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.NET developers need reliable patterns for Azure AI Foundry project operations. This skill provides focused SDK guidance for agents, datasets, indexes, deployments, evaluations, connections, and authentication.

Microsoft Foundry applications require coordinated setup for clients, agents, tools, threads, data, and evaluations. This skill provides focused Python patterns using the Azure AI Projects SDK.

Azure AI Foundry project workflows can require many SDK operations and resource types. This skill provides focused TypeScript guidance for agents, tools, datasets, indexes, and deployments.

General-purpose assistants can use the wrong approach for a task. This skill selects structured modes for ideation, implementation, debugging, review, teaching, release, and collaboration.

Long refactors lose important decisions when work moves across sessions or agents. This skill guides semantic context retrieval, ranking, rehydration, and validation.

Large code changes can hide quality, security, performance, and testing risks. This skill coordinates a phased review workflow that turns those risks into prioritized action.

Conductor tracks can drift when tasks, tests, and metadata are updated by hand. This skill guides Claude, Codex, or Claude Code through TDD implementation, checkpoints, commits, and progress updates.

AI applications lose relevance when context, memory, and retrieval systems are poorly designed. This skill guides context architecture, RAG, knowledge graphs, and multi-agent state management.

Crypto exchange teams need a consistent way to identify and qualify token listing prospects. This skill structures discovery, scoring, wallet review, and approval-based outreach.

Feature teams often ship changes without clear evidence or measurable outcomes. This skill guides analysis, A/B testing, instrumentation, rollout, and post-launch review.

Unreviewed designs can create avoidable implementation risks and costly rework. This skill routes design work through brainstorming, risk assessment, validation, and readiness checks.

Single-perspective reviews can miss security, architecture, performance, and quality concerns. This skill coordinates specialized reviewers and synthesizes their findings into one prioritized assessment.