Debugging-first guidance for professional Docker development across CLI, Compose, Docker Desktop, and Rancher Desktop
Git CLI operations, workflows, and automation for modern development (2025)
PostgreSQL development for Python with full-text search, vector similarity, and production deployment
Build, test, and debug AWS-native systems locally with LocalStack (Community/Pro) using awslocal, IaC toolchains, event-driven pipelines, and observability; includes setup, deployment, management, monitoring, and sharp-edge guidance.
Industrial-strength NLP with spaCy 3.x for text processing and classification
Grades and improves CLAUDE.md (Claude Code) and AGENTS.md (Codex/OpenCode) configuration files
Comprehensive guidance for building and deploying static websites with the Astro framework
Build static sites with the Zola generator (Rust-based SSG)
Build headless automation and agentic workflows with Google's Gemini CLI
Automates macOS apps via Apple Events using AppleScript (discovery) and JXA (production logic)
Guides AWS CDK v2 infrastructure-as-code development in TypeScript with patterns, troubleshooting, and deployment workflows
Debugging-first guidance for professional Docker development across CLI, Compose, Docker Desktop, and Rancher Desktop. Use when asked to "debug Docker", "troubleshoot containers", "fix Docker networking", "resolve volume permissions", or "Docker Compose issues", and when explaining cross-platform runtime behavior (Linux, macOS, Windows/WSL2) or Docker runtime architecture.
Document search with hybrid BM25/semantic retrieval, GraphRAG knowledge graphs, and pluggable providers
Git CLI operations, workflows, and automation for modern development (2025). Use when working with repositories, commits, branches, merging, rebasing, worktrees, submodules, or multi-repo architectures. Includes parallel agent workflow patterns for isolated worktree development, comprehensive merge strategy selection, conflict resolution, and recovery procedures.
PostgreSQL development for Python with full-text search (tsvector, tsquery, BM25 via pg_search), vector similarity (pgvector with HNSW/IVFFlat), JSONB and array indexing, and production deployment. Use when creating search features, storing AI embeddings, querying vector similarity, optimizing PostgreSQL indexes, or deploying to AWS RDS/Aurora, GCP Cloud SQL/AlloyDB, or Azure.
Build, test, and debug AWS-native systems locally with LocalStack (Community/Pro) using awslocal, IaC toolchains, event-driven pipelines, and observability; includes setup, deployment, management, monitoring, and sharp-edge guidance.
Industrial-strength NLP with spaCy 3.x for text processing and custom classifier training. Use when: installing spaCy, selecting models (en_core_web_sm/md/lg/trf), tokenization, POS tagging, named entity recognition, dependency parsing, training TextCategorizer models, troubleshooting errors (E050/E941 model errors, E927 version mismatch, memory issues), batch processing with nlp.pipe, or deploying models to production. Includes data preparation scripts, config templates, and FastAPI serving examples.
Grades and improves CLAUDE.md (Claude Code) and AGENTS.md (Codex/OpenCode) configuration files. Use when asked to grade, score, evaluate, audit, review, improve, fix, optimize, or refactor agent config files. Triggers on 'grade my CLAUDE.md', 'score my AGENTS.md', 'is my CLAUDE.md too big', 'improve my agent config', 'fix my CLAUDE.md', 'optimize context usage', 'reduce tokens in CLAUDE.md', or 'audit my config files'. Automatically grades both files if present, generates improvement plan, and implements changes on approval.
Comprehensive guidance for building and deploying static websites with the Astro framework. This skill should be used when asked to create astro site, deploy astro to firebase, set up content collections, add mermaid diagrams to astro, configure astro i18n, build static blog, or astro markdown setup. Covers SSG fundamentals, Content Collections, Markdown/MDX, partial hydration, islands architecture, and deployment to Netlify, Vercel, GitHub Pages, or GCP/Firebase.
