# genpark-paged-attention-kv-cache-budget-calculator-skill

> genpark-paged-attention-kv-cache-budget-calculator-skill — alphaparkinc-genpark-paged-attention-kv-cache-budget-calculator-skill. Use this tool when you need to optimize GPU memory allocation and KV cache budget for large language models (LLMs) with PagedAttention. It solves problems related to memory management and performance optimization by providing a calculator for chunked prefill KV cache and GPU memory allocation. The tool takes input parameters such as model size and output requirements, and provides output recommendations for optimal cache and memory allocation.

Canonical page: https://skillsregistry.net/skills/alphaparkinc-genpark-paged-attention-kv-cache-budget-calculator-skill  
JSON: https://api.skillsregistry.net/v1/skills/alphaparkinc-genpark-paged-attention-kv-cache-budget-calculator-skill

## Description

PagedAttention chunked prefill KV cache & GPU memory allocator (vLLM)

## Trust

- **Trust score (0–1):** 1.00
- **Verification tier:** verified
- **Last scanned:** 2026-09-28

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** container
- **Runtime environment:** vm
- **Updated:** 2026-09-28

## Source

- **Source listing:** [GitHub](https://github.com/alphaparkinc/genpark-paged-attention-kv-cache-budget-calculator-skill)

## Use it

Resolve this record through the SkillsRegistry MCP server (no auth, read-only):

```
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp
```

```json
{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "get_skill",
    "arguments": {
      "slug": "alphaparkinc-genpark-paged-attention-kv-cache-budget-calculator-skill"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/alphaparkinc-genpark-paged-attention-kv-cache-budget-calculator-skill` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/alphaparkinc-genpark-paged-attention-kv-cache-budget-calculator-skill/pull`

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SkillsRegistry indexes agent skills from public registries and GitHub. Skills we have analysed are scanned with Circle-IR and scored on six dimensions; each listing states its scan coverage. More: https://skillsregistry.net/llms.txt