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.
npx skills add yunseo-kim/agent-toolbox --skill rag-patternsgit clone --depth 1 https://github.com/yunseo-kim/agent-toolboxWrote 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.
[](https://agentmods.dev/skills/yunseo-kim/agent-toolbox/rag-patterns)<a href="https://agentmods.dev/skills/yunseo-kim/agent-toolbox/rag-patterns"><img src="https://agentmods.dev/badge/skills/yunseo-kim/agent-toolbox/rag-patterns/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.
<a href="https://agentmods.dev/skills/yunseo-kim/agent-toolbox/rag-patterns"><img src="https://agentmods.dev/badge/skills/yunseo-kim/agent-toolbox/rag-patterns.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00044 | $0.04154 |
| Opus 5 | $0.00022 | $0.02077 |
| Sonnet 5 | $0.00009 | $0.00831 |
| Haiku 4.5 | $0.00004 | $0.00415 |
Grade A, and why
rag-patterns 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 5d 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.
The source is not reproduced here
A licence we could not identify
The repository carries a LICENSE file, but it is custom or dual enough that GitHub cannot name it and neither can this catalogue. Unknown terms are not permission, so the body is not copied here. Read the licence at the source and decide for yourself.
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 5d ago First seen · 368 lines · 44 tokens per session scan A 09e9c1b5d331
rag-patterns is a skill published in the GitHub repository yunseo-kim/agent-toolbox (1 stars, last pushed yesterday), with no licence file. It adds 44 tokens to every session and 4,154 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.
Other skills, from other repositories
azure-ai-contentunderstanding-py
Multimodal AI service that extracts semantic content from documents, video, audio, and image files for RAG and automated workflows.
ai-engineer
Build production-ready LLM applications, RAG systems, and intelligent agents. Use when implementing AI features, chatbots, vector search, or agent orchestration.
ai-product
Every product will be AI-powered. The question is whether you'll build it right or ship a demo that falls apart in production. This skill covers LLM integration patterns, RAG architecture, prompt ...
azure-search-documents-py
Full-text, vector, and hybrid search with AI enrichment capabilities.
azure-ai-openai-dotnet
Client library for Azure OpenAI Service providing access to OpenAI models including GPT-4, GPT-4o, embeddings, DALL-E, and Whisper.
azure-ai-projects-dotnet
High-level SDK for Azure AI Foundry project operations including agents, connections, datasets, deployments, evaluations, and indexes.