Agent Builder
shareAI-lab/learn-claude-code
Design and build AI agents for any domain. An agent skill from shareAI-lab/learn-claude-code.
Show Honey's benchmark scoreboard — the committed quality and token results per task tier (code, user-facing, agent-to-agent) from bench/.
Install Honey Gain
$ npx skills add Green-PT/honey-for-devs --skill honey-gain -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install Green-PT/honey-for-devs honey-gain --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/Green-PT/honey-for-devs.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/honey-gain .claude/skills/honey-gain && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "honey-gain" agent skill from https://github.com/Green-PT/honey-for-devs/tree/main/skills/honey-gain into .claude/skills/honey-gain/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "honey-gain", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/Green-PT/honey-for-devs/tree/main/skills/honey-gainType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add Green-PT/honey-for-devs --skill honey-gain -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install Green-PT/honey-for-devs honey-gain --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/Green-PT/honey-for-devs.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/honey-gain .agents/skills/honey-gain && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "honey-gain" agent skill from https://github.com/Green-PT/honey-for-devs/tree/main/skills/honey-gain into .agents/skills/honey-gain/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "honey-gain", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add Green-PT/honey-for-devs --skill honey-gain -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install Green-PT/honey-for-devs honey-gain --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/Green-PT/honey-for-devs.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/honey-gain .cursor/skills/honey-gain && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "honey-gain" agent skill from https://github.com/Green-PT/honey-for-devs/tree/main/skills/honey-gain into .cursor/skills/honey-gain/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "honey-gain", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/Green-PT/honey-for-devs.git --path skills/honey-gain--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add Green-PT/honey-for-devs --skill honey-gain -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install Green-PT/honey-for-devs honey-gain --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/Green-PT/honey-for-devs.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/honey-gain .gemini/skills/honey-gain && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "honey-gain" agent skill from https://github.com/Green-PT/honey-for-devs/tree/main/skills/honey-gain into .gemini/skills/honey-gain/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "honey-gain", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install Green-PT/honey-for-devs honey-gainInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add Green-PT/honey-for-devs --skill honey-gain -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/Green-PT/honey-for-devs.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/honey-gain .github/skills/honey-gain && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "honey-gain" agent skill from https://github.com/Green-PT/honey-for-devs/tree/main/skills/honey-gain into .github/skills/honey-gain/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "honey-gain", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add Green-PT/honey-for-devs --skill honey-gain -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install Green-PT/honey-for-devs honey-gain --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/Green-PT/honey-for-devs.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/honey-gain .opencode/skills/honey-gain && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "honey-gain" agent skill from https://github.com/Green-PT/honey-for-devs/tree/main/skills/honey-gain into .opencode/skills/honey-gain/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "honey-gain", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
Facts
- Skill name
honey-gain- GitHub stars
- 313
- Token cost
- ~661 tokens
- SKILL.md length
- 303 words
- Files
- 1
- Skills in repo
- 14
- Repo updated
- First seen
- Licence
- MIT
At a glance
Show Honey's benchmark scoreboard — the committed quality and token results per task tier (code, user-facing, agent-to-agent) from bench/.
- Works in 2 steps: Recompute from the committed records at… → Report the tier table terse: Δ LOC and Δ…
- Asked how much Honey saves
- SKILL.md covers Do and Rules
- Calls node and npm
What it does
Honey Gain is an agent skill from Green-PT/honey-for-devs. 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.
Its SKILL.md is about 660 tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.
It sits in AI & LLM Engineering. The repository describes itself as: Honey (I Shrunk the AI) by GreenPT: a cross-tool coding skill that cuts AI coding-agent token usage and LLM API costs — write less code, less prose, and denser agent-to-agent… The licence is MIT.
When your agent uses it
- Asked how much Honey saves
- How it compares to Caveman / Ponytail / no-skill baseline
- For the headline numbers
Example prompts
- “/honey-gain”
Workflow steps
2 steps, taken from the first numbered list in SKILL.md.
- Recompute from the committed records at use time — don't recite from memory, and
- Report the tier table terse: Δ LOC and Δ output, each with its p, judge as
What it can do on your machine
Read from SKILL.md and the folder at commit 9169fc5. It shows what the files ask for, not the result of running them.
Tool permissions
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Runs code
Shell commands in SKILL.md call:
nodenpm
From the folder's file list and the shell code blocks in SKILL.md.
Network
No URLs in SKILL.md. Its commands use npm, which can reach the network depending on how they are called.
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Context cost
Honey Gain loads about 661 tokens when it runs. Until then it costs about 89 tokens; SKILL.md has 303 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
Safety
Auto-check passed
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.
SKILL.md
The full file from Green-PT/honey-for-devs at commit 9169fc5, republished under its MIT licence (© Green-PT). 303 words, ~661 tokens.
Download SKILL.mdSave it as
.claude/skills/honey-gain/SKILL.md (or your agent's skills folder).- name
- honey-gain
- description
- 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.
- license
- MIT
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):
bash 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.
© Green-PT, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Files
Just SKILL.md in skills/honey-gain of Green-PT/honey-for-devs.
