bevy-diagnostics-profiling

bevy-diagnostics-profiling is a skill for Claude Code from chrisgliddon/bevy-skills. It costs 66 tokens per session (1,320 once invoked), scanned A, original, MIT.

A Bevy 0.19 guide for measuring game performance over time and tracing where CPU, GPU, rendering, queues, and worker tasks spend time.

In plain words
What is it for?
Use it to add custom performance metrics, measure render-pass timing, monitor queues and uploads, count outdated results, and check native, Steam Deck, or WebGPU limits.
Why use it?
It helps replace guesses about slowdowns with evidence from several kinds of measurements, including cases where CPU and GPU results disagree.

Skill for Claude Code

Written for Claude Code: shipped in a Claude Code plugin. Also seen: mentions OpenCode.

Part of the bevy-skills plugin — 31 skills shipped together

Good fit Use it to add custom performance metrics, measure render-pass timing, monitor queues and uploads, count outdated results, and check native, Steam Deck, or WebGPU limits.

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Install with agentmods
npx agentmods add skills/chrisgliddon/bevy-skills/bevy-diagnostics-profiling
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 chrisgliddon/bevy-skills --skill bevy-diagnostics-profiling
Clone the repo
git clone --depth 1 https://github.com/chrisgliddon/bevy-skills

Made for: Claude Code.

Or install bevy-skills, the plugin that ships this one along with the rest of its 31 skills.

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 bevy-diagnostics-profiling

README.md
[![agentmods](https://agentmods.dev/badge/skills/chrisgliddon/bevy-skills/bevy-diagnostics-profiling/github.svg)](https://agentmods.dev/skills/chrisgliddon/bevy-skills/bevy-diagnostics-profiling)
Your own site
<a href="https://agentmods.dev/skills/chrisgliddon/bevy-skills/bevy-diagnostics-profiling"><img src="https://agentmods.dev/badge/skills/chrisgliddon/bevy-skills/bevy-diagnostics-profiling/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 bevy-diagnostics-profiling

Your own site · 80×15
<a href="https://agentmods.dev/skills/chrisgliddon/bevy-skills/bevy-diagnostics-profiling"><img src="https://agentmods.dev/badge/skills/chrisgliddon/bevy-skills/bevy-diagnostics-profiling.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 66 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,320 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. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
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 $0.00066 $0.01320
Opus 5 $0.00033 $0.00660
Sonnet 5 $0.00013 $0.00264
Haiku 4.5 $0.00007 $0.00132

Measured 9d ago against content hash abef857206f3, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-09, from the pricing page.

Security

Grade A, and why

bevy-diagnostics-profiling 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 9d 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/bevy-diagnostics-profiling/SKILL.md · 144 lines

How it starts

The opening of the file, as written. The whole thing — 144 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Bevy 0.19 — diagnostics and profiling

When to use this skill

  • A frame, render pass, worker pipeline, or upload path needs causal evidence.
  • A queue/task system needs stable gauges, counters, latency, and high-water marks.
  • Performance claims must pass native, Steam Deck, or browser acceptance budgets.
  • Render GPU diagnostics are absent or disagree with CPU traces.

Diagnostics answer “what is happening over time?” Tracing answers “where did this execution spend time?” Render diagnostics expose pass-level renderer measurements. Use all three, but do not treat any one of them as proof of a bottleneck.

Canonical pattern

use bevy::{
    diagnostic::{
        Diagnostic, DiagnosticPath, Diagnostics, RegisterDiagnostic,
    },
    prelude::*,
};

const REMESH_QUEUE_DEPTH: DiagnosticPath =
    DiagnosticPath::const_new("voxel/remesh_queue_depth");

#[derive(Resource, Default)]
struct RemeshQueue {
    valid_jobs: usize,
}

struct VoxelDiagnosticsPlugin;

impl Plugin for VoxelDiagnosticsPlugin {
    fn build(&self, app: &mut App) {
        app.init_resource::<RemeshQueue>()
            .register_diagnostic(
                Diagnostic::new(REMESH_QUEUE_DEPTH).with_suffix(" sections"),
            )
            .add_systems(Update, record_voxel_diagnostics);
    }
}

fn record_voxel_diagnostics(
    queue: Res<RemeshQueue>,
    mut diagnostics: Diagnostics,
) {
    diagnostics.add_measurement(&REMESH_QUEUE_DEPTH, || queue.valid_jobs as f64);
}

Paths are an API: use namespaced, stable names with explicit units in suffixes or documentation. Register before recording. DiagnosticsStore provides latest and historical/smoothed values for displays and exporters. Measurements are deferred telemetry, not a same-system synchronisation mechanism.

Built-in plugins

  • FrameTimeDiagnosticsPlugin: FPS, frame time, and frame count.
  • EntityCountDiagnosticsPlugin: live entity count.
  • SystemInformationDiagnosticsPlugin: process/system CPU and memory on supported native targets. It is unavailable/no-op for WASM, iOS, and dynamic-link builds.
  • LogDiagnosticsPlugin: development output; filter paths and cadence to avoid noise.
  • RenderDiagnosticsPlugin: CPU/GPU time per recorded render span and pipeline statistics where the backend supports them.

Read the full file on GitHub · 144 lines

Files

What ships with it

3 files 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.

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. 9d ago First seen · 144 lines · 66 tokens per session scan A abef857206f3

Subscribe to this mod's changes

bevy-diagnostics-profiling is a skill published in the GitHub repository chrisgliddon/bevy-skills (11 stars, last pushed 15d ago), licensed MIT. It adds 66 tokens to every session and 1,320 once invoked, about $0.0003 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.