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inference-latency-profiler

Profile inference latency profiler operations. Auto-activating skill for ML Deployment. Triggers on: inference latency profiler, inference latency profiler Part of the ML Deployment skill category. Use when working with inference latency profiler functionality. Trigger with phrases like "inference latency profiler", "inference profiler", "inference".

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ソース情報

リポジトリ
RunnerQuan/SAFE-Agent
ソースの最終更新活動
2026年3月30日 04:33
検出された SKILL.md の言語
英語
スター
0
フォーク
0

インストール方法

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ファイルエクスプローラー
3 ファイル

SKILL.md を表示中

SKILL.md
ソースの指示 · 読み取り専用プレビュー
name
inference-latency-profiler
description
Profile inference latency profiler operations. Auto-activating skill for ML Deployment. Triggers on: inference latency profiler, inference latency profiler Part of the ML Deployment skill category. Use when working with inference latency profiler functionality. Trigger with phrases like "inference latency profiler", "inference profiler", "inference".
allowed-tools
Read, Write, Edit, Bash(cmd:*), Grep
version
1.0.0
license
MIT
author
Jeremy Longshore <jeremy@intentsolutions.io>
# Inference Latency Profiler ## Overview This skill provides automated assistance for inference latency profiler tasks within the ML Deployment domain. ## When to Use This skill activates automatically when you: - Mention "inference latency profiler" in your request - Ask about inference latency profiler patterns or best practices - Need help with machine learning deployment skills covering model serving, mlops pipelines, monitoring, and production optimization. ## Instructions 1. Provides step-by-step guidance for inference latency profiler 2. Follows industry best practices and patterns 3. Generates production-ready code and configurations 4. Validates outputs against common standards ## Examples **Example: Basic Usage** Request: "Help me with inference latency profiler" Result: Provides step-by-step guidance and generates appropriate configurations ## Prerequisites - Relevant development environment configured - Access to necessary tools and services - Basic understanding of ml deployment concepts ## Output - Generated configurations and code - Best practice recommendations - Validation results ## Error Handling | Error | Cause | Solution | |-------|-------|----------| | Configuration invalid | Missing required fields | Check documentation for required parameters | | Tool not found | Dependency not installed | Install required tools per prerequisites | | Permission denied | Insufficient access | Verify credentials and permissions | ## Resources - Official documentation for related tools - Best practices guides - Community examples and tutorials ## Related Skills Part of the **ML Deployment** skill category. Tags: mlops, serving, inference, monitoring, production
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