Copilot Studio Pattern Library

Only read the pattern file relevant to the current task — do NOT read all files.

Pattern Index

JIT Glossary → jit-glossary.md

Loads customer-specific acronyms into a global variable on first message so the orchestrator can expand them before searching knowledge sources.

Read this pattern when:

• The user wants to add a glossary, acronym list, or terminology table
• Knowledge search quality is poor because the agent doesn't understand internal abbreviations
• The user asks about loading CSV/text data into a variable at conversation start

JIT User Context → jit-user-context.md

Loads the current user's M365 profile (country, department) into global variables for personalized answers.

Read this pattern when:

• The user wants country-aware, department-aware, or role-aware answers
• The agent needs to call the M365 Users connector
• The user asks about personalizing responses based on who is chatting

Dynamic Topic Redirect → dynamic-topic-redirect.md

Uses a Switch expression inside a BeginDialog node to route to different topics based on a variable.

Read this pattern when:

• The user needs to route to one of several topics based on a variable
• The user wants to replace nested ConditionGroup nodes with a cleaner approach
• The user asks about dynamic topic redirects or Switch expressions

Prevent Child Agent Responses → prevent-child-agent-responses.md

Stops child agents from messaging users directly by instructing them to use output variables.

Read this pattern when:

• The user wants a child agent to return data without messaging the user
• The user is confused about the completion setting on a child agent
• The parent agent needs to control all user-facing responses

Date Context → date-context.md

Injects the current date into agent instructions using Power Fx for accurate date-relative responses.

Read this pattern when:

• Users ask date-relative questions ("What's next week?", "upcoming events")
• The agent handles schedules, calendars, deadlines, or time-sensitive content
• Date interpretation is causing confusion or hallucinations

Orchestrator-Generated Variables → orchestrator-variables.md

Uses AutomaticTaskInput to classify or extract structured data from the user's message at orchestration time — zero extra cost or latency.

Read this pattern when:

• The user needs to route knowledge searches by category
• The user wants to extract a classification without asking the user or using an AI Prompt
• Knowledge search quality suffers because all sources are searched indiscriminately

Prevent Tool Call Leaks → prevent-tool-call-leaks.md

Stops the orchestrator from leaking internal reasoning and tool call metadata to the end user.

Read this pattern when:

• Users report seeing raw JSON in agent responses
• The agent has connector actions that the orchestrator invokes indirectly
• Responses contain explanation_of_tool_call or similar internal metadata

Channel-Aware Behavior → channel-aware-behavior.md

Detects the host channel from System.Activity.ChannelId and gates behavior per surface (Teams, M365 Copilot, web chat, Direct Line, voice).

Read this pattern when:

• A feature works on one channel but breaks on another (file upload, Adaptive Card variants, hyperlinks)
• The user asks to detect Teams vs. M365 Copilot vs. web vs. voice
• A naive =Lower(ChannelId) = "msteams" check is silently failing for msteams:Copilot or other compound channel IDs

RAI Error Handling → rai-error-handling.md

Classifies Azure OpenAI content-filter errors by subcode in the OnError topic and returns category-specific user messages with telemetry. Azure OpenAI models only — does not work with Anthropic or xAI models.

Read this pattern when:

• The user needs industry-specific or empathetic error messages for RAI content-filter violations
• The user wants category-specific handling (e.g., crisis resources for self-harm, security messaging for jailbreak attempts)
• The user asks about OnError, ContentFiltered, Azure OpenAI content filters, or RAI subcodes

Line Breaks in Messages → line-breaks-in-messages.md

Uses <br /><br /> inside message and question nodes to render reliable paragraph spacing across channels.

Read this pattern when:

• Users report that bot messages feel like walls of text
• Multi-part questions or welcome messages need visual separation
• The user asks about line breaks, <br />, or formatting in messages or questions

Knowledge Hold Message → knowledge-hold-message.md

Sends a randomized hold message during knowledge search so users know the agent is working.

Read this pattern when:

• The agent has noticeable knowledge-search latency
• Users are abandoning conversations or resending questions during delays
• The user asks about OnKnowledgeRequested, typing indicators, or hold messages

Deterministic MCP Calls → deterministic-mcp-calls.md

Workarounds to improve MCP tool invocation reliability using instruction-based nudges or a dedicated child agent wrapper.

Read this pattern when:

• An MCP tool must fire every time for a specific intent but the orchestrator skips it
• The user asks about forcing MCP tool invocation or / syntax with MCP tools
• The user needs deterministic tool calls for business-critical workflows

Chain of Thought Logging → chain-of-thought-logging.md

Sends high-level "Thinking" messages during multi-step orchestration to improve observability and perceived responsiveness.

Read this pattern when:

• The agent uses multiple tools, MCP servers, or child agents that chain together
• Users experience long silences during multi-step reasoning
• The user wants a debug or observability trace of orchestrator behavior
• The user asks about streaming, typing indicators, or progress messages for complex flows

Conversation History Variable → conversation-history-variable.md

Captures a best-effort conversation transcript into a variable for escalation, logging, and downstream automation.

Read this pattern when:

• The user needs to capture conversation context for live-agent escalation
• A downstream tool or connector requires conversation history as input
• The user wants to log conversations to Dataverse, a ticketing system, or email

Teams Production Hardening → teams-production-hardening.md

Eight coordinated production patterns for Teams and M365 Copilot agents covering reinstalls, stale context, resets, diagnostics, and suggested prompts.

Read this pattern when:

• The user is deploying or hardening a Copilot Studio agent on Microsoft Teams
• Users report stale context after returning to a long-running Teams conversation
• Context variables work on web chat but not in Microsoft 365 Copilot
• The user wants richer OnError or Start Over experiences with diagnostic info
• The user asks about OnInstallationUpdate, OnInactivity, OnSystemRedirect, suggested prompts, or Teams-specific behavior

Combining patterns

Multiple patterns can be combined in a single agent. Common combinations:

• JIT Glossary + JIT User Context → merge into a single conversation-init OnActivity topic (template at templates/topics/conversation-init.topic.mcs.yml)
• Date Context + JIT User Context → both go in agent instructions; date is a Power Fx expression, user context is a global variable reference
• Orchestrator Variables + JIT User Context → classify by category AND personalize by country for precise knowledge routing
• RAI Error Handling + Teams Production Hardening → handle RAI subcodes first in OnError, then fall through to the generic diagnostic card from Pattern 7
• Knowledge Hold Message + Chain of Thought Logging → use hold messages for knowledge-heavy agents and CoT logging for multi-tool agents; both reduce perceived latency but solve different problems
• Teams Production Hardening + JIT User Context → Pattern 4 sets Global.UserContext cross-channel; replace hard-coded values with the JIT User Context connector call for real profile data

How to use patterns

Patterns are recommendations, not requirements. How you present them depends on your role:

If you are the Advisor agent:

• Present each pattern as a suggestion — explain the challenge it solves and why it's relevant
• Use status-appropriate language:
  • proven: "This is a proven pattern used in production — consider it for…"
  • recommended: "A recommended approach that works well — consider it for…"
  • experimental: "This is an experimental approach, not yet fully validated — you may want to test thoroughly before adopting"
• Always say "you could consider…" or "a common approach is…", never "you must…"
• Let the user decide — do NOT auto-apply patterns without confirmation

If you are the Author agent:

• When implementing a pattern the user or Advisor has already chosen, read the relevant pattern file for the correct YAML structure
• Do NOT suggest patterns yourself — that is the Advisor's role
• Use the YAML examples as reference for the correct kinds, fields, and structure