Open the folder on GitHubat commit 9169fc5
Compare with similar skills
Honey Gain next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Honey Gain this skillGreen-PT/honey-for-devs | 313 | — | ~661 | Automated safety check: Pass | MIT | |
| Agent BuildershareAI-lab/learn-claude-code | 78k | 4 repos | ~1.2k | Automated safety check: Pass | MIT | |
| Add Uint Supportpytorch/pytorch | 104k | 2 repos | ~2.3k | Automated safety check: Pass | Custom licence | |
| LLM Benchmarking with lm-evaluation-harnessOrchestra-Research/AI-Research-SKILLs | 13k | 8 repos | ~3k | Automated safety check: Pass | MIT | |
| Segment Anything Model GuideOrchestra-Research/AI-Research-SKILLs | 13k | 8 repos | ~3.3k | Automated safety check: Pass | MIT | |
| 1passwordtrpc-group/trpc-agent-go | 1.9k | 14 repos | ~656 | Automated safety check: Pass | Apache-2.0 |
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Runs lm-evaluation-harness to benchmark language models on academic suites such as MMLU, GSM8K and HumanEval, compare models and track training checkpoints.
Segment Anything Model Guide
Orchestra-Research/AI-Research-SKILLs
Guide to using Meta's Segment Anything Model for zero-shot image segmentation with point, box or mask prompts, or automatic mask generation.
1password
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Set up and use 1Password CLI (op). An agent skill from trpc-group/trpc-agent-go.
Planning With Files
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Transforms workflow to use Manus-style persistent markdown files for planning, progress tracking, and knowledge storage.
More from Green-PT/honey-for-devs
All 14 skills in this repoHoney
Green-PT/honey-for-devs
Write less code and say less about it. An agent skill from Green-PT/honey-for-devs.
Honey Ccr
Green-PT/honey-for-devs
Compress-Cache-Retrieve for huge, repetitive array tool output (logs, scan results, time series, event streams) before it enters context.
Honey Eco
Green-PT/honey-for-devs
Report this session's output tokens and CO₂ by running the repo's committed EcoLogits port, plus the modelled CO₂/$ saved vs a no-Honey baseline — always labelled with the bench stamp it came from.
Honey Px
Green-PT/honey-for-devs
Read huge, dense, read-only text as rendered PNG pages instead of raw text — image tokens scale with pixels, not characters, so token-dense bulk (big files, vendored code, diffs, logs) costs ~60–75%…
Honey Superpowers
Green-PT/honey-for-devs
Stack Honey onto Superpowers-style workflows (subagent-driven-development, dispatching-parallel-agents, executing-plans) and any orchestration that dispatches fresh subagents.
Honey Debt
Green-PT/honey-for-devs
Harvest every honey: comment in the codebase into a debt ledger, so the deliberate shortcuts Lever 1 leaves behind get tracked instead of rotting into "later means never".
Related
Categories
Questions about Honey Gain
What does Honey Gain do?
Show Honey's benchmark scoreboard — the committed quality and token results per task tier (code, user-facing, agent-to-agent) from bench/. Honey Gain is an agent skill from Green-PT/honey-for-devs. Show Honey's benchmark scoreboard — the committed quality and token results per task tier (code, user-facing, agent-to-agent) from bench/.
When should I use Honey Gain?
Honey Gain fits situations like: asked how much Honey saves; how it compares to Caveman / Ponytail / no-skill baseline; for the headline numbers.
How do I install Honey Gain in Claude Code?
Run `npx skills add Green-PT/honey-for-devs --skill honey-gain -a claude-code`. Or copy the skill folder (skills/honey-gain in Green-PT/honey-for-devs) into .claude/skills/honey-gain in your project. Claude Code loads it when a task matches its description.
How do I install Honey Gain in Codex?
Run `npx skills add Green-PT/honey-for-devs --skill honey-gain -a codex`. Or copy the skill folder (skills/honey-gain in Green-PT/honey-for-devs) into .agents/skills/honey-gain in your project. Codex loads it when a task matches its description.
Can I use Honey Gain in Cursor, Gemini CLI or GitHub Copilot?
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add Green-PT/honey-for-devs --skill honey-gain -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/honey-gain, .gemini/skills/honey-gain, .github/skills/honey-gain and .opencode/skills/honey-gain in your project.
What does Honey Gain need to run?
Going by SKILL.md and its folder, Honey Gain needs the command-line tools its instructions call (node and npm).
Does Honey Gain access the network?
SKILL.md contains no URLs. Its commands use npm, which can reach the network depending on how they are called. This is read from the text; nothing was executed.
Is Honey Gain safe to install?
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.
What licence does Honey Gain use?
Honey Gain is published under the MIT licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.
How many tokens does Honey Gain use?
About 661 tokens (SKILL.md is roughly 2.6k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
What are the alternatives to Honey Gain?
Skills that share tags, products or a category with Honey Gain: Agent Builder (shareAI-lab/learn-claude-code, 78k stars), Add Uint Support (pytorch/pytorch, 104k stars), LLM Benchmarking with lm-evaluation-harness (Orchestra-Research/AI-Research-SKILLs, 13k stars) and Segment Anything Model Guide (Orchestra-Research/AI-Research-SKILLs, 13k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Honey Gain?
Green-PT (a GitHub organization) maintains it in Green-PT/honey-for-devs, which has 313 GitHub stars. The repository holds 14 skills in this directory. The repository was last updated on September 7, 2026.
Source: Green-PT/honey-for-devs on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.