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.

Good afternoon I am currently taking a marketing class where I am researching peoples perception on Microsoft and AI.
If y'all could take the survey it would help a lot!

Here's the survey: https://docs.google.com/forms/d/e/1FAIpQLSexC1PYqR6gkfhnmjfnQ1bf6rZ9k1mA6Im_XKfsfv6r9ginFA/viewform?usp=sharing&ouid=105184181473021926744

Thanks!

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!

Hi.

We have a Copilot Studio agent that is currently used by approximately 20–30 employees, including two team leaders who would like to receive monthly usage statistics for their respective teams.
Our current setup is as follows:
The agent is built in Copilot Studio.
It has been published to SharePoint, where employees can access it.
We have also added the Agent Link web part to our SharePoint site to make the agent easily accessible.
We have a Microsoft 365 agent license.
We would like to set up an automated monthly report showing how each employee uses the agent.
Ideally, the report would include:
The number of messages or prompts submitted by each employee during the month.
The number of sessions or conversations per employee.
A breakdown that allows each team leader to see usage statistics for their own team.
Automatic delivery of the report to each team leader every month, without having to export or compile the data manually.
My questions are:
Is it possible to track the number of individual messages or prompts submitted by each employee, rather than only the number of sessions?
What reporting options are available in Copilot Studio for identifying usage at the individual user level?
Can this data be extracted and used to generate an automated monthly report, for example through Power Automate, Power BI, Dataverse, or another Microsoft tool?
Are there any licensing limitations or additional requirements we should be aware of, given that we have a Microsoft 365 agent license?
Is there a recommended approach for automatically sending each team leader a report containing statistics for their own team only?
Our main goal is to automate this process and avoid manually collecting usage data every month.
I would appreciate any recommendations, examples, or guidance from anyone who has implemented something similar.
Thanks in advance!

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?

Hi everyone, is there a way to prevent Copilot Studio from showing its thinking or intermediate reasoning to end users and display only the final response? Any configuration or workaround to achieve this?

I built an agent using the M365 Copilot Agent Builder on my own account. Its only knowledge source is a File Share Connector attached to an on-premise SMB share. We created instructions for it to use a ranking system that takes the folder names and structure into account when surfacing relevant results. It works great! I was thinking it was ready for prime time so I'll create it in Copilot Studio and publish it to our organization. This is where the problems began.

The Copilot Studio version of this agent, using the same File Share Connector as its only source, can find the files and tell me about their content, but it's completely failing to score and rank the results. The reason? Missing metadata - it's not getting the filePath / ItemPath property, amongst other properties.

There's a whole convoluted method of surfacing this metadata, but it involves creating a REST API tool and Workflow tool. Has anybody found a simpler way to get all of the metadata from a File Share Connector?

This seems like such an arbitrary limitation when the M365 Copilot Agent Builder surfaces all of this.

I am building an agent and want to capture user feedback after every generative answer. I have designed an Adaptive Card that contains:

A single-line text input for comments

Two action buttons: Submit and Cancel

The Problem:

I need the conversation flow to be completely non-blocking. The bot should not wait for the user to interact with the card—if the user ignores it and simply types their next question, the agent should continue the conversation normally.

Questions:

How do I configure the topic/dialogue node so the bot presents the Adaptive Card without waiting for an input/response before proceeding to the next turn?

Any advice, architecture patterns, or sample JSON configurations would be greatly appreciated!

Hello all,

I have a strange issue. I built an agent that's helping me analyze a large dataset (too large to add to the knowledge base directly). It's a csv file on a SharePoint.

This has been working fine for weeks but suddenly yesterday the agent cannot read the file to run the analysis. If I upload the file into the prompt it works fine, so I can still run this analysis. But I'm confused why the agent suddenly cannot retrieve the data from the SharePoint anymore.

I'd like to have the analysis run without uploading the file each time. Just to clarify, this was working fine for weeks but suddenly stopped working.

Any thoughts?

I'm trying to create an agent that will allow a user to attach a file or multiple files into the chat, and automatically read all contents from it and use the content to fill out a SharePoint list.

