Skip to main content

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 startup projects, programs, organizations, and application windows.

​
Send Your Agent to Early Bird

Copy and send this to your agent: 
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
  2. How To Ask Questions
  3. 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