Tag: Microsoft Teams

  • Copilot Cowork Prompt of the Day: Real Microsoft 365 Workflows That Actually Save Time

    Copilot Cowork Prompt of the Day: Real Microsoft 365 Workflows That Actually Save Time

    Copilot Cowork Prompt of the Day: Real Microsoft 365 Workflows That Actually Save Time

    I have been testing Copilot Cowork across real work patterns inside Microsoft 365: meetings, calendar cleanup, files, time entries, customer feedback, follow-ups, and workspace history.

    The pattern is becoming clear.

    The strongest Copilot Cowork prompts do not just ask for an answer. They assign a business outcome. They define the source of truth. They set guardrails. They tell Cowork what finished work should look like.

    That is where this gets serious.

    Below is a practical prompt library based on my Copilot Cowork Prompt of the Day posts across X and LinkedIn. I grouped them by scenario so the examples are easier to scan, reuse, and adapt.

    Note: Some examples use demo companies, files, customers, and project names. Replace those with your own Microsoft 365 content, folders, meetings, and business context.

    Table of Contents

    Calendar and Focus Management

    Calendar work looks simple until it eats your day. Declining meetings, cancelling organizer-owned events, protecting focus time, and finding clean openings are perfect examples of work that should be delegated.

    These prompts show Cowork acting like a real calendar operator, not a passive chatbot.

    Decline and Cancel Holiday Meetings

    The situation

    Friday is a holiday. Your calendar still has meetings. Some meetings were created by other people. Some meetings may be yours. You need everything cleaned up properly.

    The important part is the distinction between declining and cancelling. If you are only an attendee, Cowork should decline the meeting. If you are the organizer, Cowork should cancel it and send a note so attendees know why it disappeared.

    Copilot Cowork using calendar management to decline meetings and cancel organizer-owned meetings for a holiday.

    The prompt

    [Day] is a holiday. Check [Date].
    - Decline every meeting.
    - If I’m the organizer, cancel it and send a note.
    Use /calendar-management

    What Cowork should do

    • Check the target date.
    • Find every meeting on that day.
    • Decline meetings where you are an attendee.
    • Cancel meetings where you are the organizer.
    • Send a professional cancellation note where needed.
    • Summarize what changed.

    This is the kind of task that burns attention. The value is not only the minutes saved. The real value is that Cowork understands the difference between attendee action and organizer responsibility.

    Cancelling a meeting you own sends a different signal than declining a meeting someone else owns.

    How I would tighten the prompt

    For a production-style version, I would add the wording for the cancellation note directly into the prompt.

    Friday is a company holiday. Check April 3rd in my calendar.
    For every meeting that day:
    - If I am only an attendee, decline the meeting.
    - If I am the organizer, cancel the meeting.
    - For cancelled meetings, send this note:
    “April 3rd is a holiday, so I’m cancelling this meeting.
    Please reschedule for the following week if still needed.”
    After you finish, send me a summary grouped by declined meetings
    and cancelled meetings.
    Use /calendar-management

    Create Focus Time from Your Phone

    The situation

    This one is simple. That is why it matters.

    I used the iOS app from bed and told Cowork to find two separate one-hour focus blocks for Monday morning. Cowork checked my calendar, found the openings, and created both events.

    No desktop. No calendar hunting. No dragging blocks around half asleep.

    The prompt

    Set some focus time for me up for Monday morning.
    Find 2 separate 1 hour blocks so I can focus on:
    1) <Task>
    2) <Task>

    What Cowork should do

    • Review your Monday morning calendar.
    • Find two separate one-hour openings.
    • Create calendar events for each focus block.
    • Name each block clearly based on the task.
    • Add useful context where available.

    Focus time only helps if it actually lands on the calendar. A lot of people know what they need to work on, then lose the day to meetings, messages, and context switching.

    This turns focus protection into a command.

    That is the kind of small task agents should crush first. Scheduling. Calendar juggling. Protecting time. Removing the coordination mess.

    How I would tighten the prompt

    I would add preferred working hours, meeting buffer rules, and event details.

    Set up 2 separate 1-hour focus blocks for Monday morning.
    Focus areas:
    1) <Task 1>
    2) <Task 2>
    Rules:
    - Only schedule between 8:00 AM and 12:00 PM.
    - Do not overlap existing meetings.
    - Leave at least 15 minutes between meetings and focus blocks where possible.
    - Use clear calendar titles: “Focus: <Task>”.
    - Add a short note to each event with the goal for that focus block.
    After scheduling, tell me the times you picked.

