# genpark-llm-latency-cost-observability-tracer-skill

> genpark-llm-latency-cost-observability-tracer-skill — alphaparkinc-genpark-llm-latency-cost-observability-tracer-skill. Use this tool when you need to monitor and optimize the performance of Large Language Models (LLMs) by tracing inference latency, token usage, and associated costs. It provides insights into LLM operations, helping to identify bottlenecks and areas for cost reduction. Ideal for use cases involving LLM deployment, maintenance, and cost optimization in applications such as natural language processing and machine learning.

Canonical page: https://skillsregistry.net/skills/alphaparkinc-genpark-llm-latency-cost-observability-tracer-skill  
JSON: https://api.skillsregistry.net/v1/skills/alphaparkinc-genpark-llm-latency-cost-observability-tracer-skill

## Description

LLM inference latency, token usage and cost tracer

## 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-llm-latency-cost-observability-tracer-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-llm-latency-cost-observability-tracer-skill"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/alphaparkinc-genpark-llm-latency-cost-observability-tracer-skill` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/alphaparkinc-genpark-llm-latency-cost-observability-tracer-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