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 1llu50ry/mcp-gamehacking --skill ags-anticheatgit clone --depth 1 https://github.com/1llu50ry/mcp-gamehackingWrote 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/1llu50ry/mcp-gamehacking/ags-anticheat)<a href="https://agentmods.dev/skills/1llu50ry/mcp-gamehacking/ags-anticheat"><img src="https://agentmods.dev/badge/skills/1llu50ry/mcp-gamehacking/ags-anticheat/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/1llu50ry/mcp-gamehacking/ags-anticheat"><img src="https://agentmods.dev/badge/skills/1llu50ry/mcp-gamehacking/ags-anticheat.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 | $0.00039 | $0.00232 |
| Opus 5.5 | $0.00016 | $0.00093 |
| Sonnet 5.5 | $0.00008 | $0.00046 |
| Haiku 4.5 | $0.00004 | $0.00023 |
Grade A, and why
ags-anticheat 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 2d 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
anticheat
Author: Hexze Source: mcp-gamehacking/skills/ags-anticheat
Description
Cheater Detector is a Lua anticheat plugin for the Starfish framework that monitors in-game players and flags behavior patterns associated with cheating. It implements configurable detection checks such as NoSlow, AutoBlock, Eagle, Scaffold, Tower, LagRange, and NoBreakDelay, each with enable toggles, violation thresholds, alert cooldowns, and optional sound alerts. The plugin tracks player movement, equipment, animations, metadata, and block-break timing, then raises alerts and emits events when violation levels are exceeded. It is aimed at Minecraft-style game security and staff monitoring use cases where operators need to identify likely cheaters from client-side or plugin-side observation.
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.
- 2d ago First seen · 17 lines · 39 tokens per session scan A b3dab02d8fe9
ags-anticheat is a skill published in the GitHub repository 1llu50ry/mcp-gamehacking (344 stars, last pushed 2d ago), licensed MIT. It adds 39 tokens to every session and 232 once invoked, about $0.0002 per session on Opus 5.5. 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 2026-10-23.
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