    ↑ Back to top


    Time Entry and Work Reporting

    Time entry is one of the best Cowork use cases because the evidence already exists across Microsoft 365. Meetings, chats, emails, files, edits, and shared work all tell the story of the day.

    The hard part is turning that messy activity trail into believable time-entry comments that a human can review.

    Build a Daily Time Entry Summary from Microsoft 365 Activity

    The situation

    This prompt asks Cowork to review the day’s Microsoft 365 activity and produce a structured time-entry draft. The goal is not perfect accounting. The goal is a practical, honest draft that can be reviewed and corrected quickly.

    The real power is that Cowork is not only looking at meetings. It is asked to look across calendar activity, Teams chats, email, files, transcripts, meeting notes, and other signals.

    Daily time entry draft created from Microsoft 365 work activity.

    The prompt

    Review ALL of MY Microsoft 365 work activity from TODAY in
    [your timezone] and build a realistic, structured daily time entry
    summary.
    Then send it as a [direct Teams message / Email].
    Use every available signal from today:
    - calendar meetings
    - transcripts and recaps
    - meeting chats
    - Teams chats and channel messages
    - emails
    - files opened, edited, or shared
    - any other work activity signals
    Rules:
    1. Only use today in my local timezone.
    2. Look across all evidence, not just meetings.
    3. Infer the best-fit project, client, internal initiative, or business
    development category.
    4. Map work to a project whenever possible.
    5. If unclear, use: Business Development, Internal Operations,
    Practice Development, Admin, or Learning / Enablement.
    6. Consolidate fragmented activity into meaningful work blocks.
    7. Target a full day close to 8.0 hours.
    8. Acceptable total range: 6.0-8.0 hours.
    9. Accuracy first, then use reasonable consolidation to close gaps.
    10. Do not invent fake meetings, deliverables, or project names.
    11. If evidence is weak, make the best possible mapping, but keep
    descriptions honest.
    12. Avoid over-fragmenting. Prefer fewer, stronger entries.
    13. Write descriptions like real time-entry comments, not AI summaries.
    14. Keep descriptions concise but useful.
    15. Group short related activities under the same project.
    16. If there is clear prep or follow-up around meetings, emails,
    chats, or docs, include that under the relevant project when evidence
    supports it.
    17. Capture business development work where relevant:
    sales support, proposal work, internal planning, networking,
    demos, enablement, certifications, or content creation.
    Format the Teams message as HTML:
    - Bold heading: Daily Time Entry Draft – [YYYY-MM-DD]
    - Bold "Summary:" plus a 1-2 line plain-text summary
    - HTML table: # | Project Name | Description | Duration | Date
    - One row per entry, ordered largest to smallest
    - Duration in decimal hours, e.g. 3.0 hrs or 0.5 hrs
    - Bold "Total: X.X hours" at the bottom
    Quality bar: practical, believable, timesheet-ready.
    Use real work patterns. Balance to 6-8 hours.
    If today has limited evidence, still produce the best possible draft.

    What Cowork should do

    • Build a workday view from Microsoft 365 evidence.
    • Classify activity into projects, clients, or internal categories.
    • Consolidate short fragments into stronger time-entry rows.
    • Keep the wording practical and timesheet-ready.
    • Send the finished draft as a Teams message.

    This is a serious consulting and professional services scenario.

    Timesheets fail when people are forced to reconstruct their day from memory. Cowork can inspect the activity trail and give you a draft while the day is still fresh.

    You still review it. You still own it. Cowork reduces the blank-page problem.

    Important guardrails

    The guardrails are the real prompt design lesson here.

    • Do not invent fake meetings, deliverables, or project names.
    • Keep weak evidence honest.
    • Prefer fewer, stronger entries.
    • Write like a real time-entry comment.

    That is how you keep this useful without letting the agent drift into fantasy work logs.

    ↑ Back to top


    Meeting Intelligence and Follow-Up

    Meetings create a lot of residue: transcripts, AI notes, chats, files, agendas, decisions, action items, and follow-up messages.

    The problem is that the value disappears when nobody turns that residue into something clean.

