canary-deployment
🎯Skillfrom aj-geddes/useful-ai-prompts
|Automates gradual rollout of software updates by deploying to a small subset of servers first to detect potential issues before full-scale deployment.
Installation
npx skills add https://github.com/aj-geddes/useful-ai-prompts --skill canary-deploymentSkill Details
Overview
# Useful AI Prompts - Production-Ready AI Prompt Library
[](https://smithery.ai/skills?ns=aj-geddes&utm_source=github&utm_medium=badge)
[](https://github.com/aj-geddes/useful-ai-prompts)
[](LICENSE)
[](prompts/)
[](skills/)
[](hooks/)
> 488 production-ready AI prompts, all following a standardized template with validated quality gates.
Transform ChatGPT, Claude, and other AI assistants into expert consultants. Every prompt in this library passes 11 quality validation checks, ensuring consistent structure, clear deliverables, and measurable quality criteria.
---
What's Inside
| Resource Type | Count | Description |
|--------------|-------|-------------|
| [AI Prompts](prompts/) | 488+ | Standardized expert prompts across 47 categories |
| [Claude Code Skills](skills/) | 260+ | Auto-triggering capabilities with code examples |
| [Automation Hooks](hooks/) | 7 | Security, testing, formatting, and CI/CD automation |
---
Standardized Prompt Format
Every prompt follows the same validated structure:
```markdown
# [Prompt Name]
Metadata
- ID:
category-prompt-slug - Version: 1.0.0
- Category: Primary category
- Tags: searchable, keywords, here
- Complexity: simple | intermediate | advanced
- Interaction: single-shot | conversational | iterative
- Models: Claude 3+, GPT-4+
Overview
2-3 sentences explaining what the prompt does and who it's for.
When to Use
- Specific scenario 1
- Specific scenario 2
Don't use for: Anti-patterns where this prompt isn't appropriate
---
Prompt
Required: Must-have inputs
Optional: Inferred defaults when not provided
Clear steps (3-7) for what to accomplish
Format, length, and structure requirements
Measurable standards for excellent output
Hard boundaries and limitations
---
Example Usage
Input
Realistic user request (20-200 words)
Output
Representative response demonstrating quality (100-600 words)
Related Prompts
Links to complementary prompts
```
---
XML Tag Structure
The prompt section uses semantic XML tags for consistent parsing:
| Tag | Purpose | Content |
|-----|---------|---------|
|
|
|
|
|
|
|
---
Quality Gates
Every prompt passes these 11 validation checks:
| Gate | Requirement |
|------|-------------|
| metadata_complete | All required fields present (ID, Version, Category, Tags, Complexity, Interaction, Models) |
| overview_concise | 3 sentences or fewer, no marketing fluff |
| role_specific | Concrete expertise defined, not "I'll help you" |
| inputs_categorized | Required vs optional distinguished with defaults |
| task_structured | 3-7 clear numbered steps |
| outputs_specified | Format + length + requirements for each deli
More from this repository10
Automates complex deployment workflows by generating infrastructure-as-code configurations, scripting deployment pipelines, and validating deployment readiness across multiple cloud and on-premise ...
Automatically detects, categorizes, and provides actionable recommendations for resolving software development errors and exceptions across different programming environments and languages.
Filters and sorts API data dynamically based on user-defined criteria, enabling precise data retrieval and organization with flexible query parameters.
Evaluates and recommends color palette modifications to ensure web designs meet WCAG accessibility standards for color contrast and readability for users with visual impairments.
Generates optimized caching strategies and recommendations for improving application performance by analyzing code, access patterns, and memory utilization.
Automatically generates optimized cloud infrastructure autoscaling configurations for compute resources based on workload patterns and performance requirements.
Monitors database performance, tracks key metrics, and generates real-time alerts for potential issues or performance bottlenecks in database systems.
Generates standardized code generation prompt templates following a consistent, validated structure for creating high-quality, reusable AI-assisted coding prompts.
Automates Azure App Service deployment configuration and infrastructure setup for web applications, providing standardized templates and best practices for cloud hosting.
Generates comprehensive backup and disaster recovery strategies, providing step-by-step plans for data protection, system restoration, and business continuity in enterprise IT environments.