honey-hive

Agent Building

Decide when to delegate to Honey's read-only subagents (hive-scout, hive-reviewer) instead of working inline, so the expensive tokens — large file reads and review passes injected back into the orchestrator's context — come back compressed (Honey Lever 3). Use when a task is search-heavy or review-heavy, spans many files, or you want to keep the orchestrator's context small. Not for trivial one-file work.

QUICK START

How to use this skill

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Prompt to paste

I want to install this Agent Skill for this project in Codex.

Source SKILL.md: https://github.com/Green-PT/honey-for-devs/blob/HEAD/skills/honey-hive/SKILL.md

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First, summarize what it does, its dependencies, license status if identifiable, and any risks. Show the exact files you propose to add under .agents/skills/honey-hive/. Do not write files or run scripts until I approve.

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Copying this prompt does not install or run the skill. Review third-party files before use. Codex skill guide

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 n against 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.