Build static sites with the Zola generator (Rust-based SSG). Handles project initialization, config.toml configuration, Tera templates, Markdown content (sections via _index.md, pages via *.md), taxonomies, image processing, and deployment. Use for Zola project setup, Tera templating, _index.md structure, RSS/Atom feeds, syntax highlighting, or deployment to Netlify/Cloudflare/GitHub Pages/Vercel/Firebase. Also covers Zola+Astro hybrid architectures.
Build headless automation and agentic workflows with Google's Gemini CLI. Covers approval modes (default, auto_edit, yolo), file permission model, Edit vs WriteFile tool selection, smartEdit configuration, GEMINI.md context files, settings.json hierarchy, and MCP server integration.
Automates macOS apps via Apple Events using AppleScript (discovery) and JXA (production logic). Use when asked about AppleScript, JXA, osascript, or macOS app automation.
Guides AWS CDK v2 infrastructure-as-code development in TypeScript with patterns, troubleshooting, and deployment workflows. Use when creating or refactoring CDK stacks, debugging CloudFormation or CDK deploy errors, setting up CI/CD with GitHub Actions OIDC, or integrating AWS services (Lambda, API Gateway, ECS/Fargate, S3, DynamoDB, EventBridge, Aurora, MSK).
Debugging-first guidance for professional Docker development across CLI, Compose, Docker Desktop, and Rancher Desktop. Use when asked to "debug Docker", "troubleshoot containers", "fix Docker networking", "resolve volume permissions", or "Docker Compose issues", and when explaining cross-platform runtime behavior (Linux, macOS, Windows/WSL2) or Docker runtime architecture.
Git CLI operations, workflows, and automation for modern development (2025). Use when working with repositories, commits, branches, merging, rebasing, worktrees, submodules, or multi-repo architectures. Includes parallel agent workflow patterns for isolated worktree development, comprehensive merge strategy selection, conflict resolution, and recovery procedures.
PostgreSQL development for Python with full-text search (tsvector, tsquery, BM25 via pg_search), vector similarity (pgvector with HNSW/IVFFlat), JSONB and array indexing, and production deployment. Use when creating search features, storing AI embeddings, querying vector similarity, optimizing PostgreSQL indexes, or deploying to AWS RDS/Aurora, GCP Cloud SQL/AlloyDB, or Azure.
Build, test, and debug AWS-native systems locally with LocalStack (Community/Pro) using awslocal, IaC toolchains, event-driven pipelines, and observability; includes setup, deployment, management, monitoring, and sharp-edge guidance.
Industrial-strength NLP with spaCy 3.x for text processing and custom classifier training. Use when: installing spaCy, selecting models (en_core_web_sm/md/lg/trf), tokenization, POS tagging, named entity recognition, dependency parsing, training TextCategorizer models, troubleshooting errors (E050/E941 model errors, E927 version mismatch, memory issues), batch processing with nlp.pipe, or deploying models to production. Includes data preparation scripts, config templates, and FastAPI serving examples.
Grades and improves CLAUDE.md (Claude Code) and AGENTS.md (Codex/OpenCode) configuration files. Use when asked to grade, score, evaluate, audit, review, improve, fix, optimize, or refactor agent config files. Triggers on 'grade my CLAUDE.md', 'score my AGENTS.md', 'is my CLAUDE.md too big', 'improve my agent config', 'fix my CLAUDE.md', 'optimize context usage', 'reduce tokens in CLAUDE.md', or 'audit my config files'. Automatically grades both files if present, generates improvement plan, and implements changes on approval.
Comprehensive guidance for building and deploying static websites with the Astro framework. This skill should be used when asked to create astro site, deploy astro to firebase, set up content collections, add mermaid diagrams to astro, configure astro i18n, build static blog, or astro markdown setup. Covers SSG fundamentals, Content Collections, Markdown/MDX, partial hydration, islands architecture, and deployment to Netlify, Vercel, GitHub Pages, or GCP/Firebase.
