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-airtestgit 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-airtest)<a href="https://agentmods.dev/skills/1llu50ry/mcp-gamehacking/ags-airtest"><img src="https://agentmods.dev/badge/skills/1llu50ry/mcp-gamehacking/ags-airtest/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-airtest"><img src="https://agentmods.dev/badge/skills/1llu50ry/mcp-gamehacking/ags-airtest.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 | $0.00038 | $0.00201 |
| Opus 5.5 | $0.00015 | $0.00080 |
| Sonnet 5.5 | $0.00008 | $0.00040 |
| Haiku 4.5 | $0.00004 | $0.00020 |
Grade A, and why
ags-airtest 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
Airtest
Author: AirtestProject Source: mcp-gamehacking/skills/ags-airtest
Description
This project is a cross-platform UI automation framework for games and mobile apps. It is primarily written in Python and uses image recognition to locate UI elements without injecting into the target process. The framework provides device control APIs, scalable execution on device farms, command-line and Python interfaces, HTML reporting, and integration with an IDE and object-hierarchy tooling for advanced UI interaction. It is mainly used by QA engineers and game or app teams that need repeatable end-to-end automation across Android, iOS, and desktop environments.
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 · 38 tokens per session scan A a0f7abf1cecf
ags-airtest is a skill published in the GitHub repository 1llu50ry/mcp-gamehacking (344 stars, last pushed 2d ago), licensed MIT. It adds 38 tokens to every session and 201 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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