpg | head -50

convert input.jpg \
  -set comment "Product Photo Description" \
  -set IPTC:2:80 "Brand Name Photography" \
  -set IPTC:2:116 "Copyright 2026 Brand Name" \
  output.jpg

Note: WebP supports EXIF and XMP but not IPTC natively. For WebP files, use XMP fields instead of IPTC. exiftool handles this conversion automatically.

AI-Generated Images: DigitalSourceType (Merchant Center requirement)

For product images produced by generative AI, Google Merchant Center requires IPTC DigitalSourceType: TrainedAlgorithmicMedia metadata. This is an operational policy requirement, not a ranking factor: feeds missing this label on AI-generated imagery can be disapproved.

Primary source (Merchant Center AI-generated content policy): https://support.google.com/merchants/answer/14743464 (the ai-optimization-guide does not document DigitalSourceType/IPTC/Merchant labeling.)

Audit command:

bash
# Audit a directory for the IPTC label (counts: missing, ai, captured, etc.)
"${CLAUDE_PLUGIN_ROOT}/scripts/claude-seo" run iptc_ai_label.py audit ./images/ --json

# Audit a single image
"${CLAUDE_PLUGIN_ROOT}/scripts/claude-seo" run iptc_ai_label.py audit ./hero.webp --json

# Inject the AI label into an image
"${CLAUDE_PLUGIN_ROOT}/scripts/claude-seo" run iptc_ai_label.py inject ./ai-hero.webp \
    --source-type trainedAlgorithmicMedia

# Other vocabulary values:
#   compositeSynthetic               (mix of captured + AI elements)
#   algorithmicMedia                 (created purely by algorithm, NOT from sampled training data)
#   compositeWithTrainedAlgorithmicMedia (e.g. AI inpainting/outpainting over real media)
#   digitalCapture                   (fully captured photograph)

Raw exiftool equivalents (for ad-hoc usage):

bash
# Inject manually
exiftool \
  -XMP-iptcExt:DigitalSourceType="https://cv.iptc.org/newscodes/digitalsourcetype/trainedAlgorithmicMedia" \
  ai-generated-product.jpg

# Audit: find images missing the label across a directory
exiftool -if 'not $XMP-iptcExt:DigitalSourceType' \
  -filename -DigitalSourceType *.jpg *.webp *.png

Google extracts these IPTC DigitalSourceType values:

  • trainedAlgorithmicMedia: fully AI-generated (use this for diffusion-model product imagery)
  • compositeSynthetic: mixes captured + AI-generated elements
  • algorithmicMedia: created purely by an algorithm, not from sampled training data
  • compositeWithTrainedAlgorithmicMedia: composite of trained algorithmic media + other media (e.g. AI inpainting/outpainting over a real photo)
  • digitalCapture: fully captured photograph (note: digitalCapture is not on Google's extracted-values list, but is a valid IPTC value)

Provenance signals (consumer-facing): SynthID watermarks and C2PA Content Credentials are emerging signals for AI media identification. Treat product-surface coverage as subject to change unless verified from a current Google-owned source. This is detection/transparency, not an extra required Merchant feed field beyond IPTC DigitalSourceType.

Licensable images: to earn the Licensable badge, supply EITHER structured data (ImageObject with the license property + acquireLicensePage for the "Get this image" link) OR embedded IPTC photo metadata (Licensor URL / Web Statement of Rights). Cross-link seo-schema for the ImageObject markup.

Discovery note: image discovery now includes visual search fan-out across Lens / AI Mode / Circle to Search (Gemini multimodal scene/object understanding), so images surface via scene, objects, and materials, not alt text alone. No new published image-SEO lever yet; keep descriptive alt text + clean structured data.

When /seo images optimize is run on AI-generated assets, prompt the user to confirm the source type and inject the matching IPTC value automatically.

For AI-generated product titles and descriptions, Google Merchant Center also requires the AI-generated text to be separately specified and labeled in the feed. This is enforced at the feed layer, not the page layer, flag this in cross-reference with seo-ecommerce.

Metadata Audit

bash
# Quick audit with exiftool
exiftool -IPTC:all -XMP:all -EXIF:ImageDescription image.jpg

# Batch audit - find images missing IPTC Creator
exiftool -if 'not $IPTC:By-line' -filename *.jpg *.webp *.png

Full Optimization Pipeline

For maximum image SEO, run this pipeline on each image:

  1. Audit existing metadata: exiftool -IPTC:all -XMP:all image.jpg
  2. Inject IPTC/XMP metadata: Creator, Copyright, Description
  3. Convert to WebP: cwebp -q 82 -metadata all image.jpg -o image.webp
  4. Generate responsive variants: 400w, 800w, 1200w
  5. Verify metadata preserved: exiftool image.webp
  6. Generate <picture> HTML: AVIF > WebP > JPEG fallback chain

What Matters vs What Doesn't for Google Images

FactorImpactWhere to Set
Alt textCRITICAL (ranking)HTML <img alt="">
FilenameHIGH (ranking)File system (descriptive, hyphenated)
Page contextHIGH (ranking)Surrounding HTML content
File size/speedMEDIUM (indirect via CWV)Compression + format conversion
IPTC Creator/CopyrightLOW (display only)Image file metadata
EXIF camera dataNONEIrrelevant for SEO
IPTC KeywordsNONEGoogle ignores these

Error Handling

ScenarioAction
URL unreachableReport connection error with status code. Suggest verifying URL and checking if site requires authentication.
No images found on pageReport that no <img> elements were detected. Suggest checking if images are loaded via JavaScript or CSS background-image.
Images behind CDN or authenticationNote that image files could not be directly accessed for size analysis. Report available metadata (alt text, dimensions, format from markup) and flag inaccessible resources.
exiftool not installedFall back to ImageMagick for metadata. Recommend: sudo apt install libimage-exiftool-perl
cwebp not installedFall back to ImageMagick or FFmpeg for WebP conversion. Recommend: sudo apt install webp
DataForSEO MCP not availableSkip Image SERP Analysis section. Note extension is not installed.

Frequently asked questions

What does the Seo Images AI skill do?

Image optimization analysis for SEO and performance. Checks alt text, file sizes, formats, responsive images, lazy loading, CLS prevention, image SERP rankings (via DataForSEO), and image file optimization (WebP/AVIF conversion, IPTC/XMP metadata injection). Use when user says "image optimization", "alt text", "image SEO", "image size", "image audit", "optimize images", "image metadata", "image SERP", "convert to webp", or "image file optimize".

Why use Seo Images on TypingMind?

Because you install it once and use it with any model. Seo Images 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 Seo Images in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/AgriciDaniel/claude-seo/tree/main/skills/seo-images. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Seo Images?

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 Seo Images?

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

Is the Seo Images AI skill free?

Yes. It is published on GitHub by AgriciDaniel 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.

View all

Set up your own AI workspace now

Get notified about new features and future giveaways by subscribing to our newsletter 👇