Build static sites with the Zola generator (Rust-based SSG). Handles project initialization, config.toml configuration, Tera templates, Markdown content (sections via _index.md, pages via *.md), taxonomies, image processing, and deployment. Use for Zola project setup, Tera templating, _index.md structure, RSS/Atom feeds, syntax highlighting, or deployment to Netlify/Cloudflare/GitHub Pages/Vercel/Firebase. Also covers Zola+Astro hybrid architectures.
Build headless automation and agentic workflows with Google's Gemini CLI. Covers approval modes (default, auto_edit, yolo), file permission model, Edit vs WriteFile tool selection, smartEdit configuration, GEMINI.md context files, settings.json hierarchy, and MCP server integration.
Automates macOS apps via Apple Events using AppleScript (discovery) and JXA (production logic). Use when asked about AppleScript, JXA, osascript, or macOS app automation.
Automates macOS apps via Apple Events using AppleScript (discovery) and JXA (production logic). Use when asked about AppleScript, JXA, osascript, or macOS app automation.
Automates macOS apps via Apple Events using AppleScript (discovery) and JXA (production logic). Use when asked about AppleScript, JXA, osascript, or macOS app automation.
Automates macOS apps via Apple Events using AppleScript (discovery) and JXA (production logic). Use when asked about AppleScript, JXA, osascript, or macOS app automation.
Automates macOS apps via Apple Events using AppleScript (discovery) and JXA (production logic). Use when asked about AppleScript, JXA, osascript, or macOS app automation.
Automates macOS apps via Apple Events using AppleScript (discovery) and JXA (production logic). Use when asked about AppleScript, JXA, osascript, or macOS app automation.
Automates macOS apps via Apple Events using AppleScript (discovery) and JXA (production logic). Use when asked about AppleScript, JXA, osascript, or macOS app automation.
Automates macOS apps via Apple Events using AppleScript (discovery) and JXA (production logic). Use when asked about AppleScript, JXA, osascript, or macOS app automation.
Automates macOS apps via Apple Events using AppleScript (discovery) and JXA (production logic). Use when asked about AppleScript, JXA, osascript, or macOS app automation.
Automates macOS apps via Apple Events using AppleScript (discovery) and JXA (production logic). Use when asked about AppleScript, JXA, osascript, or macOS app automation.
Automates macOS apps via Apple Events using AppleScript (discovery) and JXA (production logic). Use when asked about AppleScript, JXA, osascript, or macOS app automation.
Automates macOS apps via Apple Events using AppleScript (discovery) and JXA (production logic). Use when asked about AppleScript, JXA, osascript, or macOS app automation.
Automates macOS apps via Apple Events using AppleScript (discovery) and JXA (production logic). Use when asked about AppleScript, JXA, osascript, or macOS app automation.
Automates macOS apps via Apple Events using AppleScript (discovery) and JXA (production logic). Use when asked about AppleScript, JXA, osascript, or macOS app automation.
Automates macOS apps via Apple Events using AppleScript (discovery) and JXA (production logic). Use when asked about AppleScript, JXA, osascript, or macOS app automation.
Automates macOS apps via Apple Events using AppleScript (discovery) and JXA (production logic). Use when asked about AppleScript, JXA, osascript, or macOS app automation.
Guides AWS CDK v2 infrastructure-as-code development in TypeScript with patterns, troubleshooting, and deployment workflows. Use when creating or refactoring CDK stacks, debugging CloudFormation or CDK deploy errors, setting up CI/CD with GitHub Actions OIDC, or integrating AWS services (Lambda, API Gateway, ECS/Fargate, S3, DynamoDB, EventBridge, Aurora, MSK).
Debugging-first guidance for professional Docker development across CLI, Compose, Docker Desktop, and Rancher Desktop. Use when asked to "debug Docker", "troubleshoot containers", "fix Docker networking", "resolve volume permissions", or "Docker Compose issues", and when explaining cross-platform runtime behavior (Linux, macOS, Windows/WSL2) or Docker runtime architecture.
