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 roedyrustam/vibes-plug --skill ai-llm-integration-expertgit clone --depth 1 https://github.com/roedyrustam/vibes-plugWrote 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/roedyrustam/vibes-plug/ai-llm-integration-expert)<a href="https://agentmods.dev/skills/roedyrustam/vibes-plug/ai-llm-integration-expert"><img src="https://agentmods.dev/badge/skills/roedyrustam/vibes-plug/ai-llm-integration-expert/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/roedyrustam/vibes-plug/ai-llm-integration-expert"><img src="https://agentmods.dev/badge/skills/roedyrustam/vibes-plug/ai-llm-integration-expert.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00067 | $0.03202 |
| Opus 5 | $0.00034 | $0.01601 |
| Sonnet 5 | $0.00013 | $0.00640 |
| Haiku 4.5 | $0.00007 | $0.00320 |
Grade A, and why
ai-llm-integration-expert 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 11d 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.
How it starts
The opening of the file, as written. The whole thing — 189 lines — stays where its author put it; the contents beside it link to each section on GitHub.
AI & LLM Integration Expert (2026 Edition)
English
Description
Production-grade guidelines for integrating AI, Model Context Protocol (MCP), and Large Language Models (LLMs) into modern applications. Covers RAG pipelines, vector embeddings, real-time token streaming, agentic tool execution, memory architectures, prompt caching, and multi-model orchestration.
Trigger Conditions
- Integrating frontier models: OpenAI GPT-4o / GPT-4.1 / GPT-5, Anthropic Claude 3.7 / Claude 4 Sonnet/Opus, Google Gemini 3.1 Pro/Flash/Ultra, or open-source models (DeepSeek-V3/R2, Llama 4, Qwen 3).
- Implementing Model Context Protocol (MCP) server or client integrations (MCP 1.9+).
- Building AI chatbots, copilots, or autonomous AI agent workflows (LangGraph, OpenAI Agents SDK, Google ADK, Mastra.ai, Vercel AI SDK 4.x/5.x).
- Building agentic memory systems (short-term, long-term, episodic) using Mem0, MemGPT, or Supabase-backed memory stores.
- Implementing RAG with vector databases (Supabase pgvector HNSW, Qdrant, Pinecone, Weaviate).
- Handling real-time AI token streaming via SSE, Web Streams, or WebSockets.
- Designing AI agents with tool-calling, computer use (browser/OS automation), or code interpreter capabilities.
Model Capability Matrix (2026)
| Provider | Model | Context | Strengths |
|---|---|---|---|
| OpenAI | GPT-4o / GPT-4.1 | 128K | Multimodal, tool-calling, speed |
| OpenAI | GPT-5 | 1M+ | Reasoning, agentic tasks |
| Anthropic | Claude 4 Sonnet | 200K | Coding, long documents, Computer Use |
| Anthropic | Claude 4 Opus | 200K | Complex reasoning, deep analysis |
| Gemini 3.1 Flash | 2M | Speed, cost efficiency, multimodal | |
| Gemini 3.1 Pro | 2M | Code, reasoning, deep research | |
| Meta | Llama 4 Scout/Maverick | 512K | Open-source, self-hosted |
| DeepSeek | V3 / R2 | 128K | Code, math, cost-efficient |
Core Architecture Guidelines
1. Model Context Protocol (MCP) Integration (v1.9+)
Standardize agent-tool interactions using MCP. The 2026 standard adds Streamable HTTP transport alongside stdio/SSE:
- MCP Servers: Expose tools, resources, and prompt templates over JSON-RPC 2.0.
- Streamable HTTP: New default transport for cloud-hosted MCP servers — supports bidirectional streaming without long-polling.
- Security & Scope: Validate all incoming parameters with Zod schemas. Enforce strict authorization boundaries before executing tool calls.
- Tool namespacing: Use
domain/actionnaming (files/read,db/query) to avoid collisions in multi-server environments.
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.
- 11d ago First seen · 189 lines · 67 tokens per session scan A 37a0dfcb7bc6
ai-llm-integration-expert is a skill published in the GitHub repository roedyrustam/vibes-plug (50 stars, last pushed today), licensed MIT. It adds 67 tokens to every session and 3,202 once invoked, about $0.0003 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 2026-08-30.
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