    Create a Meeting Recap and Send It to Attendees

    The situation

    This prompt gives Cowork one target meeting and asks it to pull all available meeting content. The output is a structured recap and a concise email to attendees.

    The prompt also changes the recap style based on the meeting type. A requirements session should not be summarized the same way as a standup or UAT meeting.

    Meeting recap generated from meeting content, notes, transcript, chat, and related files.

    The prompt

    Use the meeting provided in context: <Meeting>.
    Meeting type: [Requirements | Standup | Training | UAT | Other]
    Treat this as the only target meeting. Pull all available meeting content
    including AI notes, transcript, meeting chat, shared files, agenda,
    description, and attached notes.
    Create a recap with:
    - purpose
    - key discussion points
    - decisions
    - action items
    - owners
    - due dates
    - follow-ups
    Adapt the recap based on the meeting type:
    - Requirements: needs, requested features, pain points, constraints,
    open requirements
    - Standup: progress, blockers, next steps
    - Training: what was taught, guidance shared, takeaways, resources
    - UAT: what was tested, issues found, defects, next steps for fixes or
    retesting
    - Other: use the most appropriate structure
    If anything is unclear or missing, state that clearly instead of guessing.
    Then draft and send a concise, professional recap email to all attendees.

    What Cowork should do

    • Use only the meeting provided in context.
    • Pull available transcript, recap, chat, files, agenda, and notes.
    • Build a recap that matches the meeting type.
    • Call out missing or unclear details.
    • Send a concise recap email to attendees.

    The most useful meeting recap is not a generic summary. It captures the operating details that move work forward: decisions, owners, due dates, and follow-ups.

    This prompt also handles one of the biggest issues with AI meeting summaries: context control. It tells Cowork to treat the provided meeting as the only target meeting.

    How I would tighten the prompt

    For client-facing work, I would add a review step before sending.

    Use the meeting provided in context: <Meeting>.
    Meeting type: [Requirements | Standup | Training | UAT | Other]
    Treat this as the only target meeting. Pull all available meeting conten
    including AI notes, transcript, meeting chat, shared files, agenda,
    description, and attached notes.
    Create a recap with:
    - Purpose
    - Key discussion points
    - Decisions
    - Action items
    - Owners
    - Due dates
    - Follow-ups
    Adapt the recap based on the meeting type.
    If anything is unclear or missing, state that clearly instead of guessing.
    Draft a concise, professional recap email to all attendees,
    but do not send it until I review and approve it.

    ↑ Back to top


    Customer Feedback and Leadership Deliverables

    This is the most advanced scenario in the set.

    The assignment is not just “summarize feedback.” The assignment is to turn scattered customer signals into a leadership-ready action package.

    That means Cowork has to analyze, prioritize, create deliverables, flag weak evidence, and prepare different outputs for different audiences.

    Turn Customer Feedback into a Product Action Plan

    The situation

    Kavora’s marketing department has customer feedback scattered across interviews, surveys, comments, web signals, and meeting notes.

    Leadership needs the real story:

    • What customers are saying.
    • What matters most.
    • What needs action.
    • What needs human judgment before the team moves.

    For the demo, the input files were:

    • Customer interview notes
    • Product feedback survey and web signal export
    • Source customer comments
    • Marketing leadership request and context email

    The Cowork assignment was to review the feedback, find the strongest themes, rank them by impact and urgency, flag gaps or contradictions, then build the deliverables a marketing team would actually need.

    Copilot Cowork turning scattered customer feedback into a brief, deck, emails, Teams update, and decision tracker.

    The expected outputs

    • Executive feedback brief
    • Stakeholder-ready presentation deck
    • Customer follow-up email pack
    • Launch squad Teams update
    • Leadership decision tracker

    The prompt

    Act as my marketing operations lead.
    Goal:
    I’m working on turning messy customer product feedback into a clear
    action plan for product, marketing, and leadership teams.
    Sources:
    Use the attached files and project folder as the source of truth.
    These may include customer interview notes, survey results,
    web/funnel data, Teams meeting summaries, support themes,
    website feedback, campaign comments, and leadership request emails.
    Task:
    1. Review the materials and identify the strongest customer feedback
    themes.
    2. Prioritize the themes by customer impact, urgency, revenue risk, and
    brand risk.
    3. Pull proof points from the source material, including customer
    quotes, survey signals, and web/funnel trends.
    4. Identify gaps, contradictions, sampling bias, or anything that needs
    validation before decisions are made.
    5. Recommend the next best actions for product, marketing,
    customer success, and leadership.
    Produce:
    • A polished executive feedback brief
    • A stakeholder-ready presentation deck
    • A customer follow-up email pack
    • A Teams update for the launch squad
    • A leadership decision tracker with priorities, owners, and dates
    Guardrails:
    • Separate facts from recommendations
    • Do not invent evidence
    • Call out assumptions clearly
    • Flag anything that needs human review
    • Make the outputs ready for me to review, edit, and share