Build, test, and debug AWS-native systems locally with LocalStack (Community/Pro) using awslocal, IaC toolchains, event-driven pipelines, and observability; includes setup, deployment, management, monitoring, and sharp-edge guidance.
Build, test, and debug AWS-native systems locally with LocalStack (Community/Pro) using awslocal, IaC toolchains, event-driven pipelines, and observability; includes setup, deployment, management, monitoring, and sharp-edge guidance.
Industrial-strength NLP with spaCy 3.x for text processing and custom classifier training. Use when: installing spaCy, selecting models (en_core_web_sm/md/lg/trf), tokenization, POS tagging, named entity recognition, dependency parsing, training TextCategorizer models, troubleshooting errors (E050/E941 model errors, E927 version mismatch, memory issues), batch processing with nlp.pipe, or deploying models to production. Includes data preparation scripts, config templates, and FastAPI serving examples.
Industrial-strength NLP with spaCy 3.x for text processing and custom classifier training. Use when: installing spaCy, selecting models (en_core_web_sm/md/lg/trf), tokenization, POS tagging, named entity recognition, dependency parsing, training TextCategorizer models, troubleshooting errors (E050/E941 model errors, E927 version mismatch, memory issues), batch processing with nlp.pipe, or deploying models to production. Includes data preparation scripts, config templates, and FastAPI serving examples.
Industrial-strength NLP with spaCy 3.x for text processing and custom classifier training. Use when: installing spaCy, selecting models (en_core_web_sm/md/lg/trf), tokenization, POS tagging, named entity recognition, dependency parsing, training TextCategorizer models, troubleshooting errors (E050/E941 model errors, E927 version mismatch, memory issues), batch processing with nlp.pipe, or deploying models to production. Includes data preparation scripts, config templates, and FastAPI serving examples.
Build static sites with the Zola generator (Rust-based SSG). Handles project initialization, config.toml configuration, Tera templates, Markdown content (sections via _index.md, pages via *.md), taxonomies, image processing, and deployment. Use for Zola project setup, Tera templating, _index.md structure, RSS/Atom feeds, syntax highlighting, or deployment to Netlify/Cloudflare/GitHub Pages/Vercel/Firebase. Also covers Zola+Astro hybrid architectures.
Build static sites with the Zola generator (Rust-based SSG). Handles project initialization, config.toml configuration, Tera templates, Markdown content (sections via _index.md, pages via *.md), taxonomies, image processing, and deployment. Use for Zola project setup, Tera templating, _index.md structure, RSS/Atom feeds, syntax highlighting, or deployment to Netlify/Cloudflare/GitHub Pages/Vercel/Firebase. Also covers Zola+Astro hybrid architectures.
Automates macOS apps via Apple Events using AppleScript (discovery) and JXA (production logic). Use when asked about AppleScript, JXA, osascript, or macOS app automation.
Automates macOS apps via Apple Events using AppleScript (discovery) and JXA (production logic). Use when asked about AppleScript, JXA, osascript, or macOS app automation.
Automates macOS apps via Apple Events using AppleScript (discovery) and JXA (production logic). Use when asked about AppleScript, JXA, osascript, or macOS app automation.
Automates macOS apps via Apple Events using AppleScript (discovery) and JXA (production logic). Use when asked about AppleScript, JXA, osascript, or macOS app automation.
Automates macOS apps via Apple Events using AppleScript (discovery) and JXA (production logic). Use when asked about AppleScript, JXA, osascript, or macOS app automation.
Automates macOS apps via Apple Events using AppleScript (discovery) and JXA (production logic). Use when asked about AppleScript, JXA, osascript, or macOS app automation.
Automates macOS apps via Apple Events using AppleScript (discovery) and JXA (production logic). Use when asked about AppleScript, JXA, osascript, or macOS app automation.
