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Install in OpenClaw
/install geo-multimodal-tagger
Description
Generate AI-optimized Alt Text, file names, captions, and Schema markup for images, videos, and audio assets. Improves AI discoverability on Google Lens, Cha...
README (SKILL.md)
Multimodal Asset Tagger
Methodology by GEOly AI (geoly.ai) — every image and video is a citation opportunity AI can either read or miss.
Generate optimized metadata for images, videos, and audio files for AI platforms.
Quick Start
python scripts/optimize_asset.py --type image --description "dashboard showing metrics" --output optimized.md
Why Multimodal Matters
AI platforms increasingly read visual content:
| Platform | Visual Capability | Citation Type |
|---|---|---|
| Google Lens | Image search | Direct image citation |
| ChatGPT Vision | Image understanding | Contextual reference |
| Perplexity | Video transcripts | Transcript citations |
| Gemini | Native image processing | Multimodal answers |
Image Optimization
Alt Text Formula
[Descriptive subject] + [Brand if relevant] + [Context/use case]
Examples:
❌ alt="image1.jpg"
❌ alt="product photo"
✅ alt="GEOly AI dashboard showing AIGVR score trend over 30 days"
✅ alt="Brand visibility comparison chart across ChatGPT and Perplexity — GEOly AI"
Filename Formula
[primary-keyword]-[secondary-keyword]-[brand]-[descriptor].jpg
Examples:
❌ IMG_3847.jpg
✅ geo-brand-visibility-dashboard-geoly-ai.png
✅ aigvr-score-chart-ai-search-monitoring.jpg
ImageObject Schema
{
"@context": "https://schema.org",
"@type": "ImageObject",
"name": "AIGVR Score Dashboard",
"description": "Dashboard showing brand visibility scores across AI platforms",
"contentUrl": "https://example.com/images/dashboard.jpg",
"author": {
"@type": "Organization",
"name": "GEOly AI"
},
"keywords": "AIGVR, brand visibility, AI search, dashboard"
}
Video Optimization
Checklist
- Title contains primary keyword
- Description: first 150 chars = keyword + brand
- Transcript/captions attached (SRT/VTT)
- Chapters/timestamps for long videos
- Thumbnail: keyword-rich filename
- VideoObject Schema added
VideoObject Schema
{
"@context": "https://schema.org",
"@type": "VideoObject",
"name": "How to Optimize for AI Search",
"description": "Complete guide to GEO strategies...",
"thumbnailUrl": "https://example.com/thumbs/geo-guide.jpg",
"uploadDate": "2024-01-15",
"duration": "PT12M30S",
"contentUrl": "https://example.com/videos/geo-guide.mp4"
}
Audio/Podcast Optimization
- Descriptive episode titles (not "Episode 47")
- 150+ word descriptions, keyword-rich
- Full transcript as page content
- Guest names and topics as entities
Asset Optimization Tool
python scripts/optimize_asset.py \
--type [image|video|audio] \
--description "Asset description" \
--brand "BrandName" \
--keywords "keyword1,keyword2"
Output:
- Optimized Alt Text
- Recommended filename
- Schema markup
- Discoverability score (Before/After)
Scoring
| Factor | Weight | Best Practice |
|---|---|---|
| Descriptiveness | 30% | Specific, detailed |
| Keyword presence | 25% | Natural inclusion |
| Brand mention | 20% | When relevant |
| Context | 15% | Use case clear |
| Length | 10% | 100-150 chars for Alt |
Discoverability Score: 0-10
- 8-10: Excellent
- 6-7: Good
- 4-5: Fair
- \x3C4: Poor
Usage Guidance
This skill appears harmless and consistent with generating simple alt text/filenames, but the documentation over-promises features the code doesn't implement (schema markup, scoring, video/audio support). Before installing: (1) verify the source or owner if you require provenance; (2) review and run the small Python script in a sandbox/local environment—it only prints an alt text and a filename; (3) if you need Schema markup, scoring, or video/audio handling, plan to extend the code or use a different tool; (4) avoid supplying secrets or connecting it to production systems until you expand and test its functionality.
Capability Analysis
Type: OpenClaw Skill
Name: geo-multimodal-tagger
Version: 1.0.0
The `scripts/optimize_asset.py` file generates filenames from user-provided descriptions without adequate sanitization. While the script itself only prints to stdout, this creates a path traversal or command injection vulnerability if the OpenClaw agent or a downstream system uses the generated filename directly to create files or execute shell commands. The `SKILL.md` instructs the agent to execute this script with user-controlled input, making this a potential attack vector. There is no evidence of intentional malicious behavior like data exfiltration or persistence.
Capability Assessment
Purpose & Capability
The name and description (generate alt text, filenames, captions, and Schema markup for images, video, audio) align with the provided SKILL.md guidance. However, the only executable code (scripts/optimize_asset.py) only produces simple Alt Text and a filename for images; it does not produce Schema markup, discoverability scores, or explicit support for video/audio. This is an over-promise vs. actual capability.
Instruction Scope
SKILL.md instructs running the bundled Python script and contains methodology and templates. The runtime instructions do not request any secrets, system files, or network endpoints. They do, however, instruct generation of outputs (Schema, scores) that are not produced by the script, so following the SKILL.md may give a false expectation of behavior.
Install Mechanism
No install spec is provided (instruction-only). The included Python script is small, pure local code, and there are no external downloads, package installs, or archive extraction steps.
Credentials
The skill requests no environment variables, no credentials, and references no config paths. The code does not access environment variables or external services, so requested privileges are minimal and proportionate.
Persistence & Privilege
The skill is not always-enabled and does not request persistent presence or modify agent/system configuration. It runs a local script when invoked and does not store credentials or alter other skills.
How to Use
- Make sure OpenClaw is installed (local or Docker)
- Run the install command in chat:
/install geo-multimodal-tagger - After installation, invoke the skill by name or use
/geo-multimodal-tagger - Provide required inputs per the skill's parameter spec and get structured output
Version History
v1.0.0
Initial release: Generate Alt Text, filenames and Schema for images/videos, GEOly AI Multimodal Agent approach
Metadata
Frequently Asked Questions
What is Multimodal Asset Tagger?
Generate AI-optimized Alt Text, file names, captions, and Schema markup for images, videos, and audio assets. Improves AI discoverability on Google Lens, Cha... It is an AI Agent Skill for Claude Code / OpenClaw, with 407 downloads so far.
How do I install Multimodal Asset Tagger?
Run "/install geo-multimodal-tagger" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.
Is Multimodal Asset Tagger free?
Yes, Multimodal Asset Tagger is completely free (open-source). You can download, install and use it at no cost.
Which platforms does Multimodal Asset Tagger support?
Multimodal Asset Tagger is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).
Who created Multimodal Asset Tagger?
It is built and maintained by GEOLY AI (@geoly-geo); the current version is v1.0.0.
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