Honey Hive
Delegate the token-heavy reading; keep the thinking. A subagent's return is injected back into your context — Honey's hive returns it as a compressed Lever-3 handoff, so the most expensive tokens in an agentic session shrink ~25–55% with no loss the orchestrator can use.
When to delegate (any one holds)
- Search-heavy — "where is X / who calls Y / find all Z" across many files →
hive-scout. - Review-heavy — review a diff or file set for bugs and bloat →
hive-reviewer. - Context-preserving — the read would dump many files into your context but you need only the conclusions.
- Parallel — independent locate/review jobs that can run at once.
When NOT to (work inline)
- One known file, a trivial edit, or content you already have in context.
- Dispatch + return overhead would exceed just reading it yourself (a file or two).
- You need the full file body, not a map.
The crew is read-only by design — they locate and review; you decide and edit.
The crew
| Agent | Does | Returns |
|---|---|---|
hive-scout | locate symbols / callers / configs / patterns | compact id-keyed JSON map |
hive-reviewer | review diff/files for bugs + over-engineering + verbosity | columnar id-keyed JSON findings |
Reading a hive return (Lever 3, in reverse)
Every return is compact/columnar JSON, records addressed by a stable id, with an n count. Read it as data:
- Address by
id, never "the 3rd finding" — ordinal lookup misparses, frontier models included. - Aggregate in code — to count or filter, do it programmatically; don't eyeball rows.
- Check
nagainst the rows you received — a dense misparse is silent. - Safety carve-out — auth / money / migration / delete findings come back explicit, not slugged. Treat them verbatim.
ESON is opt-in: ask for it only on a high-volume, cached review pipe you own end-to-end.
