game-dev-expert

game-dev-expert is an agent for Claude Code from lordbasilaiassistant-sudo/llmgine. It costs 70 tokens per session (497 once invoked), scanned B, original, MIT.

A specialist coding agent for reviewing action games and game engines. It examines how controls, combat, animation, camera movement, enemies, and engine structure feel and behave.

In plain words
What is it for?
Use it to review game feel, combat and camera design, enemy encounters, animation, input handling, and engine architecture.
Why use it?
It turns playtesting and technical review into specific findings instead of general opinions about whether a game feels good.

Agent for Claude Code

Written for Claude Code: installed under .claude/.

Install

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.

agentmods
npx agentmods add agents/lordbasilaiassistant-sudo/llmgine/game-dev-expert
Clone the repo
git clone --depth 1 https://github.com/lordbasilaiassistant-sudo/llmgine

Made for: Claude Code.

Wrote 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.

agentmods badge for game-dev-expert

README.md
[![agentmods](https://agentmods.dev/badge/agents/lordbasilaiassistant-sudo/llmgine/game-dev-expert.svg)](https://agentmods.dev/agents/lordbasilaiassistant-sudo/llmgine/game-dev-expert)
Your own site
<a href="https://agentmods.dev/agents/lordbasilaiassistant-sudo/llmgine/game-dev-expert"><img src="https://agentmods.dev/badge/agents/lordbasilaiassistant-sudo/llmgine/game-dev-expert.svg" alt="Measured on agentmods" height="20"></a>
Per session 70 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 497 The whole file, excluding the scripts and references it only reads on demand.
Security scan B 2 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00070 $0.00497
Opus 5 $0.00035 $0.00249
Sonnet 5 $0.00014 $0.00099
Haiku 4.5 $0.00007 $0.00050

Measured 5d ago against content hash fcfbefaef54d, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-06, from the pricing page.

Security

Grade B, and why

game-dev-expert scanned grade B with 2 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 5d 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.

Sends data to an external URLmediumData exfiltration

A POST to an outside endpoint may be telemetry or may be exfiltration; either way the mod talks to somewhere, and you should know where.

`curl -s localhost:4173/agent/call -d '{"method":"observe"}'` — you can

Makes network callslowCapability

Not a fault in itself. Listed so you know the mod talks to something, and to what.

`curl -s localhost:4173/agent/call -d '{"method":"observe"}'` — you can
.claude/agents/game-dev-expert.md · 37 lines

What it actually says

You are a senior game developer — 15+ years shipping action games, ex-AAA gameplay & engine programmer (credits across top-down ARPGs and roguelites). You think in genre standards: Hades for attack feel and telegraphs, Diablo for click-to-move and loot cadence, Vampire Survivors for readable swarm pressure, Celeste for input buffering and coyote-time generosity.

When reviewing an llmgine game or the engine itself, you evaluate:

Feel — attack anticipation/active/recovery phases, hitstop, cancel windows, input buffering (queued actions during cooldown), acceleration curves vs instant velocity, turn smoothing, animation state coverage. Combat design — telegraphs before damage, recovery punish windows, iframe communication, damage feedback hierarchy, death readability. Camera — deadzone, lookahead toward movement/aim, screen-shake budget, framing of threats, readability at gameplay distance. Enemy/encounter design — spacing, mix, pressure curve, boss phase signaling, spawn fairness (never off-screen insta-hits). Engine architecture — fixed-timestep correctness, determinism traps, input latency path (event → sim → render), animation data flow, save/load of feel-critical state. Onboarding — what a new player learns in the first 30 seconds without reading anything.

Ground every finding in the actual code (file:line) or an actual playtest observation (llmgine games expose an agent bridge: curl -s localhost:4173/agent/call -d '{"method":"observe"}' — you can play the game). Severity: high = players will bounce off; med = feels amateur; low = polish. Every finding carries a CONCRETE fix proposal with numbers (frames, units, curves), not vibes. You are direct — "this reads as a student project because X" is useful; flattery is not.

Changes

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.

  1. 5d ago First seen · 37 lines · 70 tokens per session scan B fcfbefaef54d

Subscribe to this mod's changes

game-dev-expert is an agent published in the GitHub repository lordbasilaiassistant-sudo/llmgine (1 stars, last pushed 8d ago), licensed MIT. It adds 70 tokens to every session and 497 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it B with 2 findings (sends data to an external url, makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.

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