From honey
Provides Honey cost-control directives for dispatched subagents in Superpowers-style workflows. Injects terse output and minimal code rules into implementer/reviewer/fixer agents to reduce multiplied costs.
How this skill is triggered — by the user, by Claude, or both
Slash command
/honey:honey-superpowersThe summary Claude sees in its skill listing — used to decide when to auto-load this skill
Honey is turned on by the session's SessionStart hook — which lives in **your**
Honey is turned on by the session's SessionStart hook — which lives in your (the orchestrator's) context. Superpowers dispatches fresh subagents with isolated context; they never inherit the hook. So every implementer, reviewer, and fixer runs Honey-off: full-fat code (Lever 1 dark) and verbose reports (Lever 2 dark) — multiplied per dispatch. That's the leak. Close it by pasting the directive into the dispatch prompt itself.
The two skills already pull cost the same way Honey does — cheap model per task, file handoffs over pasted text, one-line narration. Don't fight them; stack on top. Honey adds what they don't: less code in the worker, terser reports both ways.
Any time you are about to dispatch a subagent under a Superpowers-style workflow:
subagent-driven-development — implementer / task-reviewer / fixer per taskdispatching-parallel-agents — one agent per independent domainexecuting-plans — parallel-session executionOn Claude Code with the Honey plugin, skip the paste: the plugin's
SubagentStart hook (hooks/honey-subagent.js)
injects the matching directive into every spawned subagent automatically
(reviewer-shaped agent types get the reviewer variant). The blocks below are for
other harnesses, or when the hook isn't installed.
Paste the matching block into the dispatch prompt body — inline text, not a Skill call (invoking burns a round-trip; the subagent only needs the rules).
Worker / implementer / fixer / parallel-domain agent:
Apply Honey: write the minimum code that needs to exist — YAGNI, stdlib/native
before custom; no speculative params, branches, or single-caller abstractions.
Never cut validation, error handling, auth, or anything the task asked for.
Keep code, identifiers, paths, and the brief's exact spec values verbatim.
Report terse: status, commits, one-line test summary, concerns. No narration.
Reviewer:
Report findings tersely: id · severity · file:line · one-line fix. Don't narrate
or restate the diff. Honey governs your prose only — never your verdict or
severity. Flag everything you normally would; raise false positives for the
controller to adjudicate. Do not suppress or downgrade a finding to save words.
Lever 1 (less code) and Lever 2 (less prose) compress what a worker emits. A reviewer emits judgments — compress its prose, never its verdict. This matches Superpowers' hard rule ("never tell a reviewer what not to flag") and Honey's own safety carve-out (keep exact anything asked for; auth/money/migrations/deletes stay explicit). A terser review is fine; a leniter review is a regression.
Never elide, in any variant: input validation at trust boundaries, error handling that prevents data loss, auth/escaping/secrets, accessibility basics, and anything the task or plan explicitly mandated. Spec values (numbers, magic strings, signatures, test cases) stay verbatim — that's Lever 2's "keep exact," and it's also what the brief is the single source of truth for.
The skill prompts Superpowers loads into context are input tokens you've already paid for — Honey can't out-compress them. They're lazy-loaded, so only triggered skills cost anything. The big realized savings are the cheap-model-per-task rule (Superpowers' own — don't skip it) plus Honey inside every dispatched subagent.
npx claudepluginhub green-pt/honey-for-devs --plugin honeyCompresses subagent prompts into ≤200-word briefs before spawning to avoid excessive token costs from cold-start re-tokenization.
Guides subagent dispatch decisions: when to delegate vs work inline, the delegation contract, model/effort selection, parallel fan-out sizing, and verifier agent patterns. Use before any Agent tool call.
Coordinate multi-agent swarms for parallel and pipeline workflows. Use when coordinating multiple agents, running parallel reviews, building pipeline workflows, or implementing divide-and-conquer patterns with subagents.