Create, design, and validate agents for Microsoft 365 Copilot. The skill guides JSON configuration or TypeSpec definitions, a typed alternative, alongside local testing, enterprise requirements, and deployment planning with Microsoft 365 Agents Toolkit.
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Complete development kit for Microsoft 365 Copilot declarative agents with three comprehensive workflows (basic, advanced, validation), TypeSpec support, and Microsoft 365 Agents Toolkit integration
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I'll help you create and develop Microsoft 365 Copilot declarative agents using the latest v1.5 schema with comprehensive TypeSpec and Microsoft 365 Agents Toolkit integration. Choose from three specialized workflows:
Perfect for: New developers, simple agents, quick prototypes
I'll guide you through:
Perfect for: Complex enterprise scenarios, production deployment, advanced features
I'll help you architect:
Perfect for: Existing agents, troubleshooting, performance optimization
I'll perform:
teamsdevapp.ms-teams-vscode-extension// Modern declarative agent definition
model MyAgent {
name: string;
description: string;
instructions: string;
capabilities: AgentCapability[];
conversation_starters?: ConversationStarter[];
}
{
"name": "${AGENT_NAME}",
"description": "${AGENT_DESCRIPTION}",
"instructions": "${AGENT_INSTRUCTIONS}"
}
Which workflow would you like to start with? Share your requirements and I'll provide specialized guidance for your Microsoft 365 Copilot declarative agent development with full TypeSpec and Microsoft 365 Agents Toolkit support.
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Map an existing codebase into seven documents covering its technology, structure, architecture, conventions, integrations, tests, and concerns. Link findings to file evidence, mark unknowns, and highlight differences between stated plans and the actual implementation.
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Assess a repository’s readiness for AI agents with AgentRC and generate a standalone HTML dashboard. Review scores across nine areas, see prioritized improvements, and optionally apply scoring policies tailored to an organization.
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Generate coding agent instruction files from a project's actual code using AgentRC. Capture detected languages, frameworks, and conventions in one shared file or split rules by topic and project area, with a preview before writing.
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Customize AgentRC readiness assessments to match team or organization standards. Choose or create policies that adjust check importance, disable irrelevant checks, set pass thresholds, and define requirements for automated checks in CI workflows.
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Analyze supplied ad performance data to identify wasted spend, strong campaigns, and next tests. Compare channels, assess whether test differences are meaningful, and produce budget reallocation recommendations with a prioritized action plan.
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Turn code files into learning resources by adding comments that explain syntax, programming concepts, and design choices. Adjust explanation depth and repetition to the reader’s knowledge while preserving file structure, encoding, and syntax.
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