embedding-strategies

embedding-strategies is a skill for Claude Code, Codex from tourze/ai-infra. It costs 37 tokens per session (4,310 once invoked), scanned A, original, no licence file.

A guide to choosing and improving embedding models for semantic search and RAG. Embeddings are numerical representations of text that help systems find meaning-related content; RAG retrieves that content to support an AI answer.

In plain words
What is it for?
Use it to choose embedding models, design chunking approaches, and improve retrieval quality in search or RAG systems.
Why use it?
It helps address poor search results caused by unsuitable models, text chunks, or domain-specific language.

Skill for Claude CodeCodex

Which agent this was written for is unclear — body not stored (licence); the path alone says nothing.

Good fit Use it to choose embedding models, design chunking approaches, and improve retrieval quality in search or RAG systems.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/tourze/ai-infra/embedding-strategies
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add tourze/ai-infra --skill embedding-strategies
Clone the repo
git clone --depth 1 https://github.com/tourze/ai-infra

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for embedding-strategies

README.md
[![agentmods](https://agentmods.dev/badge/skills/tourze/ai-infra/embedding-strategies/github.svg)](https://agentmods.dev/skills/tourze/ai-infra/embedding-strategies)
Your own site
<a href="https://agentmods.dev/skills/tourze/ai-infra/embedding-strategies"><img src="https://agentmods.dev/badge/skills/tourze/ai-infra/embedding-strategies/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for embedding-strategies

Your own site · 80×15
<a href="https://agentmods.dev/skills/tourze/ai-infra/embedding-strategies"><img src="https://agentmods.dev/badge/skills/tourze/ai-infra/embedding-strategies.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 37 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 4,310 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin unknown No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00037 $0.04310
Opus 5 $0.00018 $0.02155
Sonnet 5 $0.00007 $0.00862
Haiku 4.5 $0.00004 $0.00431

Measured 9d ago against content hash d949436dadf3, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

embedding-strategies scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 9d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

skills/embedding-strategies/SKILL.md · 601 lines

The source is not reproduced here

No licence file

A repository with no LICENSE is all rights reserved by default, so the body is not copied here. The metadata, the measurements and the link are.

Read it on GitHub

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 9d ago First seen · 601 lines · 37 tokens per session scan A d949436dadf3

Subscribe to this mod's changes

embedding-strategies is a skill published in the GitHub repository tourze/ai-infra (5 stars, last pushed 5mo ago), with no licence file. It adds 37 tokens to every session and 4,310 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.

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