Wiki Aggregate — N raw sources → 1 structured pack

A protocol for agentic aggregation of long-horizon research material. Inverts the standard "concat all → ask LLM to summarize" pipeline: instead, an aggregator agent navigates the N source files with three tools, building a notes scratchpad with full path:line provenance, and finally writes a structured pack (brief / findings / sources / aggregation log).

Core principle: don't read everything upfront. Don't merge final answers. Treat the N sources as a queryable environment.

Why this exists

Three traditional ways to aggregate N parallel research outputs all fail on long-horizon, open-ended tasks:

  ❌ concat all sources into one prompt
       → 200K+ token explosion, attention collapse on long context

  ❌ summarize each, then merge summaries
       → ~90% of intermediate evidence (the "I noticed X but..." asides) is lost

  ❌ LLM-as-judge picks the single best source
       → discards the other N-1 sources' independent findings