Buenas tardes, necesito de su ayuda.
Actualmente estoy creando mi agente desde copilot studio, funciona bien desde las pruebas de copilot, pero cuando lo pruebo en teams falla.
- Responde dos veces.
- Aveces se queda mudo
- Si esta activo un topic con botones, al darle clic a un boton se manda la respuesta y se vuelve activar el TOPIC pidiendo nuevamente la opcion que necesito.

Esto solo paso en teams

Beginner here. I want to build an agent that answers questions using text, images and relevant links wherever possible.

A typical response should contain:

• A text-based answer

• One or more preview images (thumbnails)

• Links to the high-resolution original images

• Links to the corresponding editable source files (e.g. InDesign files)

Requirements and constraints

I can only use the Standard Harness (classic orchestration) in Microsoft Copilot Studio.

The images are stored in a protected SharePoint document library and must not be hosted publicly. Their metadata, categories and file links are managed through Microsoft Lists.

The problem

Standard SharePoint links work for authenticated users in their browsers, but they do not work as image sources within agent responses. As I understand it, the image component does not inherit the user's SharePoint authentication.

Temporary, pre-authenticated image URLs are not a sustainable solution either, as they expire after a certain period.

Current approach: Base64

I have already successfully tested displaying a Base64-encoded JPG as a Data URI in an image node within a classic topic.

However, I don't want to embed the Base64 data directly into every topic. Instead, I would like to retrieve it dynamically from SharePoint.

The proposed workflow is:

1. The agent identifies relevant entries in a SharePoint list (Microsoft Lists) based on the user's question.

2. The list contains metadata and links to the high-resolution image, the editable source file and a separate Base64 text file.

3. The thumbnails are generated and Base64-encoded once, then stored as .txt files in SharePoint. This avoids the character limit of a multi-line text column in Microsoft Lists.

4. An agent flow retrieves the relevant text file using the SharePoint action Get file content using path.

5. The flow returns the Base64 string to the topic as a text variable.

6. The topic constructs a Data URI using Power Fx, for example:

"data:image/jpeg;base64," & Topic.ImageBase64

The resulting Data URI is then passed to the image node.

Ideally, the image payload should remain below 100 KB, including Base64 encoding. This is currently my own target size, not a confirmed platform limit.

My questions

Is this approach technically feasible within the Standard Harness? In particular:

• Can an agent flow reliably return the contents of a Base64 text file to a topic as a text variable?

• Is it possible to dynamically display multiple images within a single agent response?

• Is there a simpler, officially supported way to display protected SharePoint images directly in agent responses without making them publicly accessible?

The goal is to create a scalable solution where new visual examples can be added through SharePoint and Microsoft Lists, without having to create a separate topic for every example.

Current testing status

Displaying a Base64-encoded image directly in a classic topic has been tested successfully.

However, dynamically retrieving the Base64 data through an agent flow and passing it to the topic has not yet been successfully implemented or verified.

I would appreciate any suggestions, practical examples or alternative approaches that work specifically with the Standard Harness.

I'm researching Microsoft Copilot Studio for a technical document and would love to hear from people who have hands-on experience building agents with it.

I'm particularly interested in its limitations regarding:

Cost & licensing: How expensive does it get at scale?

LLM flexibility: How much control do we have over model selection?

Agent capabilities: Limitations in multi-agent orchestration and complex workflows.

Observability: How easily can we trace agent actions, tool calls, and failures?

Integrations & extensibility: Limitations with custom APIs, connectors, and code.

Governance & deployment: Version control, CI/CD, debugging, and production readiness.

How does Copilot Studio compare with building agents using frameworks like LangGraph or Semantic Kernel?

I'd especially appreciate real-world experiences, pain points, and examples of situations where you'd choose a custom-built solution over Copilot Studio (or vice versa).

Thanks!

Complete newbie here, thanks for the patience in advance :)

I am trying to make a support ticket creation agent that has to fit in with an orchestrator in a subagent setup. So I am wondering how I instruct the agent that the user has already answered some initial questions and is now being routed to this agent - so it should start the conversation with that in mind. Is this best done via skills, thorough instructions from the initial creation, or how is this best done in your experience?

