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 jayll1303/AIEKit --skill vllm-tgi-inferencegit clone --depth 1 https://github.com/jayll1303/AIEKitWrote 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/jayll1303/aiekit/vllm-tgi-inference)<a href="https://agentmods.dev/skills/jayll1303/aiekit/vllm-tgi-inference"><img src="https://agentmods.dev/badge/skills/jayll1303/aiekit/vllm-tgi-inference.svg" alt="Measured on agentmods" 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 | $0.00062 | $0.03866 |
| Opus 5 | $0.00031 | $0.01933 |
| Sonnet 5 | $0.00012 | $0.00773 |
| Haiku 4.5 | $0.00006 | $0.00387 |
Grade C, and why
vllm-tgi-inference scanned grade C with 2 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 8d 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.
Downloads and executes remote codehighSupply chain
curl | sh runs whatever the server returns today, which is not necessarily what it returned when this was reviewed.
**Validate:** `curl -s http://localhost:8000/v1/models | python -m json.tool` returns a model list. If not → check `nvidia-smi` for VRAM availability and server logs for loading errors. Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
- Calling OpenAI-compatible `/v1/` endpoints from Python or curl 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.
What ships with it
4 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.
- 8d ago First seen · 315 lines · 62 tokens per session scan C 4b44f2630611
vllm-tgi-inference is a skill published in the GitHub repository jayll1303/AIEKit (18 stars, last pushed 3mo ago), with no licence file. It adds 62 tokens to every session and 3,866 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it C with 2 findings (downloads and executes remote code, makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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