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fizz-production
Enables Copilot to SSH into the Fizz EC2 instance and manage Docker containers for the fyzz.dev production app.
用 Codex 或 Claude 帮你安装 复制这段 Prompt,粘贴到 Codex、Claude 或其他助手里,让它检查 Skill 页面并帮你完成安装。
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Enables Copilot to SSH into the Fizz EC2 instance and manage Docker containers for the fyzz.dev production app.
用 Codex 或 Claude 帮你安装 复制这段 Prompt,粘贴到 Codex、Claude 或其他助手里,让它检查 Skill 页面并帮你完成安装。
基于 SOC 职业分类
Common patterns and workflows for Azure DevOps and database queries. Use to avoid inefficient searches and tangents.
Retrieve complete details for specific Azure DevOps work items by ID, including all fields, comments, change history, and related items. Use when the user asks about a specific ticket number or needs full context on a work item. PAT token in .env file at network/.env.
Search for Azure DevOps work items using text search and filters. Use when the user asks to find tickets, work items, issues, bugs, or user stories by keyword, state, assignment, tags, or area. PAT token in .env file at network/.env.
Navigate and understand the EvaAPI codebase structure. Use when searching for models, services, controllers, migrations, or any code related to Eva database entities. Helps locate where specific features are implemented.
Query and analyze the Eva QA database using PowerShell functions. Use when working with Eva sessions, committee reports, meeting notices, or any Eva application data in the QA environment.
Generate markdown reports of work items with optional details like acceptance criteria, descriptions, and comments. Use when creating sprint summaries, feature overviews, or documenting requirements.
| name | fizz-production |
| description | Enables Copilot to SSH into the Fizz EC2 instance and manage Docker containers for the fyzz.dev production app. |
This skill enables you to manage the Fizz lead generation application running on AWS EC2.
Fizz is a Next.js application deployed on EC2 with the following components:
fizz-worker-discovery: Lead discoveryfizz-worker-screenshots: Website screenshotsfizz-worker-lighthouse: Performance analysisfizz-worker-vision: AI vision analysisfizz-worker-sections: Section extractionfizz-worker-email: Email generationfizz-worker-followup: Follow-up email handlingFirst, import the module:
Import-Module .\FizzAws.psm1
Connect to the server:
Connect-FizzServer
View container status:
Get-FizzContainers
Get-FizzHealth
View logs:
Get-FizzLogs -Container app -Tail 100
Get-FizzLogs -Container worker-discovery -Follow
Watch-FizzLogs # All containers
Debug errors:
Get-FizzErrors
Get-FizzStats
Restart containers:
Restart-FizzContainer -Container app
Invoke-FizzCompose -Action restart
Enter container shell:
Enter-FizzContainer -Container app
Enter-FizzContainer -Container postgres -Shell /bin/bash
Run commands in containers:
Invoke-FizzDocker -Container app -Command "npx prisma studio"
Invoke-FizzDocker -Container postgres -Command "psql -U fizz -d fizz"
When investigating production issues:
Get-FizzHealthGet-FizzErrorsGet-FizzLogs -Container <name>Test-FizzDatabaseGet-FizzStatsThe app uses these key environment variables:
DATABASE_URL: PostgreSQL connection stringREDIS_URL: Redis connection stringANTHROPIC_API_KEY: For AI featuresSERPAPI_API_KEY: For search functionalityPAGESPEED_API_KEY: For Lighthouse analysisAUTH_SECRET: Authentication secretSMARTLEAD_API_KEY: For email campaigns