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 frabcd/codex-ai-game-studio --skill engine-automationgit clone --depth 1 https://github.com/frabcd/codex-ai-game-studioWrote 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/frabcd/codex-ai-game-studio/engine-automation)<a href="https://agentmods.dev/skills/frabcd/codex-ai-game-studio/engine-automation"><img src="https://agentmods.dev/badge/skills/frabcd/codex-ai-game-studio/engine-automation.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 | $0.00030 | $0.00463 |
| Opus 5 | $0.00015 | $0.00231 |
| Sonnet 5 | $0.00006 | $0.00093 |
| Haiku 4.5 | $0.00003 | $0.00046 |
Grade A, and why
engine-automation 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 6d 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.
How it starts
The opening of the file, as written. The whole thing — 59 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Engine Automation
Outcome
Route an approved operation to the correct editor adapter while preserving user control and rollback.
Required inputs
- host application and project
- desired operation
- selected pack, exact upstream pin, permissions, and rollback expectations
Ask for missing information only when it changes the route materially. Otherwise state conservative assumptions and proceed with read-only analysis.
Workflow
- Run read-only host and project detection and inventory existing MCP configurations.
- Refuse ambiguous host selection or multiple active servers for the same application.
- Prepare a transaction with exact commands, files, process and network permissions, health checks, backups, rollback, expiry, and digest.
- Show the plan and wait for explicit confirmation of its digest.
- After confirmation, apply only the listed actions, run health checks, and stop on the first divergence.
- Record the resulting lock state and tested rollback path.
Expected artifacts
- approved transaction
- backup inventory
- health-check result
- lock update
- rollback report
Workflow-specific gates
- Never install, enable, launch, configure, or control an editor implicitly.
- Only one MCP server per host application may be active.
- A digest mismatch, expired plan, changed environment, or failed backup invalidates apply and requires a new plan.
Production completion gate
Before recommending production use, complete and report all seven gates:
- Rights, consent, code/model/dataset/output license, and generation-provenance checks.
- Technical format, naming, scale, color, metadata, and target-import validation.
- Visual and temporal consistency review across representative views and states.
- Runtime memory, frame-time, draw-call, streaming, and asset-budget checks.
- Playability and interaction smoke tests in the target runtime.
- Screenshot, capture, diff, or artifact-regression evidence with reproducible settings.
- Human approval before replacing source assets or promoting generated output.
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.
- 6d ago First seen · 59 lines · 30 tokens per session scan A c9f485f4d15c
engine-automation is a skill published in the GitHub repository frabcd/codex-ai-game-studio (9 stars, last pushed 6d ago), licensed MIT. It adds 30 tokens to every session and 463 once invoked, about $0.0002 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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