llm-integration

Rules for adding large-language-model features using OpenAI and Anthropic services. Large language models are AI systems that generate or interpret text and code.

In plain words
What is it for?
Applying the listed patterns when building OpenAI or Anthropic integrations.
Why use it?
They provide consistent guidance for connecting applications to these AI services.

Cursor rule for Cursor

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.

agentmods
npx agentmods add rules/humanstack/vibe-coding-template/llm-integration
Clone the repo
git clone --depth 1 https://github.com/humanstack/vibe-coding-template

Made for: Cursor.

Per session 0 Nothing until a file matches its globs; then the whole rule loads.
When invoked 703 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
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 $0.00000 $0.00703
Opus 5 $0.00000 $0.00351
Sonnet 5 $0.00000 $0.00141
Haiku 4.5 $0.00000 $0.00070

Measured yesterday against content hash fa0cc328f62c, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

llm-integration 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 yesterday.

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.

.cursor/rules/backend/llm-integration.mdc · 113 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. yesterday First seen · 113 lines · 0 tokens per session scan A fa0cc328f62c

Subscribe to this mod's changes

llm-integration is a cursor rule published in the GitHub repository humanstack/vibe-coding-template (245 stars, last pushed 12mo ago), with no licence file. It costs nothing until one of its globs matches a file; then it loads 703 tokens. 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.