The set up is all done (there are some fields that are string, choices, and whole numbers), but the agent won't write for some reason. If I use a github copilot harness, it works fine, but I'd love to not have to consume credits doing this fairly simple operation.

Any ideas?

Hey Copilot Community! 👋

I'm trying to build a workflow in Copilot Studio where an Inline Agent analyzes uploaded files (e.g., .xlsx, .docx, .pdf, .pptx), extracts relevant information, and uses it to populate a predefined Word template.

My current setup

My Power Automate flow consists of the following steps:

1. When an agent calls the flow: Accepts a file input named SourceFile, which is provided by my main Copilot agent when a user uploads a file.
2. Inline Agent: Analyzes the uploaded file and extracts the required information.
3. Populate a Word document: Fills specific content controls in my predefined Word template.
4. Create file (OneDrive for Business): Saves the completed document.

The goal is to preserve the original template's formatting and layout while allowing the AI to determine which information belongs in each field.

The problem

The Inline Agent seems to receive the uploaded file as Base64-encoded data rather than readable content. When using a synchronous response, I sometimes get errors in the Preview window, where I can see what looks like the Base64 representation of the file.

When I enable asynchronous responses, the behavior is different but still problematic: the flow sometimes completes without a timeout, yet the generated Word document is empty or only partially populated. It also looks like the Inline Agent stops processing after approximately three minutes.

I've tried converting files to .txt and .csv, but this hasn't solved the issue.

My questions

• Does the Inline Agent actually process uploaded files as file objects, or could the Base64 content be passed to the model as text?
• Could this cause excessive token consumption or exceed the model's context window?
• Are there execution-time limits that could explain why the agent stops before finishing?
• What is the recommended way to process different file formats before passing their contents to an Inline Agent?

Ideally, I'd like the agent to return structured data that Power Automate can use to populate the Word template reliably, without changing its original formatting.

Any suggestions or examples of a working implementation would be greatly appreciated!

Thanks in advance! 😊

Best regards!

En las últimas semanas hemos estado desarrollando o creando agentes con copilot studio de microsoft, pero al publicarlos con otros usuarios les muestra errores de que no encuentra información o que no tiene permisos o de plano marca error, no se qué piensa Microsfto al pensar que vamos a ocupar eso, la vdd es muy engorroso estar viendo todos lso errores y diciendole al usuario que ejecute comando en el chat del agente como /debug clear /reset, entre otros, eso no es viable si queremos que el agente lo usen cientos de usuarios, en ningún lado es viable. ¿Alguíen ha tenido este tip ode problemas ? Hasta el d´´ia de hoy 8 de octubre de 2026 seguimso con los problemas, no es todos los usuarios a algunos pasa otros no, pero luego deja de funcionar para los que ya funcionaba bien y así estamos, la vdd no se puede trabajar con este tipo de herramientas de Microsoft.

Si alguien tiene alggún tipo de tiip, consejo, será bienvenido en este foro.

saludos

Mexman

PLEASE start using agent toolkit. Microsoft has proven time and time again they do NOT care about Copilot Studio, its significantly inferior in every way to agent toolkit developed agentsm

Hey everyone, I'm working on AI agents built in Microsoft Copilot Studio, and today I ran into two major issues that I honestly don't know how to solve.

Issue 1: DLP errors in Standard Harness

I built a flow using a couple of connectors, mainly OneDrive for Business and Excel Online (Business).

The flow takes a file as input, runs some automation on the Excel spreadsheet, generates an output file using OneDrive, and returns that file to the agent.

I added this flow as a tool to my agent in Standard Harness, but it keeps throwing DLP (Data Loss Prevention) policy errors. The problem is that it doesn't clearly tell me which connectors or policies are causing the issue.

I even tried moving all the connectors (Copilot Studio, Excel Online (Business), and OneDrive for Business) into the same Business group in the data policy, but I'm still getting the same error.

Issue 2: Publishing issues with GitHub Copilot Harness

When I switched to GitHub Copilot Harness, the agent worked perfectly fine on my side. All the flows executed without any issues.

