# Performance Budgeting

> Set and manage frame, load, memory, streaming, or bandwidth budgets before performance debt becomes structural.

- **Type:** Skill
- **Install:** `agentstack add skill-mrcalderon3d-everything-game-dev-code-performance-budgeting`
- **Verified:** Yes — security-reviewed for prompt injection and unsafe behavior
- **Seller:** [MRCalderon3D](https://agentstack.voostack.com/s/mrcalderon3d)
- **Installs:** 0
- **Category:** [Agent Skills](https://agentstack.voostack.com/c/agent-skills)
- **Latest version:** 0.1.0
- **License:** MIT
- **Upstream author:** [MRCalderon3D](https://github.com/MRCalderon3D)
- **Source:** https://github.com/MRCalderon3D/everything-game-dev-code/tree/main/skills/engineering-common/performance-budgeting

## Install

```sh
agentstack add skill-mrcalderon3d-everything-game-dev-code-performance-budgeting
```

Requires the [AgentStack CLI](https://agentstack.voostack.com/docs/cli). Works with Claude Code, Cursor, and any MCP-compatible agent.

## About

# Performance Budgeting

## Purpose
Set and manage frame, load, memory, streaming, or bandwidth budgets before performance debt becomes structural.

## Use When
- target hardware is defined
- performance problems are emerging
- content scale is increasing

## Inputs
- target platforms
- feature set
- technical architecture
- content assumptions

## Process
1. set budgets by platform and major runtime mode
2. allocate budget ownership by system or content class
3. choose representative benchmark scenarios
4. review regressions at milestone checkpoints
5. link descopes or optimization work to measured overages

## Outputs
- budget sheet
- owner-by-budget map
- benchmark scenarios
- regression review cadence

## Quality Bar
- budgets are set per system (frame time, memory, draw calls, asset sizes) against the weakest target device
- every budget has an owner and a repeatable measurement method
- regressions are caught by measurement at integration time, not discovered in QA
- budget exceptions are negotiated and recorded, not silently absorbed

## Common Failure Modes
- budgets defined as totals with no per-system allocation, so no one owns overruns
- profiling only on developer hardware, missing the real target floor
- performance treated as a polish-phase task instead of a standing budget
- one-off optimizations that decay because no measurement guards them

## Related Agents
- performance-reviewer
- producer
- technical-artist

## Related Commands
- perf-budget
- verify
- release-check

## Notes
- Keep this skill aligned with the relevant rules layer and current project documentation.
- If engine-specific constraints materially change the workflow, hand off to the matching engine skill or engine-specific reviewer.

## Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

- **Author:** [MRCalderon3D](https://github.com/MRCalderon3D)
- **Source:** [MRCalderon3D/everything-game-dev-code](https://github.com/MRCalderon3D/everything-game-dev-code)
- **License:** MIT

Install and usage instructions live in the source repository linked above.

## Pricing

- **Free** — Free

## Security capabilities

Automated source analysis of v0.1.0 — what this tool can access:

- **Network access:** no
- **Filesystem access:** no
- **Shell / process execution:** no
- **Environment & secrets:** no
- **Dynamic code execution:** no

*"Yes" means the capability is present in the source — more access means more to trust, not that it is unsafe.*


## Versions

- **0.1.0** — security scan: passed — Imported from the upstream source.

## Links

- Listing page: https://agentstack.voostack.com/l/skill-mrcalderon3d-everything-game-dev-code-performance-budgeting
- Seller: https://agentstack.voostack.com/s/mrcalderon3d
- Browse the marketplace: https://agentstack.voostack.com/browse

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Listed on AgentStack — the marketplace for AI agent skills and MCP servers. Every listing is security-reviewed. Creators keep 70%.