Automates macOS apps via Apple Events using AppleScript (discovery) and JXA (production logic). Use when asked about AppleScript, JXA, osascript, or macOS app automation.
Automates macOS apps via Apple Events using AppleScript (discovery) and JXA (production logic). Use when asked about AppleScript, JXA, osascript, or macOS app automation.
Guides AWS CDK v2 infrastructure-as-code development in TypeScript with patterns, troubleshooting, and deployment workflows. Use when creating or refactoring CDK stacks, debugging CloudFormation or CDK deploy errors, setting up CI/CD with GitHub Actions OIDC, or integrating AWS services (Lambda, API Gateway, ECS/Fargate, S3, DynamoDB, EventBridge, Aurora, MSK).
Guides AWS CDK v2 infrastructure-as-code development in TypeScript with patterns, troubleshooting, and deployment workflows. Use when creating or refactoring CDK stacks, debugging CloudFormation or CDK deploy errors, setting up CI/CD with GitHub Actions OIDC, or integrating AWS services (Lambda, API Gateway, ECS/Fargate, S3, DynamoDB, EventBridge, Aurora, MSK).
Guides AWS CDK v2 infrastructure-as-code development in TypeScript with patterns, troubleshooting, and deployment workflows. Use when creating or refactoring CDK stacks, debugging CloudFormation or CDK deploy errors, setting up CI/CD with GitHub Actions OIDC, or integrating AWS services (Lambda, API Gateway, ECS/Fargate, S3, DynamoDB, EventBridge, Aurora, MSK).
Guides AWS CDK v2 infrastructure-as-code development in TypeScript with patterns, troubleshooting, and deployment workflows. Use when creating or refactoring CDK stacks, debugging CloudFormation or CDK deploy errors, setting up CI/CD with GitHub Actions OIDC, or integrating AWS services (Lambda, API Gateway, ECS/Fargate, S3, DynamoDB, EventBridge, Aurora, MSK).
Debugging-first guidance for professional Docker development across CLI, Compose, Docker Desktop, and Rancher Desktop. Use when asked to "debug Docker", "troubleshoot containers", "fix Docker networking", "resolve volume permissions", or "Docker Compose issues", and when explaining cross-platform runtime behavior (Linux, macOS, Windows/WSL2) or Docker runtime architecture.
Debugging-first guidance for professional Docker development across CLI, Compose, Docker Desktop, and Rancher Desktop. Use when asked to "debug Docker", "troubleshoot containers", "fix Docker networking", "resolve volume permissions", or "Docker Compose issues", and when explaining cross-platform runtime behavior (Linux, macOS, Windows/WSL2) or Docker runtime architecture.
Debugging-first guidance for professional Docker development across CLI, Compose, Docker Desktop, and Rancher Desktop. Use when asked to "debug Docker", "troubleshoot containers", "fix Docker networking", "resolve volume permissions", or "Docker Compose issues", and when explaining cross-platform runtime behavior (Linux, macOS, Windows/WSL2) or Docker runtime architecture.
Build, test, and debug AWS-native systems locally with LocalStack (Community/Pro) using awslocal, IaC toolchains, event-driven pipelines, and observability; includes setup, deployment, management, monitoring, and sharp-edge guidance.
Build, test, and debug AWS-native systems locally with LocalStack (Community/Pro) using awslocal, IaC toolchains, event-driven pipelines, and observability; includes setup, deployment, management, monitoring, and sharp-edge guidance.
Industrial-strength NLP with spaCy 3.x for text processing and custom classifier training. Use when: installing spaCy, selecting models (en_core_web_sm/md/lg/trf), tokenization, POS tagging, named entity recognition, dependency parsing, training TextCategorizer models, troubleshooting errors (E050/E941 model errors, E927 version mismatch, memory issues), batch processing with nlp.pipe, or deploying models to production. Includes data preparation scripts, config templates, and FastAPI serving examples.