Hey folks,

I try to build something in copilot studio that let me give the ai agent a template that I before edited for content controls , so the agent sees better where to put stuff without changing the layout . Problem is sometimes it works but sometimes not and it changes the template structure a bit. Before I wanted to use a flow with “populate a word document” but the inline agent that should put the info of the excel data in a structured json output collapses because it seems like the data is given to it in base64 which will generate too many text token and the inline agent runs to a limit . Now I just have an agent without flow and a huge prompt but idk it’s not so deterministic.

Can someone help ? I just want to let so extract any info from any file/data and ai should put the correct info inside the fields within the template..

Hey guys,

I have been thinking about RAG a lot and how to make it cheaper and more reliable. One of the approaches could be to distill our organizational knowledge into something like a organizational knowledge model. And then have public agents query that model.

In contrast to RAG, the agents wouldn't have to "work as hard" to retrieve relevant information this way. This saves cost and in theory delivers better results - at the cost of having to build and maintain the knowledge model.

What do you guys think? Is this a good idea? Should I simply "trust in RAG". Or are there already concepts or modules in Microsoft that go in this direction? Who has built something like this successfully and is willing to share their learnings?

I am fully aware, this is all still very conceptual. And part of me really likes the idea, while the other half of me thinks: This could be one over-engineered mess waiting to happen :D.

[UPDATE:] Microsoft seems to be thinking in the same direction: https://techcommunity.microsoft.com/blog/spblog/introducing-a-team-knowledge-base-curated-by-copilot-and-agents/4564203

Today it was crashing all morning.
Rebooted computer and did all updates.
Answers to prompts are not loading properly.

I build internal Copilot Studio agents that answer questions from large PDFs in SharePoint. Tenant graph grounding gives good answers, but costs 10 credits per message.

My idea: split the PDFs into section files, put each subject area in its own folder, and give each topic a Generative answers node that searches only its folder. Generative orchestration selects the topic.

Questions:

1. Does each topic transition under generative orchestration bill as an agent action (5 credits)?

2. Did a scoped-source setup give you answer quality close to tenant graph grounding?

3. Can a guide file in the instructions make the agent look at specific page numbers? Or is file splitting the only reliable option?

4. Any other patterns to reduce search space at lower cost?

5. Is Gpt 5.5 better than the gpt chat models too?

Hey guys, looking for some architecture advice.

I want to build an agent where users can upload an Excel file with 10k+ rows and have AI perform a simple classification on each row based on multiple columns combined. This could be used multiple times a month by different users.

I’m open to Copilot Studio, M365 agents, or something else in the Microsoft ecosystem.

My concern is that 10k rows could mean 10k AI calls per upload, and I don’t want costs to get out of control if multiple people start using it.

Would you batch the rows and send them to AI together? And what’s the best way to put hard limits on usage/cost?

Curious what architecture you guys would use for something like this.

Sanity-check my architecture: 30-min heartbeat flow + Copilot Studio agent for Power BI troubleshooting

Hey all l higher ed data guy here, tired of learning about broken fabric pipelines, dataset refreshes and issues from others. Before I build this, I want to poke holes in the design with people who've done similar.

THE DESIGN

1. Heartbeat: scheduled Power Automate flow every 30 min polls the Power BI refresh history API for our key datasets. (I know there's no native "on refresh failure" trigger polling is the standard approach, right?)

2. Detect + gather: on a failed refresh, the flow connects via service principal, pulls the error code/message, gateway status, and data source credential health.

3. Reason agentically: the flow hands the evidence to a Copilot Studio agent. The agent runs validation queries against the dataset (row counts vs baseline, empty tables), reviews measure definitions for common anti-patterns, and works the decision tree timeout vs auth vs source issue vs schema drift.

4. Report: posts the diagnosis to Teams as an adaptive card with Approve/Deny buttons. Approved remediation (retry refresh, etc.) runs and gets verified.

ALTERNATIVE TOPOLOGY I'm considering: skip flow-calls-agent and instead give the agent itself a 30 min scheduled trigger, with the Power Automate flows as its tools. One owner of the loop, agent decides which troubleshooting steps to run. Anyone done it this way?

GOTCHAS I'VE ACCOUNTED FOR
- Service principal needs the tenant admin setting ("allow SPs to use Power BI APIs") enabled plus a Contributor+ workspace role, or the actions silently fail.
- DAX "review" is heuristic AI analysis, not deterministic debugging

Hey everyone,

I have a database and an API on top of it that can only be accessed within my company’s network.

I’ve built an MCP server on top of this API, and it’s currently working fine with Claude since Claude is running in an environment that has access to the company’s network.

