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-amicegit 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-amice)<a href="https://agentmods.dev/skills/1llu50ry/mcp-gamehacking/ags-amice"><img src="https://agentmods.dev/badge/skills/1llu50ry/mcp-gamehacking/ags-amice/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-amice"><img src="https://agentmods.dev/badge/skills/1llu50ry/mcp-gamehacking/ags-amice.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 | $0.00049 | $0.00272 |
| Opus 5.5 | $0.00020 | $0.00109 |
| Sonnet 5.5 | $0.00010 | $0.00054 |
| Haiku 4.5 | $0.00005 | $0.00027 |
Grade A, and why
ags-amice 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
amice
Author: fuqiuluo Source: mcp-gamehacking/skills/ags-amice
Description
Amice is an LLVM pass plugin written in Rust that loads into the compiler via clang -fpass-plugin and applies compile-time obfuscation to LLVM IR from C/C++, Rust, and other LLVM-based languages. It implements a broad set of protection transforms including string encryption, control-flow flattening, bogus control flow, mixed boolean-arithmetic (MBA) rewriting, indirect calls and branches, basic-block splitting and shuffling, and instruction-level virtual machine protection (VMP). The project is built with llvm-plugin-rs and inkwell, supports LLVM 11 through 22, and includes Android NDK integration for mobile builds. It is aimed at developers who need to harden native binaries against reverse engineering, tampering, and static analysis in game security, software protection, and anti-cheat contexts.
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 · 49 tokens per session scan A cc293680c8b3
ags-amice is a skill published in the GitHub repository 1llu50ry/mcp-gamehacking (344 stars, last pushed 2d ago), licensed MIT. It adds 49 tokens to every session and 272 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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