# Community News Summaries

**Purpose:**\
This workflow aggregates and summarizes community discussions on platforms like Discord, Slack, and Telegram. It provides a concise report of the key topics and queries raised over a defined time period, allowing teams to stay informed without sifting through vast amounts of content.

**Prerequisites:**

* Discord, Telegram, or Slack Loader Agents configured.
* Topic Classification and Sentiment Agents set up to analyze content.

**How it Works:**

1. Loader Agents pull discussion data from Discord, Telegram, or Slack.
2. Topic Classification Agent categorizes conversations by topic.
3. The workflow generates a summary of key topics, sentiment, and questions raised.

**Inputs:**

* Conversation data from community platforms.
* Pre-defined timeframes for analysis.

**Processing:**

* Data is categorized and analyzed to identify the most frequently discussed topics.
* Sentiment Agent evaluates the tone of conversations.

**Outputs:**

* A concise summary of key topics and sentiment over the specified period.

**Usage:**\
The team reviews the summary to get a high-level view of community activity and identify any pressing issues or common queries.

**Example:**\
The summary highlights that most discussions last week centered around API issues, with an overall positive sentiment toward recent updates.

**Advanced Features:**

* Sentiment analysis and alerting for high-priority topics.

**Troubleshooting:**

* **Missing Topics:** Adjust the Topic Classification Agent to ensure all discussions are categorized correctly.

**Logs:**

* Summary reports and logs are available in the Community Platform Summary dashboard.

**Related Workflows:**

* Sentiment Agent for deeper sentiment analysis.
* Q\&A Agent for automatically addressing frequently raised topics.


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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://docs.katara.ai/about/workflows/community-news-summaries.md?ask=<question>
```

The question should be specific, self-contained, and written in natural language.
The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

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.