senior-devops

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更新时间2025年12月20日 02:14

Comprehensive DevOps skill for CI/CD, infrastructure automation, containerization, and cloud platforms (AWS, GCP, Azure). Includes pipeline setup, infrastructure as code, deployment automation, and monitoring. Use when setting up pipelines, deploying applications, managing infrastructure, implementing monitoring, or optimizing deployment processes.

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来源

davila7

davila7/claude-code-templates

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Senior Devops

Complete toolkit for senior devops with modern tools and best practices.

Quick Start

Main Capabilities

This skill provides three core capabilities through automated scripts:

# Script 1: Pipeline Generator
python scripts/pipeline_generator.py [options]

# Script 2: Terraform Scaffolder
python scripts/terraform_scaffolder.py [options]

# Script 3: Deployment Manager
python scripts/deployment_manager.py [options]

Core Capabilities

1. Pipeline Generator

Automated tool for pipeline generator tasks.

Features:

Automated scaffolding
Best practices built-in
Configurable templates
Quality checks

Usage:

python scripts/pipeline_generator.py <project-path> [options]

2. Terraform Scaffolder

Comprehensive analysis and optimization tool.

Features:

Deep analysis
Performance metrics
Recommendations
Automated fixes

Usage:

python scripts/terraform_scaffolder.py <target-path> [--verbose]

3. Deployment Manager

Advanced tooling for specialized tasks.

Features:

Expert-level automation
Custom configurations
Integration ready
Production-grade output

Usage:

python scripts/deployment_manager.py [arguments] [options]

Reference Documentation

Cicd Pipeline Guide

Comprehensive guide available in references/cicd_pipeline_guide.md:

Detailed patterns and practices
Code examples
Best practices
Anti-patterns to avoid
Real-world scenarios

Infrastructure As Code

Complete workflow documentation in references/infrastructure_as_code.md:

Step-by-step processes
Optimization strategies
Tool integrations
Performance tuning
Troubleshooting guide

Deployment Strategies

Technical reference guide in references/deployment_strategies.md:

Technology stack details
Configuration examples
Integration patterns
Security considerations
Scalability guidelines

Tech Stack

Languages: TypeScript, JavaScript, Python, Go, Swift, Kotlin Frontend: React, Next.js, React Native, Flutter Backend: Node.js, Express, GraphQL, REST APIs Database: PostgreSQL, Prisma, NeonDB, Supabase DevOps: Docker, Kubernetes, Terraform, GitHub Actions, CircleCI Cloud: AWS, GCP, Azure

Development Workflow

1. Setup and Configuration

# Install dependencies
npm install
# or
pip install -r requirements.txt

# Configure environment
cp .env.example .env

2. Run Quality Checks

# Use the analyzer script
python scripts/terraform_scaffolder.py .

# Review recommendations
# Apply fixes

3. Implement Best Practices

Follow the patterns and practices documented in:

references/cicd_pipeline_guide.md
references/infrastructure_as_code.md
references/deployment_strategies.md

Best Practices Summary

Code Quality

Follow established patterns
Write comprehensive tests
Document decisions
Review regularly

Performance

Measure before optimizing
Use appropriate caching
Optimize critical paths
Monitor in production

Security

Validate all inputs
Use parameterized queries
Implement proper authentication
Keep dependencies updated

Maintainability

Write clear code
Use consistent naming
Add helpful comments
Keep it simple

Common Commands

# Development
npm run dev
npm run build
npm run test
npm run lint

# Analysis
python scripts/terraform_scaffolder.py .
python scripts/deployment_manager.py --analyze

# Deployment
docker build -t app:latest .
docker-compose up -d
kubectl apply -f k8s/

Troubleshooting

Common Issues

Check the comprehensive troubleshooting section in references/deployment_strategies.md.

Getting Help

Review reference documentation
Check script output messages
Consult tech stack documentation
Review error logs

Resources

Pattern Reference: references/cicd_pipeline_guide.md
Workflow Guide: references/infrastructure_as_code.md
Technical Guide: references/deployment_strategies.md
Tool Scripts: scripts/ directory

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doordash-allergy-shield

davila7/claude-code-templates

Persistent dietary safety layer for DoorDash CLI (dd-cli) ordering. Stores a personal/household dietary profile (allergens with severity tiers, diets, dislikes) that every cart is vetted against before checkout, with a deterministic tripwire — the vetting step saves the full cart contents to a vetted-cart dump, and a PreToolUse hook re-greps that dump against the anaphylaxis-severity allergen list before any checkout URL is allowed. Use when the user mentions allergies or dietary restrictions, when ordering food for someone with restrictions, or on every dd-cli cart flow while this skill is installed. A tripwire, not medical-grade — the human checkout page is the final check.

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doordash-group-orders

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Group food ordering through the DoorDash CLI (dd-cli) from a persistent team roster. One request ("lunch for the team") fans out into a single merged cart with every line attributed to its eater via a person-to-cart-item-id ledger, per-person cost split with fee proration, payer rotation history, and a checkout gate that re-derives allergen conflicts against the roster live. Use when ordering for multiple people — team lunch, incident-response food, "collect orders from the thread" — or for /whose-turn payer rotation questions. Handles paste-a-thread intake: paste a Slack/chat thread and it builds the order ledger from it.

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doordash-order-ledger

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Accountability layer for agent-driven DoorDash ordering. Works with the doordash-audit-log hook (which appends every dd-cli invocation to an append-only audit log) and the /doordash-report command to answer "what has my AI been ordering and what did it cost" from data instead of memory. Use when the user asks about their DoorDash spending, ordering patterns, what the agent did in past sessions, or wants jq recipes for querying the audit log. Covers log schema, query patterns, rotation, and privacy guidance.

