Update TRANSPARENCY_FAQS.md

Co-authored-by: Mark Sze <[email protected]>

TRANSPARENCY_FAQS.md

@@ -53,6 +53,6 @@ Additionally, AG2's multi-agent framework may amplify or introduce additional ri
 ## What operational factors and settings allow for effective and responsible use of AG2?
 -	Code execution: AG2 recommends using docker containers so that code execution can happen in a safer manner. Users can use function calls instead of free-form code to execute pre-defined functions only, increasing reliability and safety. Users can also tailor the code execution environment to their requirements.
 -	Human involvement: AG2 prioritizes human involvement in multi agent conversation. The overseers can step in to give feedback to agents and steer them in the correct direction. Users can get a chance to confirm before code is executed.
--	Agent modularity: Modularity allows agents to have different levels of information access. Additional agents can assume roles that help keep other agents in check. For example, one can easily add a dedicated agent to play the role of safeguard.
+-	Agent modularity: Modularity allows agents to have different levels of information access. Additional agents can assume roles that help keep other agents in check. For example, one can easily add a dedicated agent to play the role of a safeguard.
 -	LLMs: Users can choose the LLM that is optimized for responsible use. For example, OpenAI's GPT-4o includes RAI mechanisms and filters. Caching is enabled by default to increase reliability and control cost. We encourage developers to review [OpenAI’s Usage policies](https://openai.com/policies/usage-policies) and [Azure OpenAI’s Code of Conduct](https://learn.microsoft.com/en-us/legal/cognitive-services/openai/code-of-conduct) when using their models.
 -	Multi-agent setup: When using auto replies, the users can limit the number of auto replies, termination conditions etc. in the settings to increase reliability.