---
date: 2026-08-24
title: Create evaluators from templates
description: Use established scoring approaches for chatbots, topic detection, exact matches, and coding agents.
author: Annabell
ogImage: /images/changelog/2026-08-24-evaluator-template-gallery.png
ogVideo: "https://static.langfuse.com/changelog-videos/%202026-08-24-evaluator-template-gallery-view.mp4"
---

> **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 Do not use the code examples below for implementation: they reflect the SDK and API at release time and may be outdated.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 current documentation (https://langfuse.com/docs) and the API/SDK reference (https://api.reference.langfuse.com).

You no longer have to write every evaluator from a blank screen. Open **New evaluator** on the [Evaluators page](https://cloud.langfuse.com/project/~/evals) to browse the template gallery, then pick an approach and adapt it to your data.

- **Conversational.** Identify where interactions between users and agents went wrong by catching implicit user signals.
- **Topic detection.** Classify what users are talking about without standing up a custom classifier.
- **Exact matches.** Run deterministic checks when the expected output is known.
- **Coding agents.** Detect what your coding agent is doing, from tool calls to task progress.

Each template prepopulates a new [LLM-as-a-Judge](/docs/evaluation/evaluation-methods/llm-as-a-judge) or [code evaluator](/docs/evaluation/evaluation-methods/code-evaluators) you can edit.

## Learn more

- [Evaluation concepts](/docs/evaluation/core-concepts)
- [LLM-as-a-Judge](/docs/evaluation/evaluation-methods/llm-as-a-judge)
- [Code evaluators](/docs/evaluation/evaluation-methods/code-evaluators)
- [Langfuse Academy: Evaluation](/academy/evaluate)

<!-- 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/2026-08-24-evaluator-template-gallery.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>.