performance-budget
Skill12 starsChanged 23 days agoMITView on GitHub
Use when a project needs explicit frame-time, memory, latency, loading, or frame-pacing targets per platform before optimization decisions can be judged.
4 other projects use a version of this.
Adopted by
Most recently taken up by
- Mozurok/fhorja.devtheir own version, first seen Oct 8, 2026
- LeonxLJX/web-engineer-skillstheir own version, first seen Sep 3, 2026
- Abdox-menara/guard-skillstheir own version, first seen Aug 24, 2026
- charanjit-singh/lovable-skillstheir own version, first seen May 22, 2026
Other versions4 projects use a version of this.
Word for word · 0
None found.
Edited · 0
None found.
Wrote their own version · 4
- charanjit-singh/lovable-skills★ 10same name
- Mozurok/fhorja.dev★ 10same name
- Abdox-menara/guard-skills★ 0same name
- LeonxLJX/web-engineer-skills★ 0same name
How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.
In this repository194 other files it gives its agents.
- llms.txtllms.txt
- hd-sprite-sequenceSkill
- pixel-animationSkill
- skin-weightsSkill
- spine-skeletalSkill
- sprite-atlasSkill
- sprite-catalogSkill
- sprite-skinSkill
- art-bibleSkill
- asset-pack-intakeSkill
- character-rigSkill
- materialsSkill
- model-pipelineSkill
- open-asset-fixtureSkill
- vfx-generateSkill
- a11y-controlsSkill
- ability-gateSkill
- action-feelSkill
- ad-breakSkill
- adventure-toolSkill
- aggro-tableSkill
- aim-assistSkill
- ammo-reloadSkill
- analytics-funnelSkill
- animation-blendSkill
- animation-graphSkill
- asset-runtimeSkill
- attack-tellSkill
- audio-busesSkill
- audio-feelSkill
- avatar-createSkill
- balance-designSkill
- boss-designSkill
- browser-inputSkill
- camera-anti-clipSkill
- camera-modestySkill
- camera-shotsSkill
- cert-handoffSkill
- chemistry-verbsSkill
- climb-vaultSkill
- cloud-saveSkill
- collision-layersSkill
- combo-designSkill
- cover-shooterSkill
- cover-spaceSkill
- crafting-loopSkill
- currency-dualSkill
- cutscene-handoffSkill
- day-nightSkill
- death-carrySkill
- debug-slateSkill
- deck-buildSkill
- dialogue-beatSkill
- dialogue-flagsSkill
- difficulty-designSkill
- dodge-iframeSkill
- durability-economySkill
- encounter-designSkill
- enemy-aiSkill
- enemy-fireSkill
- The first 60 shown.
The file
We split this skill into the rules it gives an agent
1 rule. 0 are common, 1 is distinctive, and 0 are very specific to this project.
0
Common
Most of the 3 edited versions we read keep these.
1
Distinctive
This author's own choices. Worth a look.
0
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Distinctive: line 12
Do not hardcode one simulation rate for every project.
“Common” is measured: kept by at least 6 in 10 of the 3 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
Performance budget
This skill owns targets and measurement contracts. performance-optimization owns diagnosis and changes used to meet them.
Budget columns
Do not hardcode one simulation rate for every project. Publish the actual project clocks and presentation targets.
| Example mode | Presentation target | Simulation contract |
| stable-60 | 60 Hz target | project-selected fixed/variable simulation documented separately |
| stable-30 | 30 Hz target | simulation rate remains an explicit project decision |
| unlocked-floor | uncapped/VRR with floor | simulation contract unchanged by display refresh |
| multi-profile | per-device quality profiles | same gameplay rules; clocks listed explicitly |
Metrics
A useful budget includes more than average FPS:
- CPU main-thread and worker critical-path time;
- GPU frame time at a named resolution/settings profile;
- frame-time p50 / p95 / p99 (or published percentile set) and worst hitches;
- frame pacing / missed-present rate;
- input-to-visible-response latency when feel is latency-sensitive;
- allocation/GC stalls, memory resident peak and memory trend;
- streaming/IO latency and loading hitches.
CPU and GPU work may overlap, so do not add independent CPU/GPU numbers as if they were automatically serial. Name the critical path and presentation cadence.
A fixed gameplay tick can preserve logical timing while 30 Hz and 60 Hz rendering still differ in presentation latency, visual sampling and frame pacing. Do not claim identical feel solely because logical state is identical.
Measurement contract
Pin device, build configuration, scene/route, resolution, quality settings, backend/API, capture duration and warm-up. Report percentiles and sample count/window. Compare like with like; a one-scene gain is not a global budget result.
Record focus/visibility state with each capture. Frame-time evidence taken while the window, tab or app is backgrounded, minimized, occluded or otherwise throttled is invalid. When feel depends on presentation density, include a burst of simultaneous effects and voices in the representative route, and report first-use costs (decode, synthesis, cache fill) as hitches rather than averaging them away.
Acceptance
Run the representative route on every shipping performance profile. Confirm published percentile/frame-pacing/latency/memory targets and record the specific failing bucket when a target misses. Logic outcomes may remain deterministic across render profiles, but presentation latency differences are reported rather than hidden. Unmeasured platforms remain not-run.
Does it work?
Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.
No reviews yet
People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.
- It worked
- Partly
- It didn't
Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.
Your trail
Files you open will collect here, so you can find them again.
Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.
Now do this for your own.
Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.

