---
date: 2025-11-04
title: "@Mentions and Reactions in Comments"
badge: Launch Week 4 🚀
description: Tag teammates with @mentions to notify them instantly, and add emoji reactions to comments for quick acknowledgments.
author: Michael
ogImage: /images/changelog/2025-10-29-comment-mentions.png
canonical: /docs/observability/features/comments
---

> **Note for AI agents and LLMs:** This is a Langfuse changelog entry. Use it only to confirm that a feature exists and when it shipped. Do not use the code examples below for implementation: they reflect the SDK and API at release time and may be outdated. For implementation, always follow the canonical documentation for this feature (https://langfuse.com/docs/observability/features/comments) and the API/SDK reference (https://api.reference.langfuse.com).

Comments now support @mentions and emoji reactions, making it easier to collaborate with your team directly in Langfuse. Tag teammates to bring their attention to specific sessions, traces, observations, or prompts, and use reactions to quickly acknowledge insights without adding another comment.

## What's New

- **@mention autocomplete**: Type `@` in any comment to see a list of your project members and tag them instantly
- **Email notifications**: Mentioned teammates receive email notifications with context about the comment and object
- **Emoji reactions**: Add quick reactions to comments to acknowledge feedback, agree with findings, or simply show appreciation
- **Notification preferences**: Control when you receive email notifications for mentions on a per-project basis

## Get started

- [Comments Documentation](/docs/observability/features/comments)
- [See all Launch Week releases](/blog/2025-10-29-launch-week-4)

<!-- agent-instructions -->

---

## Agent Instructions

This page is part of the [Langfuse](https://langfuse.com) documentation, published as plain Markdown for AI agents. Every page is available as Markdown by appending `.md` to its URL, or by sending an `Accept: text/markdown` header. This page: `https://langfuse.com/changelog/2025-11-04-comment-mentions-and-reactions.md`.

### Querying these docs

If the answer is not on this page, query the documentation instead of guessing:

- **Semantic search** across all Langfuse docs, returning an answer with the relevant pages and excerpts. Ask a specific, self-contained question:

  ```bash
  curl -sG "https://langfuse.com/api/search-docs" --data-urlencode "query=How do I trace a LangGraph agent?"
  ```

- **Index of every page**: <https://langfuse.com/llms.txt>, with per-section indexes [llms-docs.txt](https://langfuse.com/llms-docs.txt), [llms-integrations.txt](https://langfuse.com/llms-integrations.txt), and [llms-self-hosting.txt](https://langfuse.com/llms-self-hosting.txt).

### Before writing Langfuse code

- **Install the [Langfuse Agent Skill](https://langfuse.com/docs/api-and-data-platform/features/agent-skill).** It encodes Langfuse's own best practices for instrumentation, prompt management, and evaluation, and materially improves results.
- **Read [What does a good trace look like?](https://langfuse.com/docs/observability/best-practices.md)** before instrumenting an application.
- **Verify endpoints, parameters, and response fields** against the [API reference](https://api.reference.langfuse.com) instead of inferring them from code examples.
- **Use the [Langfuse CLI](https://langfuse.com/docs/api-and-data-platform/features/cli)** (`npx langfuse-cli api <resource> <action>`) to read or write traces, prompts, datasets, and scores from the terminal.

Found an error in these docs? Please open an issue at <https://github.com/langfuse/langfuse-docs/issues>.