    What Cowork should do

    • Review all supplied source material.
    • Find repeated customer themes.
    • Rank themes by impact, urgency, revenue risk, and brand risk.
    • Pull quotes and proof points from the evidence.
    • Flag contradictions, bias, gaps, and validation needs.
    • Create separate deliverables for leadership, product, launch teams, and customer follow-up.

    The best part of this prompt is the deliverable design. It does not stop at analysis. It asks for the assets the business actually needs:

    • A brief for executives.
    • A deck for stakeholders.
    • Email drafts for customers.
    • A Teams update for the launch squad.
    • A decision tracker for leadership.

    That is the difference between “tell me what the files say” and “help me move the business forward.”

    The human review layer

    This prompt gets the review model right. It tells Cowork to separate facts from recommendations and flag assumptions.

    That matters because customer feedback can be messy. You can have contradictory signals, loud power users, small samples, weak survey patterns, or feedback that sounds urgent but needs validation.

    The agent can organize the evidence. The human still owns the judgment.

    How I would tighten the prompt

    I would add a scoring model so the ranking is easier to audit.

    When ranking feedback themes, score each theme from 1-5 across:
    - Customer impact
    - Urgency
    - Revenue risk
    - Brand risk
    - Evidence strength
    Then calculate a priority recommendation of P0, P1, or P2.
    For every theme, include:
    - Evidence used
    - Customer quote or signal
    - Recommended owner
    - Recommended next action
    - What needs human validation before action

    ↑ Back to top


    File and Workspace Operations

    Some of the best agent use cases are boring. That is the point.

    Moving files, finding folders, reviewing previous sessions, and organizing workspace context are small tasks by themselves. Across a week, they become attention tax.

    Move a File in OneDrive

    The situation

    I downloaded a zip file on my phone, uploaded it to OneDrive, and told Cowork to move it into the right demo folder.

    No laptop. No desk. No clicking through folders.

    Cowork found the file, found the destination folder, and moved it.

    Copilot Cowork finding a recently uploaded zip file and moving it to the right OneDrive folder.

    The prompt

    I just uploaded a <file or folder> to OneDrive.
    Can you move it to the Copilot Cowork Demos folder

    What Cowork should do

    • Search OneDrive for the uploaded file or folder.
    • Search OneDrive for the destination folder.
    • Move the item.
    • Confirm the exact file or folder that was moved.

    This is the kind of work nobody wants to do. It is small enough to feel annoying and common enough to keep stealing attention.

    Agents should handle the annoying little tasks first.

    Find the file. Find the folder. Move it. Confirm it.


    Review Past Cowork Sessions

    The situation

    This is a fun one for understanding the workspace Cowork builds around your work.

    The prompt asks Cowork to look across previous sessions and tell you what you have built together, then pick its favorite session.

    Your Cowork sessions are stored in:

    Documents > Coworker > sessions
    Copilot Cowork reviewing previous sessions and summarizing what has been built.

    The prompt

    based on all our sessions, can you tell me the things we have built
    together, and your most favorite session?

    What Cowork should do

    • Enumerate previous session folders.
    • Identify deliverables created in each session.
    • Summarize patterns across the work.
    • Pick a favorite session and explain why.

    This shows Cowork as more than a one-off task runner. It can review the body of work created across sessions and help you understand what has been built.

    That becomes useful when you are building demos, content, project assets, templates, or repeatable internal workflows.

    How I would tighten the prompt

    I would ask for the output in a reusable inventory format.

    Review all our Cowork sessions stored in
    Documents > Coworker > sessions.
    Create a structured inventory with:
    - Session name
    - Date if available
    - Business scenario
    - Deliverables created
    - Files produced
    - Skills or tools used
    - Reusable assets I should keep
    - Your favorite session and why
    Group the results by scenario type.

