Borrowing it
Nothing to install: this file belongs to phuoctrung-ppt/ai-sdlc-workflow. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/phuoctrung-ppt/ai-sdlc-workflow/master/.cursor/skills/optional/ai-llm-integration/SKILL.mdgit clone --depth 1 https://github.com/phuoctrung-ppt/ai-sdlc-workflowWrote 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/phuoctrung-ppt/ai-sdlc-workflow/ai-llm-integration)<a href="https://agentmods.dev/skills/phuoctrung-ppt/ai-sdlc-workflow/ai-llm-integration"><img src="https://agentmods.dev/badge/skills/phuoctrung-ppt/ai-sdlc-workflow/ai-llm-integration/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/phuoctrung-ppt/ai-sdlc-workflow/ai-llm-integration"><img src="https://agentmods.dev/badge/skills/phuoctrung-ppt/ai-sdlc-workflow/ai-llm-integration.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 | $0.00069 | $0.00454 |
| Opus 5 | $0.00034 | $0.00227 |
| Sonnet 5 | $0.00014 | $0.00091 |
| Haiku 4.5 | $0.00007 | $0.00045 |
Grade A, and why
ai-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 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.
What it actually says
AI/LLM Integration
Domain skill: project-specific AI provider names, use-cases, and patterns come from
AGENTS.md §2and§5. This skill covers the universal patterns — adapt names to match your project.
When to Use
- Features that call external AI providers (OpenAI, Anthropic, etc.)
- Embedding generation + vector similarity search
- AI cost tracking and budget enforcement
- Any AI decision requiring human-in-the-loop review (per
AGENTS.md §5)
Mandatory Patterns
- Central router/service — all LLM calls route through a single service; budget check before each call
- Usage event — emit after every call with tokens, cost_usd, latency_ms (log to your project's usage table/service)
- Cost calculation — centralized cost utility shared across the codebase
- Fallback provider — on primary failure, fall back to secondary provider
- Prompt sanitization — sanitize user input before passing to LLM
- XAI — for consequential decisions: return
explanationwith confidence, key factors, counterfactuals - Human-in-the-loop — no auto-action on high-stakes decisions without explicit user confirmation (see
AGENTS.md §5)
References (load on demand)
- llm-router-pattern.md — router service template
- embedding-operations.md — vector similarity queries
- cost-tracking.md — usage event schema
Related Rules
.cursor/rules/003-ai-ethics-compliance.mdc
Agent
Use with @ai-worker and /ai-cost-check command.
What ships with it
3 files 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.
- 9d ago First seen · 40 lines · 69 tokens per session scan A 27cffb16917a
ai-llm-integration is a skill published in the GitHub repository phuoctrung-ppt/ai-sdlc-workflow (2 stars, last pushed 2d ago), licensed MIT. It adds 69 tokens to every session and 454 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 2026-08-31.
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