green-pt/honey-for-devs/honey-gain

Claude Code and agent skill by green-pt/honey-for-devs

Trust tier 2
  • community
LLM review pending
Source check pending

Checking that the SKILL.md file is still in the repository.

Show Honey's benchmark scoreboard — the committed quality and token results per task tier (code, user-facing, agent-to-agent) from bench/. Reports only the reproducible committed figures, never invents per-repo numbers. Use when asked how much Honey saves, how it compares to Caveman / Ponytail / no-skill baseline, or for the headline numbers.

Install

npx vskill@latest install green-pt/honey-for-devs/honey-gain

SKILL.md

Honey Gain

Report the committed benchmark results — never a guessed or per-session number, and never an embedded copy that can drift from the bench.

Do

  1. Recompute from the committed records at use time — don't recite from memory, and

prefer the raw records over any rendered table (renderings go stale, the records don't):

``bash cd bench && node src/report.js --stamp full-opus48 --by-type ``

Offline, no API spend. Swap --stamp full-gpt55 for the cross-provider figure, drop --by-type for the whole suite. Hive handoff numbers → `bench/hive/RESULTS.md`.

  1. Report the tier table terse: Δ LOC and Δ output, each with its `p`, judge as

win/loss/tie, and the test pass-rate, per variant. The tier split is the finding — deepest on code and handoffs, output a statistical tie on user-facing (the polish carve-out). Lead with Δ LOC: it measures Lever 1 directly, while output tokens mix code with the prose around it, and the two come apart (Ponytail cuts lines but narrates at length).

Rules

  • Never quote a delta without its p-value, and call (ns) results ties, not wins.

Every figure is a paired per-task median; a ratio of arm totals is not quotable.

are secondary. If one disagrees with a fresh --stamp recompute, the recompute wins — say the rendering is out of sync.

  • Quality is a tie, not a gain — that's the honest claim. Don't upgrade it.
  • Cost/CO₂ savings are a modelled counterfactual, not measured; those belong to

honey-eco, which labels them. Don't state a dollar saving here.

  • Asked for numbers on this repo? The bench measures the skill on a fixed task suite,

not the user's codebase — offer cd bench && npm run bench, don't extrapolate.

  • One honest caveat, once: 23 author-written tasks, judge noise — the objective test-pass

column is the trustworthy correctness signal.

  • Never resurrect the old unreproducible 92%/78%/73% / −57%/−65%/−70% numbers, or the

superseded arm-total figures (−49% code, −15% aggregate) — see `bench/METHODOLOGY.md`.

Security

  • Security scanPassed, 93 of 100Pattern checks on the skill's files.
  • Model reviewNot runA model review is scheduled for the next rescan.

Quality evaluation

  • Task evaluationNot runNo evaluation yet. Run one in Skill Studio.

Source

Popularity

Repository stars
303
Repository forks
17
7-day trend score
29

Stars and forks are for the whole GitHub repository, not this skill alone. Not refreshed yet.

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