    ↑ Back to top


    The Prompt Design Pattern

    After testing these scenarios, the pattern is obvious.

    A strong Copilot Cowork prompt usually needs these parts:

    1. Assign the role

    Example

    Act as my marketing operations lead.

    This gives Cowork a working frame. A calendar assistant, marketing operations lead, project coordinator, meeting analyst, or time-entry assistant will make different choices.

    2. Define the business goal

    Example

    I’m working on turning messy customer product feedback into a clear
    action plan for product, marketing, and leadership teams.

    The goal keeps Cowork focused on the outcome instead of wandering through the source material.

    3. Name the source of truth

    Example

    Use the attached files and project folder as the source of truth.

    This matters because Cowork may have access to a lot of context. You need to tell it what evidence matters.

    4. Add rules and guardrails

    Example

    Do not invent evidence.
    Call out assumptions clearly.
    Flag anything that needs human review.

    Guardrails keep the work usable. They also make the output safer to review, edit, and share.

    5. Specify the finished output

    Example

    Produce:
    - A polished executive feedback brief
    - A stakeholder-ready presentation deck
    - A customer follow-up email pack
    - A Teams update for the launch squad
    - A leadership decision tracker with priorities, owners, and dates

    Do not make Cowork guess what “done” means. Define the deliverables.

    6. Keep human review in the loop

    Example

    Make the outputs ready for me to review, edit, and share.

    This is the right operating model. Cowork can create the draft, organize the work, and prepare the package. You still make the judgment call.

    ↑ Back to top

    Final Thought

    Copilot Cowork gets interesting when you stop treating it like a chat box and start treating it like a worker with an assignment.

    The best prompts are direct. They give Cowork the goal, the evidence, the rules, and the expected output.

    That is how you move from “write me a summary” to:

    • Clean up my calendar.
    • Protect my focus time.
    • Draft my time entries.
    • Summarize the meeting and follow up.
    • Turn customer feedback into an action plan.
    • Move the file where it belongs.
    • Review the work we have already built.

    Small tasks. Big tasks. Same lesson.

    Give the agent clear work. Keep the guardrails tight. Review the output like a professional.

    That is where Copilot Cowork starts to feel like real capacity.

    ↑ Back to top

  • Part 2 – Build & Ship a “Docs Agent” to Microsoft Teams

    Part 2 – Build & Ship a “Docs Agent” to Microsoft Teams

    (Companion guide to “Spin-Up the Microsoft Learn MCP Server”)

    Make sure you have read and setup the Docs MCP custom connector from part 1

    1. What you’ll build
    2. Prerequisites
      1. Icons to Download (optional)
    3. 1 – Create the Agent in Copilot Studio
      1. Add Suggested Prompts
      2. Agent Settings
      3. Turn Off Pointless Topics
    4. Publish & Package for Teams
      1. Submit Agent for Approval
    5. Approve Agent App (As a Teams Admin)
    6. How to Use the Agent
      1. Adding Agent to a Meeting or Chat
      2. Troubleshooting

    What you’ll build

    A Copilot Studio agent that queries the Microsoft Learn MCP server for live docs, then answers teammates inside a Teams chat or Meeting.

    Prerequisites

    NeedNotes
    Docs MCP custom connector from Part 1Already in your environment.
    (https://flowaltdelete.ca/2025/06/26/how-to-spin-up-the-microsoft-learn-mcp-server-in-copilot-studio/)
    Copilot Studio (preview) tenantGenerative orchestration enabled. (Early Features)
    Teams admin rights (or approval from your Teams Admin)To upload a custom app or publish to the org.
    Copilot Studio LicenseMessage packs or sessions
    prereq table

    Icons to Download (optional)

    Below are icons you can use for the Agent and the MCP custom connector.

    1 – Create the Agent in Copilot Studio

    In this example I am going to use the existing agent I created from Part 1.