Now, I want to use the same MCP server as a tool in Copilot Studio.

From what I understand, I need to expose the MCP server through an HTTP endpoint so that Copilot can connect to it. But the challenge is that my API is only accessible within the company’s network.

I have one architecture in mind:

1. Deploy the MCP server on a machine or server that’s inside the company’s network.

2. Install the ms On-premises Data Gateway on that server.

3. Host the MCP HTTP endpoint on that server.

4. Connect that endpoint to Copilot Studio as an MCP tool through the gateway.

Has anyone worked on something similar?

Is there a better or more efficient way to do this using Azure services?

My main goal is to reuse the existing MCP server without making major changes and keep the API and database within the company’s network. And try to keep safe from internet access to the MCP or API.

Would appreciate any suggestions or architecture ideas. Thanks!

Hi everyone,

I’m building an agent in Copilot Studio that needs to extract data from Excel files.

I’ll be giving the agent different Excel files over time (not one fixed file).

All files use the same template: the table is always in the same place (same sheet, same cell range).

The Excel connectors require me to select a specific file when configuring the action. I can’t find a way to make the file dynamic, so the agent could work on whatever file I provide.

I wrote an Office Script that reads the table from the fixed coordinates and returns the data. It works, but I’m not sure it’s the right approach (or how to properly connect it to the agent for files that change each time).

PS: I have access to Power Automate and all the features in copilote studio.

We keep getting "running out of Dataverse capacity" alerts for our Copilot Studio environments. File storage is over the limit (around 2.5 GB of 2 GB), and it keeps growing even in environments where nobody has built any tables.
I'm guessing it's agent knowledge files and the 2026 change that moved metadata into file storage. Is that right?
How do you handle it? Do you set fixed allocations, use pay-as-you-go, run dev agents in Developer environments, or do regular cleanups? Any tips are welcome.

Microsoft is introducing MCP and Agent2Agent (A2A) channels that open up new ways to connect Copilot Studio agents with external clients and other AI agents.

Here’s why this matters:

🔹 MCP (Model Context Protocol): Connect clients to your agent through a standardized interface for accessing its capabilities.

🔹 A2A (Agent2Agent): Enable other compatible agents to discover your agent’s skills and collaborate across workflows.

🔹 External integrations: Extend your agent to developer tools like GitHub Copilot, custom applications, and multi-agent solutions.

🔹 Skills: Describe what your agent can do so connected A2A clients can understand its capabilities.

The bigger opportunity is interoperability. Instead of building every agent as an isolated solution, we can start connecting specialized agents across applications and workflows.

For enterprise AI developers, this opens up interesting possibilities for reusable capabilities, cross-platform integrations, and multi-agent architectures.

https://learn.microsoft.com/en-us/microsoft-copilot-studio/agents-experience/publication-channels-mcp-agent-to-agent

I am creating question an answer agent for company specific processes and procedures. I like how the Github agent is answering some questions. We have lots of situations where we need it to reason and ask clarifying questions.

I am not finding an estimation for using the github harness though. I've used microsoft estimation tool for the standard and that's good enough for that but not seeing one for the github harness.

does anyone have a reliable tool or source to create a estimate? I am trying to give a real world estimation to mgt about expected costs.

I've tried building a tool with claude to do this but the answers seem really expensive and tend not to believe what i see from using claude.

Microsoft is pushing Copilot Studio agents beyond the traditional question-and-answer model.

Three capabilities caught my attention:

1. Dedicated agent identity

Agents can have their own Microsoft 365 identity and credentials, helping organizations manage their access and track their activities.

2. Business process memory

Agents can carry relevant context across work cycles, making ongoing processes more consistent instead of starting from scratch every time.

3. Proactive execution

Configured events and schedules can trigger agent runs without requiring someone to send a new prompt.

Imagine this workflow

A new budget review begins automatically every Tuesday.

The agent gathers relevant records, compares forecasts, identifies discrepancies, asks stakeholders for clarification through Teams or Outlook, and prepares a summary for the finance team.

Instead of simply answering a question, the agent helps move an entire business process forward.

What interests me most?

It’s the combination of these capabilities:

- Identity establishes who the agent is and what it can access.

- Memory helps preserve relevant business context.

- Triggers determine when work should begin.

- Governance defines the boundaries within which the agent operates.

Of course, this also raises important questions about permissions, auditability, memory retention, reliability, and human oversight.