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doordash-order-playbooks

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Named, context-bound saved DoorDash orders ("post-gym", "late-night deploy") recalled through the DoorDash CLI (dd-cli) with a mandatory cart-diff before any checkout link is handed over. Use when the user names a saved order ("order my post-gym bowl", "the usual", "my Friday ramen"), wants to save the order they just placed as a playbook, or asks to list/remove saved orders. Persists name→order-uuid playbooks across sessions, catches silent menu/price drift on every recall, and self-heals stale playbooks when a restaurant's menu changes. Requires dd-cli (macOS Apple Silicon, waitlist-gated).

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doordash-spend-guard

davila7/claude-code-templates

Hard spending policy for agent-driven DoorDash ordering through the DoorDash CLI (dd-cli). Per-order ceiling, daily/weekly/monthly caps, cooldown between orders, and blocked hours — enforced deterministically by routing every cart-mutation and checkout through the dd-guard wrapper script, which prices the cart, checks the policy against a persistent spend ledger, and refuses out-of-policy checkouts with exit code 2. Use when the user wants budget limits on agent food ordering, asks "how much have I spent on DoorDash", wants to set spending caps, or whenever building carts / checking out with dd-cli while this skill is installed. Pairs with a PreToolUse hook that denies raw dd-cli checkout calls that bypass the wrapper.

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abc-xyz-segmentation

davila7/claude-code-templates

Segment a SKU portfolio on value (ABC) and demand variability (XYZ), produce the 9-box with a planning policy per cell, and reallocate planner attention accordingly. Use when the user mentions ABC analysis, inventory segmentation, SKU rationalization, stok segmentasyonu, envanter sınıflandırma, or asks which items deserve forecasting effort. Differentiator - ABC alone is treated as half an answer; policy lives in the value x variability combination.

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name	senior-devops
description	Comprehensive DevOps skill for CI/CD, infrastructure automation, containerization, and cloud platforms (AWS, GCP, Azure). Includes pipeline setup, infrastructure as code, deployment automation, and monitoring. Use when setting up pipelines, deploying applications, managing infrastructure, implementing monitoring, or optimizing deployment processes.

Senior Devops

Complete toolkit for senior devops with modern tools and best practices.

Quick Start

Main Capabilities

This skill provides three core capabilities through automated scripts:

# Script 1: Pipeline Generator
python scripts/pipeline_generator.py [options]

# Script 2: Terraform Scaffolder
python scripts/terraform_scaffolder.py [options]

# Script 3: Deployment Manager
python scripts/deployment_manager.py [options]

Core Capabilities

1. Pipeline Generator

Automated tool for pipeline generator tasks.

Features:

Automated scaffolding
Best practices built-in
Configurable templates
Quality checks

Usage:

python scripts/pipeline_generator.py <project-path> [options]

2. Terraform Scaffolder

Comprehensive analysis and optimization tool.

Features:

Deep analysis
Performance metrics
Recommendations
Automated fixes

Usage:

python scripts/terraform_scaffolder.py <target-path> [--verbose]

3. Deployment Manager

Advanced tooling for specialized tasks.

Features:

Expert-level automation
Custom configurations
Integration ready
Production-grade output

Usage:

python scripts/deployment_manager.py [arguments] [options]

Reference Documentation

Cicd Pipeline Guide

Comprehensive guide available in references/cicd_pipeline_guide.md:

Detailed patterns and practices
Code examples
Best practices
Anti-patterns to avoid
Real-world scenarios

Infrastructure As Code

Complete workflow documentation in references/infrastructure_as_code.md:

Step-by-step processes
Optimization strategies
Tool integrations
Performance tuning
Troubleshooting guide

Deployment Strategies

Technical reference guide in references/deployment_strategies.md:

Technology stack details
Configuration examples
Integration patterns
Security considerations
Scalability guidelines

Tech Stack

Development Workflow

1. Setup and Configuration

# Install dependencies
npm install
# or
pip install -r requirements.txt

# Configure environment
cp .env.example .env

2. Run Quality Checks

# Use the analyzer script
python scripts/terraform_scaffolder.py .

# Review recommendations
# Apply fixes

3. Implement Best Practices

Follow the patterns and practices documented in:

references/cicd_pipeline_guide.md
references/infrastructure_as_code.md
references/deployment_strategies.md

Best Practices Summary

Code Quality

Follow established patterns
Write comprehensive tests
Document decisions
Review regularly

Performance

Measure before optimizing
Use appropriate caching
Optimize critical paths
Monitor in production

Security

Validate all inputs
Use parameterized queries
Implement proper authentication
Keep dependencies updated

Maintainability

Write clear code
Use consistent naming
Add helpful comments
Keep it simple

Common Commands

# Development
npm run dev
npm run build
npm run test
npm run lint

# Analysis
python scripts/terraform_scaffolder.py .
python scripts/deployment_manager.py --analyze

# Deployment
docker build -t app:latest .
docker-compose up -d
kubectl apply -f k8s/

Troubleshooting

Common Issues

Check the comprehensive troubleshooting section in references/deployment_strategies.md.

Getting Help

Review reference documentation
Check script output messages
Consult tech stack documentation
Review error logs

Resources

Pattern Reference: references/cicd_pipeline_guide.md
Workflow Guide: references/infrastructure_as_code.md
Technical Guide: references/deployment_strategies.md
Tool Scripts: scripts/ directory