Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/Green-PT/honey-for-devsnpx agentmods add skills/green-pt/honey-for-devs/honey-gainWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/green-pt/honey-for-devs/honey-gain)<a href="https://agentmods.dev/skills/green-pt/honey-for-devs/honey-gain"><img src="https://agentmods.dev/badge/skills/green-pt/honey-for-devs/honey-gain/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/green-pt/honey-for-devs/honey-gain"><img src="https://agentmods.dev/badge/skills/green-pt/honey-for-devs/honey-gain.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00014 | $0.00641 |
| Opus 5 | $0.00007 | $0.00320 |
| Sonnet 5 | $0.00003 | $0.00128 |
| Haiku 4.5 | $0.00001 | $0.00064 |
Grade A, and why
honey-gain scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 11d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 50 lines — stays where its author put it; the contents beside it link to each section on GitHub.
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
-
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):
cd bench && node src/report.js --stamp full-opus48 --by-typeOffline, no API spend. Swap
--stamp full-gpt55for the cross-provider figure, drop--by-typefor the whole suite. Hive handoff numbers →bench/hive/RESULTS.md. -
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. - Prose renderings (
bench/README.md,results/combined.md) are secondary. If one disagrees with a fresh--stamprecompute, 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) — seebench/METHODOLOGY.md.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 11d ago First seen · 50 lines · 14 tokens per session scan A a5af0d140fb3
honey-gain is a skill published in the GitHub repository Green-PT/honey-for-devs (294 stars, last pushed 4d ago), licensed MIT. It adds 14 tokens to every session and 641 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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