# TELeR: A General Taxonomy of LLM Prompts for Benchmarking Complex Tasks

In one interesting paper the authors emphasize the importance of a standardized taxonomy for LLM prompts targeted towards solving complex tasks and, subsequently, provide such a taxonomy, i.e., TELeR, which can be utilized by multiple independent researchers who are conducting such research studies in order to report their results using a single unified standard. 

As developers we can look at the best level (i.e. level 6) and use all the listed promt details for our prompts we design for our task.

<figure><img src="/files/YrqBBQIXnV8FCnCUW1Rz" alt=""><figcaption><p>Image Source: Santu et al. (2023)</p></figcaption></figure>


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# Agent Instructions: Querying This Documentation

If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question.

Perform an HTTP GET request on the current page URL with the `ask` query parameter:

```
GET https://opencampus.gitbook.io/opencampus-machine-learning-program/courses/archive/deep-dive-into-llms/week-4-prompt-engineering/framework-of-prompting-of-complex-tasks.md?ask=<question>
```

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Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.