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Google Gemini Embeddings

Category: Engineering  ·  Sub-category: ml-ai-eng  ·  Last updated:
cloud:cloudflareai:geminiai:rag
This skill provides complete coverage of Google Gemini embeddings API (gemini-embedding-001) for building RAG systems, semantic search, document clustering, and similarity matching. Use when implementing vector search with Google's embedding models, integrating with Cloudflare Vectorize, or building retrieval-augmented generation systems. Covers SDK usage (@google/genai), fetch-based Workers implementation, batch processing, 8 task types (RETRIEVAL_QUERY, RETRIEVAL_DOCUMENT, SEMANTIC_SIMILARITY, etc.), dimension optimization (128-3072), and cosine similarity calculations. Prevents 8+ embedding-specific errors including dimension mismatches, incorrect task types, rate limiting issues (100 RPM free tier), vector normalization mistakes, text truncation (2,048 token limit), and model version confusion. Includes production-ready RAG patterns with Cloudflare Vectorize integration, chunking strategies, and caching patterns. Token savings: ~60%. Production tested.
Security AStatic scan found no risk patternsHow grading works ›

About this skill (catalog notes)

Google Gemini Embeddings includes a dedicated installation section; pricing or quota commentary; 35 code blocks for direct copy-paste. At roughly 3,029 words the SKILL.md is on the longer end of the catalog distribution.

Source
claudeskillz.jackspace.com
License
MIT
Original author
jackspace
Indexed lastmod
Catalog position
Engineering · ml-ai-eng
Indexed related skills
10

How Google Gemini Embeddings fits the catalog

Google Gemini Embeddings sits in the Engineering category under the ml-ai-eng sub-topic in the ClaudSkills catalog. There are 10 related skills indexed alongside it; comparing a few before installing usually reveals which fits your workflow best.

These notes are auto-generated from features detected in the SKILL.md file and from this catalog's structure — they aren't part of the source repository.

From the source SKILL.md

Complete production-ready guide for Google Gemini embeddings API

What this skill does

Google Gemini Embeddings is a community-contributed Claude Code skill in the ml-ai-eng sub-category. It ships as a SKILL.md file that Claude Code auto-discovers under ~/.claude/skills/google-gemini-embeddings/ and loads when your prompt matches the skill's trigger.

When to invoke it: Use when implementing vector search with Google's embedding models, integrating with Cloudflare Vectorize, or building retrieval-augmented generation systems. Covers SDK usage (@google/genai), fetch-based Workers implementation, batch processing, 8 task types (RETRIEVAL_QUERY, RETRIEVAL_DOCUMENT, SEMANTIC_SIMILARITY, etc.

Who uses this skill

The Google Gemini Embeddings Claude Code skill is built for software engineers, backend developers, full-stack teams, and technical leads building and maintaining production systems. It's part of ClaudSkills (also referred to as Claude Skills or Claude Code Skills) — the open community-curated registry of 178,000+ SKILL.md files for Anthropic's Claude Code agent and the wider Claude ecosystem (Claude API, Claude Agent SDK).

How to install

Free

Manual install (2 steps)

mkdir -p ~/.claude/skills/google-gemini-embeddings
curl -L https://claudskills.com/skills/google-gemini-embeddings/SKILL.md \
  -o ~/.claude/skills/google-gemini-embeddings/SKILL.md

Or just download SKILL.md directly and drop it into ~/.claude/skills/google-gemini-embeddings/. Claude Code auto-discovers it on next session.

Skills live at ~/.claude/skills/google-gemini-embeddings/SKILL.md on macOS/Linux, or %USERPROFILE%\.claude\skills\google-gemini-embeddings\SKILL.md on Windows. See the full install guide for step-by-step instructions.

Telegram

📱 Install from your phone or desktop Telegram

Open @claudskills_bot on Telegram, tap Open Desktop App, and the desktop app installs this skill for you. Or share the bot link with a colleague — they get the same one-tap install. Learn more →

Pro

One-click install via the desktop app

The ClaudSkills desktop app installs any skill directly into ~/.claude/skills/ with one click — no terminal required. Pro starts at $9/mo or $149 lifetime.

Pro

For the full experience including quality scoring and one-click install features for each skill — upgrade to Pro.

See pricing → Download desktop app

Frequently asked questions

How do I install the Google Gemini Embeddings Claude Code skill?
Install via the ClaudSkills desktop app (one click) or copy SKILL.md from the source repository to ~/.claude/skills/google-gemini-embeddings/SKILL.md and restart Claude Code. Both flows are detailed at claudskills.com/install/.
What does the Google Gemini Embeddings skill do?
This skill provides complete coverage of Google Gemini embeddings API (gemini-embedding-001) for building RAG systems, semantic search, document clustering, and similarity matching. Use when implementing vector search with Google's embedding models, integrating with Cloudflare Vectorize, or building retrieval-augmented generation systems. Covers SDK usage (@google/genai), fetch-based Workers implementation, batch processing, 8 task types (RETRIEVAL_QUERY, RETRIEVAL_DOCUMENT, SEMANTIC_SIMILARITY, etc.), dimension optimization (128-3072), and cosine similarity calculations. Prevents 8+ embedding-specific errors including dimension mismatches, incorrect task types, rate limiting issues (100 RPM free tier), vector normalization mistakes, text truncation (2,048 token limit), and model version confusion. Includes production-ready RAG patterns with Cloudflare Vectorize integration, chunking strategies, and caching patterns. Token savings: ~60%. Production tested.
Is this skill free to install?
Yes. ClaudSkills is an open registry — every skill keeps its source repository's license, and manual install via copy is free. ClaudSkills Pro ($9/mo, $79/yr, or $149 one-time) adds one-click install via the desktop app and a multi-signal Quality Score.
When should I use the Google Gemini Embeddings skill?
Use Google Gemini Embeddings when your Claude Code task falls under the Engineering category — specifically in the ml ai eng area. Claude Code auto-discovers installed skills and invokes the right one based on the task description, so you can also ask Claude directly (e.g. "use Google Gemini Embeddings" or describe the task and let Claude pick). Browse related skills at /category/engineering/.
What is a Claude Code skill and how does the Google Gemini Embeddings skill fit in?
A Claude Code skill is a SKILL.md file that lives under ~/.claude/skills/<name>/ and tells the Claude Code CLI agent how to perform a specific task (instructions, prompts, allowed tools). Skills are auto-discovered at session start. Google Gemini Embeddings is one of 67,000+ skills indexed in the open ClaudSkills catalog, classified under the Engineering category. Learn more at /learn/what-is-a-claude-skill/.

Attribution & license

Cite this skill

If you reference this skill in a blog post, paper, or documentation, you can cite it as:

APA
jackspace. (2026). Google Gemini Embeddings [Claude Code skill]. ClaudSkills. https://claudskills.com/skills/google-gemini-embeddings/
BibTeX
@misc{google-gemini-embeddings-2026,
  author    = {jackspace},
  title     = {Google Gemini Embeddings [Claude Code skill]},
  year      = {2026},
  publisher = {ClaudSkills},
  url       = {https://claudskills.com/skills/google-gemini-embeddings/}
}

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Security scan

Grade A · scanned 2026-08-07 — free static scan against the OWASP Agentic Skills Top 10.

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Browse all Engineering skills in the ClaudSkills registry, or explore these other picks from the same category:

Browse all Engineering skills → Top 100 skills
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