# Features

#### 1. Comprehensive Project Analysis

* Detailed research and analysis of any crypto project
* Scoring across six critical attributes
* TLDR summary for quick overviews
* Strengths and weaknesses identification
* Technical Analysis on real-time price data

#### 2. Multi-faceted Research Process

* Gets research data from verifiable sources using Perplexity API (sonar-pro)
* Presents unbiased report with focus on verifiable data
* Provides inline citations and source attribution

#### 3. Quantitative Scoring

* Overall project score on a scale of 0-10
* Individual attribute scores with explanations
* Analysis phase powered by advanced reasoning models (DeepSeek R1)

#### 4. Social Impact Analysis

* Community sentiment analysis
* Social media trend monitoring
* Key themes in recent news
* Market position evaluation

#### 5. Interactive Reports

* Tabbed interface with Research, Analysis, and Social Impact sections
* Support for price chart visualization for tokens
* Project summary with key features

#### 6. Autonomous Trend Monitoring/Sharing

* Monitors KOLs and automatically analyzes highlighted projects
* Auto-generated tweets about analyzed projects
* Image-based project summaries for X
* Scheduled posting capabilities

#### 7. Chat Interface

* Ask follow-up questions about analyzed projects
* Get clarification on specific points in the analysis
* Explore additional aspects not covered in the main report

<figure><img src="/files/6uhCyX7UipcWK07WhHkh" alt=""><figcaption><p>SAG3 Chat Core</p></figcaption></figure>

### Ok but it's still just a GPT-wrapper, right?

Yes that's right, but it's also so much more. SAG3.ai is a GPT-wrapper that leverages 5-6 distinct large language models that each specialize in a certain field running in parallel to produce very high quality crypto-native research and analysis that you won't find anywhere else.

You could just do the research yourself, but that would take hours. SAG3.ai does it in seconds.


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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.sag3.ai/sag3-platform/editor.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.