From coreweave-pack
Handle CoreWeave API and GPU quota limits. Use when hitting quota limits, managing GPU resource allocation, or implementing request queuing for inference endpoints. Trigger with phrases like "coreweave quota", "coreweave limits", "coreweave gpu allocation", "coreweave throttle".
npx claudepluginhub flight505/skill-forge --plugin coreweave-packThis skill is limited to using the following tools:
CoreWeave limits are primarily GPU quota-based rather than API rate limits. Each namespace has allocated GPU quotas per type.
Guides Next.js Cache Components and Partial Prerendering (PPR): 'use cache' directives, cacheLife(), cacheTag(), revalidateTag() for caching, invalidation, static/dynamic optimization. Auto-activates on cacheComponents: true.
Guides building MCP servers enabling LLMs to interact with external services via tools. Covers best practices, TypeScript/Node (MCP SDK), Python (FastMCP).
Share bugs, ideas, or general feedback.
CoreWeave limits are primarily GPU quota-based rather than API rate limits. Each namespace has allocated GPU quotas per type.
kubectl describe resourcequota -n my-namespace
kubectl get resourcequota -o json | jq '.items[].status'
import asyncio
from collections import deque
class InferenceQueue:
def __init__(self, max_concurrent: int = 10):
self.semaphore = asyncio.Semaphore(max_concurrent)
self.queue_depth = 0
async def inference(self, client, prompt: str) -> str:
self.queue_depth += 1
async with self.semaphore:
try:
return await asyncio.to_thread(client.generate, prompt)
finally:
self.queue_depth -= 1
For security, see coreweave-security-basics.