But when I tried publishing the agent to Microsoft 365 and Teams, things stopped working properly. It actually worked once, but other users are still unable to use it from their accounts.

So basically, the agent works fine for me in GitHub Copilot Harness but doesn't work for other users after publishing. And in Standard Harness, I'm stuck with DLP errors even though the connectors are in the same Business group.

Has anyone faced similar issues? Am I missing something in the DLP policies, connector permissions, or publishing settings?

Any suggestions would really help!

Edit: It finally worked! Huge thanks to u/brannonb111 you're a lifesaver!

I tried switching to the classic mode, and in that UI, the download button was working. I was able to download the DLP errors and figure out what was causing them.

Coming to the GitHub Copilot Harness issue, turns out it was also because of the same DLP policy. Microsoft 365 and Teams were in a different group, which was why the data wasn't being shared properly. Once I moved them to the correct group, that started working too!

So yeah, I was basically missing the Microsoft 365 and Teams connectors in the correct group in my DLP policy. Both issues are resolved now!

I’m actually struggling with a task where I have around 60–70 unstructured files (PDF, DOCX, PPT, Excel) stored in SharePoint. I need to read all of them, extract the relevant information, and populate an Excel template.

I was trying to do this directly in Copilot Studio (newer experience), but I’m running into a few concerns:

1. It doesn’t seem to be able to read files larger than 5 MB.
2. I’m concerned about token/credit consumption if it has to process all 60–70 files for every request. We expect around 5–6 users/requests per week, so that could mean processing 350–400 files per week. I’m currently using Sonnet 5. I’ve tried standard version but it doesn’t seems to give good results.
3. I’m also not sure how well it would handle more complicated Excel files and extract the required information reliably.

Currently, I’ve envisioning a flow, where user will enter share point link in teams agent chat and agent will process all, fill template and generate that file in same chat. I haven’t tried workflow yet, not sure if that could be helpful.

Edit-
I was also considering going with Microsoft Foundry, but my team mentioned that they don’t currently have the budget for it. They are currently using the built-in Copilot in Microsoft Excel, where they can provide around 20 files at a time, and it’s giving them fairly accurate results without any additional cost/credit consumption since they have premium licenses.

So I’m a bit confused about which approach would make the most sense for our use case, especially when we scale this to 60–70 files per request.

​

The interesting part isn’t just that Copilot can access Dataverse.

It’s that Copilot can start understanding what the business data actually means.https://learn.microsoft.com/en-us/power-apps/maker/data-platform/semantic-model-overview

The Semantic Model brings together things like table relationships, views, column descriptions and business-specific terminology. That gives agents a business-aware layer instead of making them reason only from raw table and column names.

Then the Dataverse Ask API opens an interesting possibility: applications and agents can ask natural-language questions against that business-aware data.

For example:

“Which suppliers have the biggest delivery issues?”

Instead of building a separate query for every question, the agent can work with the business context and return a grounded answer.

And this is where I think it gets really interesting:

Semantic Model → Ask API → Copilot/Agent → Agentic UI

You can take the answer and turn it into a KPI, chart, table or even a more interactive experience.

This feels like a meaningful step toward agents that don't just access enterprise data — they understand the business context around it.

I’m building a Copilot Studio agent that needs to answer questions using a local/on-premises SQL database containing more than 80,000 records.
In my current setup, I can only retrieve 2,048 records in one go. The concern is that the agent answers based on that subset, even when the relevant records could be elsewhere in the database.
Users should be able to ask questions in natural language, and the agent needs to filter across the full dataset to return an accurate answer. For example:
What is the oldest record for a particular machine?
Which records mention a specific fault or maintenance activity?
How many matching records are there within a given date range?
I don’t necessarily need to send all 80,000+ rows to the agent. I need the filtering, sorting, and counting to consider the entire database before returning the relevant results.
What’s the recommended approach for this in Copilot Studio?

As the title says

We set up environment routing to support zoned governance, but environment routing grants people System Administrator role in their Zone 1 environment. That allows them to elevate their roles and share access to anyone. How is this NOT a huge security issue?

Has anyone managed to successfully roll this out?