mega-research

Research synthesis and knowledge base for the F3L1X ecosystem

Updated: March 29, 2026

mega-research

Research synthesis and knowledge base

Mega-Research is the ecosystem's institutional memory for analysis, theory, and cross-referenced research. It stores numbered research documents that agents can query when they need background context.

What It Does

Mega-Research provides:

  1. Research Archive - Numbered documents covering analysis, theory, and findings
  2. Cross-Reference - Documents link to relevant realms, code, and other research
  3. Knowledge Synthesis - Combines findings from multiple sources into actionable knowledge
  4. Research Protocol - Three-layer research protocol (doc-u-me -> mega-research -> code)

How It Works

When an agent needs to research a topic:

  1. Layer 1: Doc-u-Me (fastest) - Search indexed documentation
  2. Layer 2: Mega-Research (fast) - Read prior analysis and theory
  3. Layer 3: Code Examination (medium) - Read actual implementation

Each layer catches what the previous missed:
- Doc-u-Me knows what is documented
- Mega-Research knows what is theorized
- Code examination knows what is real

  • Doc-u-Me - Layer 1 search (documentation)
  • Explore-Kid - Token-efficient code reading
  • All research agents - Query mega-research for background context

Further Reading

Want to query this documentation programmatically? The F3L1X MCP server gives any AI agent search_docs, get_doc_page, and get_realm_doc tool access to the full docs library — available on the Elevated plan.