Industrial-strength NLP with spaCy 3.x for text processing and custom classifier training. Use when: installing spaCy, selecting models (en_core_web_sm/md/lg/trf), tokenization, POS tagging, named entity recognition, dependency parsing, training TextCategorizer models, troubleshooting errors (E050/E941 model errors, E927 version mismatch, memory issues), batch processing with nlp.pipe, or deploying models to production. Includes data preparation scripts, config templates, and FastAPI serving examples.
Industrial-strength NLP with spaCy 3.x for text processing and custom classifier training. Use when: installing spaCy, selecting models (en_core_web_sm/md/lg/trf), tokenization, POS tagging, named entity recognition, dependency parsing, training TextCategorizer models, troubleshooting errors (E050/E941 model errors, E927 version mismatch, memory issues), batch processing with nlp.pipe, or deploying models to production. Includes data preparation scripts, config templates, and FastAPI serving examples.
Industrial-strength NLP with spaCy 3.x for text processing and custom classifier training. Use when: installing spaCy, selecting models (en_core_web_sm/md/lg/trf), tokenization, POS tagging, named entity recognition, dependency parsing, training TextCategorizer models, troubleshooting errors (E050/E941 model errors, E927 version mismatch, memory issues), batch processing with nlp.pipe, or deploying models to production. Includes data preparation scripts, config templates, and FastAPI serving examples.
Industrial-strength NLP with spaCy 3.x for text processing and custom classifier training. Use when: installing spaCy, selecting models (en_core_web_sm/md/lg/trf), tokenization, POS tagging, named entity recognition, dependency parsing, training TextCategorizer models, troubleshooting errors (E050/E941 model errors, E927 version mismatch, memory issues), batch processing with nlp.pipe, or deploying models to production. Includes data preparation scripts, config templates, and FastAPI serving examples.
Industrial-strength NLP with spaCy 3.x for text processing and custom classifier training. Use when: installing spaCy, selecting models (en_core_web_sm/md/lg/trf), tokenization, POS tagging, named entity recognition, dependency parsing, training TextCategorizer models, troubleshooting errors (E050/E941 model errors, E927 version mismatch, memory issues), batch processing with nlp.pipe, or deploying models to production. Includes data preparation scripts, config templates, and FastAPI serving examples.
Industrial-strength NLP with spaCy 3.x for text processing and custom classifier training. Use when: installing spaCy, selecting models (en_core_web_sm/md/lg/trf), tokenization, POS tagging, named entity recognition, dependency parsing, training TextCategorizer models, troubleshooting errors (E050/E941 model errors, E927 version mismatch, memory issues), batch processing with nlp.pipe, or deploying models to production. Includes data preparation scripts, config templates, and FastAPI serving examples.
Grades and improves CLAUDE.md (Claude Code) and AGENTS.md (Codex/OpenCode) configuration files. Use when asked to grade, score, evaluate, audit, review, improve, fix, optimize, or refactor agent config files. Triggers on 'grade my CLAUDE.md', 'score my AGENTS.md', 'is my CLAUDE.md too big', 'improve my agent config', 'fix my CLAUDE.md', 'optimize context usage', 'reduce tokens in CLAUDE.md', or 'audit my config files'. Automatically grades both files if present, generates improvement plan, and implements changes on approval.
Build static sites with the Zola generator (Rust-based SSG). Handles project initialization, config.toml configuration, Tera templates, Markdown content (sections via _index.md, pages via *.md), taxonomies, image processing, and deployment. Use for Zola project setup, Tera templating, _index.md structure, RSS/Atom feeds, syntax highlighting, or deployment to Netlify/Cloudflare/GitHub Pages/Vercel/Firebase. Also covers Zola+Astro hybrid architectures.
