link

Indicate where the steps to use the tool are located.

content/tools/tool1/index.md

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 title:  POET. Template-Based Prompt Generator
-summary:  POET is a template-based prompt generator for testing large language models (LLMs). It leverages customizable JSON templates to create diverse prompts, enabling comprehensive evaluation across various scenarios and inputs. This tool is complementary to EVA.
+summary:  |
+  POET is a template-based prompt generator for testing large language models (LLMs). It leverages customizable JSON templates to create diverse prompts, enabling comprehensive evaluation across various scenarios and inputs. This tool is complementary to EVA. 
+  To use POET follow the instructions in the github link below. 
 #[GitHub](https://github.com/Trust4AI/POET) # SHORT DESCRIPTION 
 
 

content/tools/tool2/index.md

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 title:  EVA. LLM Response Evaluator
-summary:  EVA takes LLM responses as inputs and classifies them as affirmative or similar. Its primary application is the assessment of large language model (LLM) responses during testing. EVA complements the POET component by evaluating the LLM responses obtained from the promps generated by POET.
+summary:  |
+  EVA takes LLM responses as inputs and classifies them as affirmative or similar. Its primary application is the assessment of large language model (LLM) responses during testing. EVA complements the POET component by evaluating the LLM responses obtained from the promps generated by POET.
+  To use EVA follow the instructions in the github link below. 
 #[GitHub](https://github.com/Trust4AI/EVA)#SHORT DESCRIPTION
 date: 2024-06-05
 

content/tools/tool3/index.md

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 title:  MUSE. AI-driven Metamorphic Testing Inputs Generator
-summary:  MUSE generates test inputs for testing the bias of AI-enabled Search Engines. It leverages the capabilities of Large Language Models (LLMs) to create a wide range of source and follow-up test cases. This tool complements GENIE, which manages communication with LLMs, and GUARD-ME, which checks for bias in responses from the systems under test.
+summary:  |
+  MUSE generates test inputs for testing the bias of AI-enabled Search Engines. It leverages the capabilities of Large Language Models (LLMs) to create a wide range of source and follow-up test cases. This tool complements GENIE, which manages communication with LLMs, and GUARD-ME, which checks for bias in responses from the systems under test.
+  To use MUSE follow the instructions in the github link below. 
 #[GitHub](https://github.com/Trust4AI/MUSE) # SHORT DESCRIPTION
 
 

content/tools/tool4/index.md

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 title:  GUARD-ME. AI-guided Evaluator for Bias Detection using Metamorphic Testing
-summary: GUARD-ME evaluates bias in AI-enabled search engines by evaluating the responses to the source and follow-up test cases. It utilizes Large Language Models (LLMs) to detect any bias and ensure that these systems adhere to ethical standards. This tool is complementary to MUSE, which generates the test cases used, and GENIE, which facilitates communication with LLMs.
+summary: |
+  GUARD-ME evaluates bias in AI-enabled search engines by evaluating the responses to the source and follow-up test cases. It utilizes Large Language Models (LLMs) to detect any bias and ensure that these systems adhere to ethical standards. This tool is complementary to MUSE, which generates the test cases used, and GENIE, which facilitates communication with LLMs.
+  To use GUAR-ME follow the instructions in the github link below. 
 #[GitHub](https://github.com/Trust4AI/GUARD-ME) # SHORT DESCRIPTION
 
 links:

content/tools/tool5/index.md

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 title:  GENIE. Natural Language Enquiry Executor
-summary:  GENIE facilitates the deployment and execution of Large Language Models (LLMs). This tool is specifically designed to integrate with MUSE, which generates test cases following a Metamorphic Testing approach, and GUARD-ME, which analyzes LLM responses to such test cases for the detection of possible biases.
+summary:  |
+  GENIE facilitates the deployment and execution of Large Language Models (LLMs). This tool is specifically designed to integrate with MUSE, which generates test cases following a Metamorphic Testing approach, and GUARD-ME, which analyzes LLM responses to such test cases for the detection of possible biases.
+  To use GENIE follow the instructions in the github link below. 
 #[GitHub](https://github.com/Trust4AI/GENIE) # SHORT DESCRIPTION
 
 links: