> For the complete documentation index, see [llms.txt](https://myros.gitbook.io/bp/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://myros.gitbook.io/bp/applications.md).

# Applications

<figure><img src="/files/J0o1wEX0hAlmE2Hv95Xl" alt=""><figcaption></figcaption></figure>

Myros is designed around one core belief:

> **Knowledge should not sit still.**

For too long, project knowledge has existed as static material: documentation, websites, announcements, FAQs, support pages, and community posts. These sources are useful, but they are not alive. They do not listen. They do not adapt. They do not respond.

Myros changes the relationship between people and information.

Instead of asking users to search through knowledge, Myros lets them speak to it.

A project can deploy Myros as its own knowledge-aware AI agent, connected to curated sources and shaped by the project’s identity. Users can ask questions naturally. Myros retrieves relevant information, applies conversational context, and responds in real time.

This turns the knowledge base from a passive archive into an active intelligence layer.

***

#### From Static Pages to Living Agents

Traditional project knowledge works like a library.

Users enter, search, scan, compare sources, and interpret what they find. This works for technical readers, but it creates friction for everyone else.

Myros works more like a living guide.

She can be deployed into a community, connected to the project’s knowledge sources, and used as an always-available point of access.

| Static Knowledge                       | Myros Knowledge Agent                   |
| -------------------------------------- | --------------------------------------- |
| Requires manual searching              | Accepts natural language questions      |
| Depends on users knowing where to look | Retrieves from approved sources         |
| Often becomes outdated                 | Pulls from live project websites        |
| Feels passive                          | Feels conversational and responsive     |
| Creates support burden                 | Reduces repeated questions              |
| Same experience for everyone           | Can respond with conversational context |

Myros does not replace documentation.

She activates it.

***

#### Designed for Project-Specific Intelligence

Generic AI models can answer general questions, but projects need something more precise.

They need agents that understand their own ecosystem, terminology, products, updates, lore, governance, roadmap, and user flows.

Myros allows each deployment to become project-specific.

A gaming project can create an agent that understands gameplay systems, patch notes, economy mechanics, lore, and onboarding.

A Web3 project can create an agent that understands token mechanics, governance proposals, ecosystem partners, documentation, and community FAQs.

A startup can create an agent that understands product pages, technical documentation, support flows, pricing, and internal processes.

A developer community can create an agent that understands API references, GitHub repositories, contribution rules, and release updates.

The result is not a generic assistant.

The result is a tailored knowledge agent shaped by the project that created it.

***

#### Built for Familiar Interfaces

The first implementation of Myros is designed around Telegram-native interaction.

This matters because users do not want another dashboard, login, or workflow. Communities already live inside messaging platforms. Support questions already happen in chat. Project discussions already happen in real time.

By placing the agent inside Telegram, Myros meets users where they already are.

Users can:

| User Action                                | Myros Response                                            |
| ------------------------------------------ | --------------------------------------------------------- |
| Ask a project question                     | Retrieves and answers from approved sources               |
| Continue a conversation                    | Uses conversation history for context                     |
| Restart context                            | Clears previous conversation history                      |
| Access a project agent through a deep link | Enters the correct project environment                    |
| Interact as a regular user                 | Receives knowledge-based responses without admin controls |

Admins can:

| Admin Action             | Myros Function                                  |
| ------------------------ | ----------------------------------------------- |
| Create a project agent   | Establishes a project-specific knowledge space  |
| Add knowledge sources    | Connects websites to the agent                  |
| Remove sources           | Keeps the knowledge base clean                  |
| Manage access            | Controls admin mode through project credentials |
| Delete or reset an agent | Reconfigures the project environment            |

This keeps Myros simple to deploy, simple to manage, and simple to use.

***

#### Use Case Summary

| Segment              | Primary Value                                |
| -------------------- | -------------------------------------------- |
| Web3 projects        | Community knowledge and user support         |
| Gaming projects      | Player guidance and lore access              |
| Open-source projects | Contributor support and documentation access |
| Startups             | Product support and onboarding               |
| DAOs                 | Governance and community education           |
| Internal teams       | Productivity and operational knowledge       |

Myros is useful wherever knowledge changes quickly, users need answers instantly, and teams need to reduce support friction.


---

# Agent Instructions
This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com.

## 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://myros.gitbook.io/bp/applications.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.