    1. Modify or create the agent with a meaningful name, description, and icon.
      (You can use the one I provided from above or use your own)
    2. Name: MS Docs Agent
    3. Description: MS Docs Agent is your on-demand mentor for Microsoft technologies—built with Copilot Studio and powered by the Microsoft Learn MCP server. Every answer comes from the live, authoritative docs that Microsoft publishes each day, so you never rely on stale model memories or web-scraped content.
    4. Orchestration = Enabled

    5. For your Instructions for the agent, we don’t want to add too much. After much testing I found that in its current state the Docs MCP server handles the instructions well and having too much instructions causes the response to fail. So its better to leave instructions blank for now.
    6. Web Search – This should be Disabled. We only want the agent to query the docs which it does through the MCP server.
    7. Knowledge should be empty, the only thing we want this agent to do is query the Docs MCP server, so this should be the only Tool that the agent has access to.
    8. To recap, the only Tools and Knowledge this agent should have is the MCP Server (custom connector) that we created in the first blog post. If you need help setting this up refer to Part 1.

    Add Suggested Prompts

    When users interact with the agent in M365 chat (Copilot) we can show suggested prompts to help guide the user in what is possible with this agent. Here are a bunch of samples you can give your agent:

    TitlePrompt
    Dev Env for Power AppsSet up a developer environment for Power Apps—step-by-step.
    Rollup vs FormulaRollup fields vs Formula columns in Dataverse—when to use each?
    Flow 502 FixPower Automate flow fails with 502 Bad Gateway—how do I resolve it?
    Cert Path FinderFastest certification path for a Dynamics 365 functional consultant.
    PL-200 Module ListList every Microsoft Learn module covered by the PL-200 exam.
    Managed Env EnableTurn on managed environments and approval gates in Power Platform.
    Finance DLP PolicyBest-practice DLP setup for finance data in Power Platform.
    Power Fx Date FilterSample Power Fx to filter a gallery to today’s records.
    OpenAI Flow SampleMinimal example: call Azure OpenAI from Power Automate.
    Secure Env VarsSecure environment variables with Azure Key Vault in flows.
    Pipeline ChecklistChecklist to deploy a solution through Power Platform pipelines.
    PCF Chart ControlBuild a PCF control that renders a chart on a model-driven form.
    New PA FeaturesSummarize new Power Apps features announced this month.
    Preview ConnectorsList preview connectors added to Power Automate in the last 30 days.
    Explain to a ChildExplain Dataverse to a five-year-old.

    You can only add 6 Suggested Prompts. So choose carefully.

    Agent Settings

    Next we want to configure some settings on the agent.

    1. Click the Settings button on the top right.

    2. (Optional) If you want the agent to have reasoning capabilities > Under Generative AI turn on: Deep reasoning
      **Note that this is a premium feature**

    3. Scroll down to Knowledge, make sure Use general knowledge and Use information from the Web are both OFF

    4. Make sure to click Save once done.

    Turn Off Pointless Topics

    Next we will turn off the topics we don’t want the agent to use.

    1. Click on Topics tab > Under Custom > Only leave Start Over topic On.

    2. Under System > Turn Off:
      – End of Conversation
      – Escalate
      – Fallback
      – Multiple Topics Matched

    3. Next, lets modify the Conversation Start to make it sound better.
      Click Conversation Start topic > Modify the Message node:

    4. Click Save.

    Now we are ready to Publish and Package for Teams!

    Publish & Package for Teams

    Next we need to Publish our agent.

    1. Click on the Channels tab > Click Publish

    2. Once your agent is published > Click on the Teams and Microsoft 365 Copilot channel.

    3. A sidebar opens > Check the Make agent available in Microsoft 365 Copilot > Click Add channel.

    4. After the channel has been added > Click Edit details.

    5. This is where we configure the agent in Teams. We will modify the icon, give a short description, long description and allow for the agent to be added to a team and meeting chats.
      Under Teams settings > Check both:
      Users can add this agent to a team
      Use this agent for group and meeting chats

    6. Click Save

    Submit Agent for Approval

    Now because we want our organization to easily find and use this agent. We will submit the agent to the Agent Store. To do this follow these steps:

    1. First Publish your agent, to make sure you have the newest version you are pushing to Teams admin for approval.
    2. Next click on the Channels tab > Select the Teams and Microsoft 365 Copilot channel.
    3. Now click Availability options.

    4. Now we will configure the Show to everyone in my org.

    5. Than click Submit for admin approval.

      Now we will look at what a Teams Admin has to do.

