tune-performance

tune-performance is a skill for Claude Code from ouzlifaneyassine1-dot/onyx-engine. It costs 95 tokens per session (2,722 once invoked), scanned A, original, MIT.

A measurement-led guide for finding and fixing slow performance in a Godot game. It checks whether rendering, physics, game code, or startup work is causing the problem.

In plain words
What is it for?
It helps investigate frame-rate drops, freezes, long startup times, and poor performance on specific hardware, then verify whether a fix improved the measurements.
Why use it?
It replaces guesswork with diagnostics, so changes target the part of the game that is actually slowing down or stuttering.

Skill for Claude Code

Written for Claude Code: allowed-tools in frontmatter. Also seen: mentions Claude Code; mentions Codex.

Part of the onyx plugin — 77 skills, 1 command, 2 hooks, 1 MCP server shipped together

Good fit It helps investigate frame-rate drops, freezes, long startup times, and poor performance on specific hardware, then verify whether a fix improved the measurements.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/ouzlifaneyassine1-dot/onyx-engine/tune-performance
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.

Any agent
npx skills add ouzlifaneyassine1-dot/onyx-engine --skill tune-performance
Clone the repo
git clone --depth 1 https://github.com/ouzlifaneyassine1-dot/onyx-engine

Made for: Claude Code.

Or install onyx, the plugin that ships this one along with the rest of its 77 skills, 1 command, 2 hooks, 1 MCP server.

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 tune-performance

README.md
[![agentmods](https://agentmods.dev/badge/skills/ouzlifaneyassine1-dot/onyx-engine/tune-performance/github.svg)](https://agentmods.dev/skills/ouzlifaneyassine1-dot/onyx-engine/tune-performance)
Your own site
<a href="https://agentmods.dev/skills/ouzlifaneyassine1-dot/onyx-engine/tune-performance"><img src="https://agentmods.dev/badge/skills/ouzlifaneyassine1-dot/onyx-engine/tune-performance/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.

agentmods 80×15 button for tune-performance

Your own site · 80×15
<a href="https://agentmods.dev/skills/ouzlifaneyassine1-dot/onyx-engine/tune-performance"><img src="https://agentmods.dev/badge/skills/ouzlifaneyassine1-dot/onyx-engine/tune-performance.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 95 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,722 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
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 $0.00095 $0.02722
Opus 5 $0.00048 $0.01361
Sonnet 5 $0.00019 $0.00544
Haiku 4.5 $0.00010 $0.00272

Measured 10d ago against content hash 9c0b2d69f007, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-10, from the pricing page.

Security

Grade A, and why

tune-performance 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 10d 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.

skills/performance/tune-performance/SKILL.md · 220 lines

How it starts

The opening of the file, as written. The whole thing — 220 lines — stays where its author put it; the contents beside it link to each section on GitHub.

/tune-performance — Profile, Diagnose, Fix

Overview

Performance tuning without measurement is gambling. This skill enforces a measure-first loop: read diagnostics, identify the dominant cost (rendering / physics / scripting / startup), drill into the specific pattern, propose one fix, verify the metric moved. No shotgun optimization.

Core principle: the engine's diagnostics tell you which subsystem is bleeding. Don't optimize a different subsystem.

Steps

1. Get the user's symptom precisely

What's slow? Pick the closest: framerate drops in scene X / startup is long / freezes for a moment / runs fine on my machine but bad on hardware Y.

Wait. The answer narrows the fix domain by 5x:

Symptom Likely subsystem
Framerate drops as more enemies spawn Scripting (_process per-instance) or physics
Framerate is fine standing still, drops looking at level X Rendering (overdraw, draw calls, lights)
Stutter every N seconds GC pause, autoload loop, or async load
Long startup Asset import, autoload _ready work, shader compilation
Runs fine on dev machine, bad on user machine Resolution, GPU features (compute, GI), shadow quality

2. Take a baseline measurement

Don't guess. Read the engine's actual numbers.

Preferred (onyx MCP):

onyx_clear_console
onyx_play
# user reproduces the slowdown for 5–10 seconds
onyx_get_diagnostics
onyx_get_console               # check for warnings (e.g. "shader compilation hot-path")
onyx_stop

onyx_get_diagnostics returns the aggregate metrics. Note (write down before fixing anything):

  • Average FPS during the slow section
  • Frame time (ms) — anything over 16.67 ms = below 60 fps
  • Draw calls per frame
  • Active physics bodies
  • Active GPUParticles instances
  • Script time vs. physics time vs. render time

Fallback (no MCP): ask the user to enable Godot's built-in monitor (Debug → Monitor or in-game with Performance.get_monitor) and paste numbers. At minimum: FPS, frame time, draw calls, physics active objects.

Read the full file on GitHub · 220 lines

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. 10d ago First seen · 220 lines · 95 tokens per session scan A 9c0b2d69f007

Subscribe to this mod's changes

tune-performance is a skill published in the GitHub repository ouzlifaneyassine1-dot/onyx-engine (0 stars, last pushed 2mo ago), licensed MIT. It adds 95 tokens to every session and 2,722 once invoked, about $0.0005 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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