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4th chunk of `docs/src/ai/agent-panel.md`
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### Model Support {#model-support}

Tool calling needs to be individually supported by each model and model provider.
Therefore, despite the presence of tools, some models may not have the ability to pick them up yet in Zed.
You should see a "No tools" label if you select a model that falls into this case.

We want to support all of them, though!
We may prioritize which ones to focus on based on popularity and user feedback, so feel free to help and contribute to fast-track those that don't fit this bill.

All [Zed's hosted models](./models.md) support tool calling out-of-the-box.

### MCP Servers {#mcp-servers}

Similarly to the built-in tools, some models may not support all tools included in a given MCP Server.
Zed's UI will inform about this via a warning icon that appears close to the model selector.

## Text Threads {#text-threads}

["Text threads"](./text-threads.md) present your conversation with the LLM in a different format—as raw text.
With text threads, you have full control over the conversation data.
You can remove and edit responses from the LLM, swap roles, and include more context earlier in the conversation.

For users who have been with us for some time, you'll notice that text threads are our original assistant panel—users love it for the control it offers.
We do not plan to deprecate text threads, but it should be noted that if you want the AI to write to your code base autonomously, that's only available in the newer, and now default, "Threads".

### Text Thread History {#text-thread-history}

Content from text thread are saved to your file system.
Visit [the dedicated docs](./text-threads.md#history) for more info.

## Errors and Debugging {#errors-and-debugging}

In case of any error or strange LLM response behavior, the best way to help the Zed team debug is by reaching for the `agent: open thread as markdown` action and attaching that data as part of your issue on GitHub.

This action exposes the entire thread in the form of Markdown and allows for deeper understanding of what each tool call was doing.

You can also open threads as Markdown by clicking on the file icon button, to the right of the thumbs down button, when focused on the panel's editor.

## Feedback {#feedback}

Every change we make to Zed's system prompt and tool set, needs to be backed by an eval with good scores.

Every time the LLM performs a weird change or investigates a certain topic in your codebase completely incorrectly, it's an indication that there's an improvement opportunity.

> Note that rating responses will send your data related to that response to Zed's servers.
> See [AI Improvement](./ai-improvement.md) and [Privacy and Security](./privacy-and-security.md) for more information about Zed's approach to AI improvement, privacy, and security.
> **_If you don't want data persisted on Zed's servers, don't rate_**. We will not collect data for improving our Agentic offering without you explicitly rating responses.

The best way you can help influence the next change to Zed's system prompt and tools is by rating the LLM's response via the thumbs up/down buttons at the end of every response.
In case of a thumbs down, a new text area will show up where you can add more specifics about what happened.

You can provide feedback on the thread at any point after the agent responds, and multiple times within the same thread.

Title: Agent Panel: Model Support, Text Threads, Errors/Debugging, and Feedback
Summary
This section covers the Agent Panel's model support and MCP server compatibility, noting that not all models support tool calling or all tools within an MCP server. It introduces text threads, which offer raw text conversations with full user control, and explains that these are saved to the file system. It details how to report errors and debug issues by exporting threads as Markdown. Finally, it emphasizes the importance of user feedback via thumbs up/down ratings to improve the system prompt and tools, and clarifies Zed's approach to AI improvement, privacy, and security regarding data collection.