    Approve Agent App (As a Teams Admin)

    A Microsoft Teams Admin will have to approve the Agent app before your org can use it. As a Teams Admin follow these steps:

    1. Navigate to https://admin.teams.microsoft.com/policies/manage-apps
      (Click on Manage apps under Teams apps)
    2. Search for your agent name in the search bar

    3. Click the agent > Publish.

    4. Note:: You will need Admin Approval each time you want to publish an update to the agent.

    How to Use the Agent

    Once your agent is approved by an Admin. You can easily find it in the Agent Store. Another easy way to get to your agent is to open it from Copilot Studio:

    1. Click Channels tab > Select Teams and Microsoft 365 Copilot channel > Click See agent in Teams.

    You will be brought to Teams with the agent open. You can now add it:

    Adding Agent to a Meeting or Chat

    There are a few ways to add the agent to a meeting. One easy way is to @mention the agent in the chat.

    **Note to start typing the name of the agent, and it should show up**

    Troubleshooting

    There are a few things to note that I ran into:
    1) If your getting an error on the MCP Server, remove all custom instructions

    2) Sometimes your agents details can be cached and showing old metadata. In this case you can resubmit the app approval.

    3) Always test the Agent inside Copilot Studio Test Pane with tracking topics and Activity Map turned On.

  • Getting User Details To Use In Power Virtual Agents (Teams)

    Getting User Details To Use In Power Virtual Agents (Teams)

    Things to Know

    This examples is based on building a Virtual Agent in Microsoft Teams.
    We will be using the ‘Only for teams’ Authentication on the bot.

    Summary

    By default PVA in Teams has some valuable variables handy, like ‘bot.UserDisplayName‘. This is awesome, but what if we want more information about the logged in user?

    This post will show both scenarios, on using the bot.UserDisplayName variable as well as getting all the user details that are stored in Office365 like:
    – Email Address
    – First Name
    – Last Name
    – Job Title
    – Etc.

    We can also use this in the Greetings Topic to address the user by their first name, rather than their display name. (Keep in mind this might affect performance by a couple seconds)

    Contents

    Bot Setup
    Scenario 1 (Display Name)
    Scenario 2 (Office365 Details)
    Conclusion

    Bot Setup

    Once you have your Bot created, make sure the Authentication is set to ‘Only for teams’. To check click
    Manage > Security, Authentication

    For this example we will be using the ‘Only for Teams’ option. This will work for ‘Manual’ as well, but will require additional steps to setup a App Registration in Azure.

    Select ‘Only for Teams’

    Customize Greeting Scenario 1 (DisplayName)

    After enabling the Authentication, you will now have access to Two variables,
    bot.UserDisplayName
    bot.UserId

    Now lets customize our greeting.

    Navigate to ‘Topics’ and select the ‘Greeting’ Topic, this is under ‘System Topics’. Click on the Authoring Canvas button.

    Inside the message under the Trigger, you can customize the greeting message to include the variable bot.UserDisplayName

    Testing this, the Bot now knows my Display Name. This variable can be used in any topic. Which gives the Bot more of a human type feel.

    To get all the user details from Office365, scenario 2 will cover this

    Customize Greeting Scenario 2 (Office365)

    Navigate to ‘Topics’ and select the ‘Greeting’ Topic, this is under ‘System Topics’. Click on the Authoring Canvas button.


    Under the ‘Trigger Phrases’ and select ‘Call an action’. We will now build a new Flow to get the user details we want.

    You will now be navigated to a new screen where you will build your Flow.
    Select the Basic PVA Flow Template

    First give the Flow a meaningful name. Mine is:
    Power Virtual Agents – Get User Info

    Add a Text Input to pass in the Display Name variable

    Next add a ‘Search for users‘ action from office365 connector, and pass in the PVA dynamic value from the trigger

    Now we have all the user details. The results are returned as an Array. To get around this.
    We can add a ‘Get user profile‘ action and pass in the first User Principal Name(UPN)

    We have to use the first() expression, so we don’t get put into an Apply to each loop, my expression:

    first(outputs('Search_for_users_(V2)')?['body/value'])?['UserPrincipalName']
    
    @{first(outputs(‘Search_for_users_(V2)’)?[‘body/value’])?[‘UserPrincipalName’]}

    Lastly in the Return values to PVA action, add all the values you want from ‘Get user profile‘ dynamic content

    Click Save, and close on top right of the screen. Back at the PVA Canvas screen, add your Flow

    Pass in the bot.UserDisplayName variable

    Now we can customize our greeting to only address the user by first name

    As a test I created a Topic called User Details

    Conclusion

    This can be a great way to give your bot more personality. Do keep in mind that this may affect performance.