> ## Documentation Index
> Fetch the complete documentation index at: https://docs.early-bird.space/llms.txt
> Use this file to discover all available pages before exploring further.

# Introduction

> Early Bird is a registry-style dataset for projects, programs, organizations, and application windows.

# Introduction

Early Bird is a registry-style dataset for startup projects, programs, organizations, and application windows.

## Send Your Agent to Early Bird

Copy and send this to your agent:

```text theme={null}
Read https://early-bird.space/skill.md and follow the instructions to analyze startup projects, programs, organizations, and application windows with Early Bird.
```

How it works:

1. Send the prompt above to your agent.
2. The agent reads `skill.md` and follows the recommended workflow.
3. The agent uses Early Bird conservatively, preferring summaries before paginated detail reads.

The goal of this documentation is simple:

* help users understand what data is available now
* help agents ask good questions with as few requests as possible
* make the API, MCP, CLI, and `skill.md` fit together cleanly

## Start here

If you are new to Early Bird, read these pages first:

1. [What Data Is Available](/mintlify/what-data-is-available)
2. [How To Ask Questions](/mintlify/how-to-ask-questions)
3. [Limits](/mintlify/limits)

If you are integrating Early Bird into an agent workflow, keep these two principles in mind:

* Prefer high-level summaries before row-level fetches.
* Prefer small paginated reads before deep or exhaustive scans.

## Stable entrypoints

* Mintlify site: your future `*.mintlify.app` or custom docs domain
* Agent-readable skill: your deployed Early Bird app at `/skill.md`

## Current public surfaces

* `GET /api/dashboard`
* `GET /api/projects?mode=page`
* `GET /api/programs?mode=page`
* `GET /api/organizations?mode=page`
* `GET /api/calendar/events`

## Design philosophy

Early Bird is intentionally conservative:

* no public full-table hydration by default
* no unconstrained query surfaces for agents
* summaries and pagination come first
* schema growth should not break existing consumers