Build static sites with the Zola generator (Rust-based SSG). Handles project initialization, config.toml configuration, Tera templates, Markdown content (sections via _index.md, pages via *.md), taxonomies, image processing, and deployment. Use for Zola project setup, Tera templating, _index.md structure, RSS/Atom feeds, syntax highlighting, or deployment to Netlify/Cloudflare/GitHub Pages/Vercel/Firebase. Also covers Zola+Astro hybrid architectures.
Automates macOS apps via Apple Events using AppleScript (discovery) and JXA (production logic). Use when asked about AppleScript, JXA, osascript, or macOS app automation.
Automates macOS apps via Apple Events using AppleScript (discovery) and JXA (production logic). Use when asked about AppleScript, JXA, osascript, or macOS app automation.
Automates macOS apps via Apple Events using AppleScript (discovery) and JXA (production logic). Use when asked about AppleScript, JXA, osascript, or macOS app automation.
Automates macOS apps via Apple Events using AppleScript (discovery) and JXA (production logic). Use when asked about AppleScript, JXA, osascript, or macOS app automation.
Automates macOS apps via Apple Events using AppleScript (discovery) and JXA (production logic). Use when asked about AppleScript, JXA, osascript, or macOS app automation.
Automates macOS apps via Apple Events using AppleScript (discovery) and JXA (production logic). Use when asked about AppleScript, JXA, osascript, or macOS app automation.
Automates macOS apps via Apple Events using AppleScript (discovery) and JXA (production logic). Use when asked about AppleScript, JXA, osascript, or macOS app automation.
Automates macOS apps via Apple Events using AppleScript (discovery) and JXA (production logic). Use when asked about AppleScript, JXA, osascript, or macOS app automation.
Automates macOS apps via Apple Events using AppleScript (discovery) and JXA (production logic). Use when asked about AppleScript, JXA, osascript, or macOS app automation.
Automates macOS apps via Apple Events using AppleScript (discovery) and JXA (production logic). Use when asked about AppleScript, JXA, osascript, or macOS app automation.
Guides AWS CDK v2 infrastructure-as-code development in TypeScript with patterns, troubleshooting, and deployment workflows. Use when creating or refactoring CDK stacks, debugging CloudFormation or CDK deploy errors, setting up CI/CD with GitHub Actions OIDC, or integrating AWS services (Lambda, API Gateway, ECS/Fargate, S3, DynamoDB, EventBridge, Aurora, MSK).
Guides AWS CDK v2 infrastructure-as-code development in TypeScript with patterns, troubleshooting, and deployment workflows. Use when creating or refactoring CDK stacks, debugging CloudFormation or CDK deploy errors, setting up CI/CD with GitHub Actions OIDC, or integrating AWS services (Lambda, API Gateway, ECS/Fargate, S3, DynamoDB, EventBridge, Aurora, MSK).
Guides AWS CDK v2 infrastructure-as-code development in TypeScript with patterns, troubleshooting, and deployment workflows. Use when creating or refactoring CDK stacks, debugging CloudFormation or CDK deploy errors, setting up CI/CD with GitHub Actions OIDC, or integrating AWS services (Lambda, API Gateway, ECS/Fargate, S3, DynamoDB, EventBridge, Aurora, MSK).
Guides AWS CDK v2 infrastructure-as-code development in TypeScript with patterns, troubleshooting, and deployment workflows. Use when creating or refactoring CDK stacks, debugging CloudFormation or CDK deploy errors, setting up CI/CD with GitHub Actions OIDC, or integrating AWS services (Lambda, API Gateway, ECS/Fargate, S3, DynamoDB, EventBridge, Aurora, MSK).
Guides AWS CDK v2 infrastructure-as-code development in TypeScript with patterns, troubleshooting, and deployment workflows. Use when creating or refactoring CDK stacks, debugging CloudFormation or CDK deploy errors, setting up CI/CD with GitHub Actions OIDC, or integrating AWS services (Lambda, API Gateway, ECS/Fargate, S3, DynamoDB, EventBridge, Aurora, MSK).