Claude Skills by fabioc-aloha

Design and optimize production-grade multi-agent systems with LangGraph, LangChain, and DeepAgents for complex AI workflows.

Coordinate multiple AI agents for complex tasks — decomposition, delegation, and synthesis

This skill should be used when designing multi-agent systems that need context isolation, supervisor or swarm coordination, explicit handoffs, parallel execution, or a decision on whether multiple agents are justified.

Create and validate .prompt.md files that pass brain-qa on first attempt

Craft effective prompts that get the best results from language models.

Build retrieval-augmented generation systems that ground LLMs in your data.

POST-based Server-Sent Events streaming for Azure Functions — HTTP streaming, chunked response parsing, reconnection

Audit and eliminate token waste from cognitive architecture memory files -- instructions, prompts, skills, and agents

Build a new API connector or provider by matching the target repo's existing integration pattern exactly. Use when adding one more integration without inventing a second architecture.

Design APIs that developers love to use.

Comprehensive project consistency review across code, documentation, diagrams, and configuration

Meta-skill for maintaining and evolving Alex's cognitive architecture through deliberate documentation and pattern extraction.

AI/LLM features default to verbose responses, causing:

Provide sensible defaults with user-overridable configuration — reduce boilerplate without limiting flexibility

Cross-domain early-filtering paradigm for reducing cognitive and computational load in data pipelines, AI context, and human attention

Design microservices architectures with service boundaries, event-driven communication, and resilience patterns. Use when building distributed systems, decomposing monoliths, or implementing microservices.

Extensions/tools that auto-write to user workspaces without consent:

Implement saga patterns for distributed transactions and cross-aggregate workflows. Use this skill when implementing distributed transactions across microservices where 2PC is unavailable, designing compensating actions for failed order workflows that span inventory, payment, and shipping services, building event-driven saga coordinators for travel booking systems that must roll back hotel, flight, and car rental reservations atomically, or debugging stuck saga states in production where comp...

Monolithic transformations are hard to test and debug:

Multi-factor decisions become arbitrary without explicit weights:

Design durable workflows with Temporal for distributed systems. Covers workflow vs activity separation, saga patterns, state management, and determinism constraints. Use when building long-running processes, distributed transactions, or microservice orchestration.

Comprehensive molecular biology toolkit. Use for sequence manipulation, file parsing (FASTA/GenBank/PDB), phylogenetics, and programmatic NCBI/PubMed access (Bio.Entrez). Best for batch processing, custom bioinformatics pipelines, BLAST automation. For quick lookups use gget; for multi-service integration use bioservices.

Analyze Azure resources used in the app (IaC files and/or resources in a target rg) and optimize costs - creating GitHub issues for identified optimizations.

Well-Architected Framework principles and Azure best practices

In PowerShell, inline JSON for Cost Management API causes \"Unsupported Media Type\" errors:

Production deployment patterns for Azure Static Web Apps, Container Apps, App Service, and infrastructure

Performs comprehensive preflight validation of Bicep deployments to Azure, including template syntax validation, what-if analysis, and permission checks. Use this skill before any deployment to Azure to preview changes, identify potential issues, and ensure the deployment will succeed. Activate when users mention deploying to Azure, validating Bicep files, checking deployment permissions, previewing infrastructure changes, running what-if, or preparing for azd provision.

CI/CD pipelines, infrastructure as code, and deployment automation for Azure workloads

Time Saved: 1-2 hours debugging identity and RBAC

Azure OpenAI API patterns for rate limiting, function calling, error handling, and token optimization

Time Saved: 30 minutes - 1 hour debugging

Time saved: 2-4 hours per issue

Azure Verified Modules (AVM), Bicep best practices, and MCP-powered infrastructure as code for Azure

Design well-architected Azure cloud systems — 10 design principles, 6 architecture styles, 44 design patterns, technology choices, WAF pillars

Containerize an ASP.NET Core project by creating Dockerfile and .dockerfile files customized for the project.

Patterns for Microsoft Graph, Microsoft Entra ID, and enterprise feature integration in VS Code extensions

Microsoft Entra Agent ID (preview) — create OAuth2-capable AI agent identities via Microsoft Graph beta API

Import existing Azure resources into Terraform using Azure CLI discovery and Azure Verified Modules (AVM). Use when asked to reverse-engineer live Azure infrastructure, generate Infrastructure as Code from existing subscriptions/resource groups/resource IDs, map dependencies, derive exact import addresses from downloaded module source, prevent configuration drift, and produce AVM-based Terraform files ready for validation and planning across any Azure resource type.

Domain: DevOps & Cloud Engineering

Microsoft Fabric workspace management, governance, REST API patterns, and medallion architecture implementation

Comprehensive Microsoft Graph API reference for M365 service integration

Microsoft Authentication Library (MSAL) patterns for React/SPA applications with Entra ID

Time Saved: 1+ hour debugging silent auth failures

Create optimized multi-stage Dockerfiles for any language or framework

Full Teams app development patterns.

Update Azure Verified Modules (AVM) to latest versions in Bicep files.

Shared audit integrity framework for all AppSec agents — enforces output quality, intellectual honesty, and continuous improvement through anti-rationalization guards, self-critique loops, retry protocols, non-negotiable behaviors, self-reflection quality gates (1-10 scoring, ≥8 threshold), and a self-learning system with lesson/memory governance for security analysis agents.

Use when a user asks to generate or improve unit tests with measurable coverage gains using a strict staged workflow (build -> baseline -> plan -> generate -> verify -> coverage delta). Trigger phrases: generate unit tests, improve coverage, write tests for uncovered code, make PR-ready tests. Do not use for integration/E2E testing, production refactoring, or planning-only requests without code generation intent.

Code-scanning regex that looks for literal strings misses real usage:

Systematic code review for correctness, security, and growth — not just style enforcement