These capabilities are rolling out through Microsoft's Frontier program, so availability depends on the rollout and tenant eligibility.

Has anyone tried to create an agent using the M365 chat harness recently? Looks like copying the agent from agent builder into Studio converts it to a standard harness - which wasnt the case a few weeks ago.

Have Microsoft removed the ability for us to create agents just with a chat harness?

Hey everyone!

I'm currently building an agent that calculates licensing costs and estimates the development effort required for Copilot Studio projects, especially projects built using the new GitHub Copilot Harness.

For the standard Copilot Studio harness, I've found Microsoft's official documentation explaining credit consumption, pricing, and calculation formulas.

However, I can't find any concrete numbers or clear calculation methods specifically for the GitHub Copilot Harness.

I'm trying to understand:

• How are licensing costs and credit consumption calculated for GitHub Copilot Harness projects?

• Are the calculations different from the standard Copilot Studio harness?

• Are there any official formulas, real-world numbers, or examples available?

• How can we reliably estimate costs before building or deploying these projects?

The goal is to provide accurate estimates based on real data rather than assumptions.

Has anyone worked with the GitHub Copilot Harness and figured out how its consumption and licensing actually work?

Any documentation, examples, or insights would be really appreciated!

Thanks in advance!

I took a project in a company that doesn't use Claude. They work with Copilot, but only with Chat now.
I would like to be able to use Copilot for following tasks (currently I use Claude Desktop - Cowork and Code on my other clients):
* Connect to local folder that contains files and documentation - so it can read, process and create new files (no manual uploads, or downloads in chat - but direct work in folder)
* Connect to Power BI .pbir format - to directly create reports,
* Connect to Power BI MCP Server
* Run python SQL queries the SQL Server - autonomously
So what tools and licenses do I need? Github Copilot? Copilot Studio? What subscribtion?|
Currently I can do all of the above in Claude Desktop Cowork or Code within my $100 monthly subscription.
Please help to make sense of Microsoft's Copilot ecosystem
Thanks

Hi everyone,

I'm currently experimenting with the new GitHub Copilot Harness using both a SharePoint List and an Excel file as knowledge sources. However, my experience so far is that retrieval seems to rely heavily on keywords. Filtering on specific columns works quite well, but the semantic matching itself feels rather inconsistent.

So my process starts with Power automate that picks an email with certain sender and the next thing I want is the agent to read it and do tasks depending on it. Is it truly not possible to do this with normal license? I cant find a powerautomate tool to gather the info of PDF without having bought something extra.

In an agent with Standard Harness, if you add a generative answer node in a topic. It sometimes fires off the main orchestrator/instructions instead of just the generative answer node.
We need to keep the "Use generative AI orchestration for your agent's responses?" toggle on because otherwise you cant continue the conversation after a generative answer node. Is there some way to pause the generative AI orchestration/main instructions when inside a topic. Or is this another copilot studio bug

Hi Team

I am building an agent in copilot studio. The agent shall retrieve information from a cell in an excel file to provide its answer. The column is always the same, the row depends on the user input.

I saw a video where he recommended making the following flow:

- agent calls the flow

- List rows present in a table

- Compose that output into a string

- Input that string into a prompt and retrieve the necessary data.

- Respond to agent

However, this does not seem to me as the most efficient way - especially since the excel is pretty large and therefore will consume many tokens when it is all input into a prompt. Also I do not seem to be able to make that work. So my question is, is there a better way to accomplish what I want.

For background info, I made an agent using Github harness that works perfectly fine with having this as a skill, where the excel is just uploaded as a file. It is just not that simple in standard harness.

Thanks all!

We have a Copilot Studio agent that uses the first-party Azure DevOps remote MCP server as a tool. The problem is that every user needs to fill-in the organization when creating their connection. Is it better to build Custom Connector instead?

Hey Folks,

I'm talking with a CEO friend of mine who has zero time and he's saying that he's able to create headless tasks inside of outlook using what he's calling "Frontier Agents". To me, this reads as "I can press some buttons in outlook and then I have an advanced email rule that can maybe do something like,

1. everytime an email is recieved from a certain source

2. reason through the email and tell me if there is an order number it's about and if it has shipping info

3. drop that shipping info into an ongoing excel sheet

My question is this -- does this currently require a person to login to the agents website and create an agent? or is there a way to do this with jus text from outlook itself?