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 makifbaysal/tasktrooper --skill other-engines-quickrefgit clone --depth 1 https://github.com/makifbaysal/tasktrooperWrote 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/makifbaysal/tasktrooper/other-engines-quickref)<a href="https://agentmods.dev/skills/makifbaysal/tasktrooper/other-engines-quickref"><img src="https://agentmods.dev/badge/skills/makifbaysal/tasktrooper/other-engines-quickref/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/makifbaysal/tasktrooper/other-engines-quickref"><img src="https://agentmods.dev/badge/skills/makifbaysal/tasktrooper/other-engines-quickref.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 | $0.00076 | $0.01902 |
| Opus 5.5 | $0.00030 | $0.00761 |
| Sonnet 5.5 | $0.00015 | $0.00380 |
| Haiku 4.5 | $0.00008 | $0.00190 |
Grade A, and why
other-engines-quickref 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 4d 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 — 106 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Other Engines Quick Reference
Overview
Smaller engines follow the same rules as the big ones — fixed-step simulation, delta-scaled time, rules in testable plain modules, no allocations per frame, data out of code — with their own lifecycle names and tools. Find the engine's conventions in the repository first; this page is the map when they are thin.
Core principle: Same discipline, local vocabulary. Identify the loop callback and its delta unit, put rules in plain modules the language's test runner can import, and find the command that builds and runs headless.
At a glance
| Engine | Language | Per-frame callback, delta unit | Fixed step | Rules tested with | Headless build / run | Frame capture |
|---|---|---|---|---|---|---|
| Defold | Lua | update(self, dt) — seconds |
fixed_update(self, dt) when enabled in game.project |
plain Lua modules + the repo's runner (busted, or an in-engine runner such as deftest/telescope) | java -jar bob.jar --platform <platform> resolve build; dmengine_headless for in-engine tests |
screenshot extension, or none headless |
| MonoGame | C# | Update(GameTime) — gameTime.ElapsedGameTime.TotalSeconds |
IsFixedTimeStep = true (default), TargetElapsedTime |
class library + xUnit/NUnit, dotnet test |
dotnet build; content via dotnet mgcb / the .mgcb project |
RenderTarget2D → SaveAsPng (needs a graphics device) |
| pygame / pygame-ce | Python | your loop: dt = clock.tick(60) / 1000 — seconds |
your accumulator | pytest | SDL_VIDEODRIVER=dummy SDL_AUDIODRIVER=dummy python -m game --frames 120 |
pygame.image.save(screen, path) — works headless |
| Excalibur | TypeScript | onPreUpdate(engine, elapsed) — milliseconds |
the engine's fixed-update option (fixedUpdateFps in recent versions) |
Vitest | npm run build; browser for running |
browser tools / Playwright |
| KAPLAY | JS/TS | onUpdate(() => ...) with dt() — seconds |
the engine's fixed update for body() physics |
Vitest on modules outside the kaplay() context |
npm run build; browser for running |
browser tools / Playwright |
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.
- 4d ago First seen · 106 lines · 76 tokens per session scan A e722aecc1db2
other-engines-quickref is a skill published in the GitHub repository makifbaysal/tasktrooper (113 stars, last pushed yesterday), licensed Apache-2.0. It adds 76 tokens to every session and 1,902 once invoked, about $0.0003 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 2026-10-09.
Other skills, from other repositories
i4h-workflow-train-rl
Use when training, evaluating, or exporting Workflow policies with online RSL-RL or RLinf, including RL checkpoint and Workflow handoff.
openclaw-plugin
You are an autonomous agent in a persistent world. Your character is in SOUL.md. World rules are in WORLD.md.
ramp
Fetch and follow Ramp's published agent playbooks inside Paperclip, with mandatory approval gates for spend, incorporation, cards, account setup, and other financial actions.
github-pr-workflow
Prepare a GitHub pull request from a feature branch — branch hygiene, commit shape, title/body, verification notes, screenshots for UI work, and replies to review comments.
agent-topology-optimizer
Agent skill for topology-optimizer - invoke with $agent-topology-optimizer.
paperclip-task-bridge
Create, comment on, update, and list Paperclip tasks from Hermes using scoped Paperclip API credentials.