Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add instructions/mathruffian-dot/gem-to-skill-kit/agents-mdgit clone --depth 1 https://github.com/mathruffian-dot/gem-to-skill-kitWrote 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/instructions/mathruffian-dot/gem-to-skill-kit/agents-md)<a href="https://agentmods.dev/instructions/mathruffian-dot/gem-to-skill-kit/agents-md"><img src="https://agentmods.dev/badge/instructions/mathruffian-dot/gem-to-skill-kit/agents-md.svg" alt="Measured on agentmods" height="20"></a>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 | $0.00626 | $0.00626 |
| Opus 5 | $0.00313 | $0.00313 |
| Sonnet 5 | $0.00125 | $0.00125 |
| Haiku 4.5 | $0.00063 | $0.00063 |
Grade A, and why
gem-to-skill-kit AGENTS.md 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 5d 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.
What it actually says
Gem to Skill Kit｜Agent 通用入口
任務
引導使用者把 Google Gemini Gem 升級成可攜、可執行、可驗證的 Agent Skill。
必讀
.agents/skills/gem-to-skill/SKILL.md.agents/skills/gem-to-skill/references/upgrade-options.md.agents/skills/gem-to-skill/references/output-spec.md
五階段
- Drive：檢查 Google Drive for desktop；未完成安裝與登入就停止。
- Locate：執行
find_gem_folder.py；找不到時請使用者手動選取完整路徑。 - Inventory：先取得讀取同意，再唯讀執行
inventory_gems.py，列出每個 Gem 原本用途。 - Upgrade：只有使用者挑選的 Gem 才分析；提出 2–4 個 Agent 能力加值選項並等待選擇。
- Save：將選定設計寫成 spec，執行
build_skill.py產生 Skill，再用validate_skill.py驗證。
固定安全規則
- 使用繁體中文；Windows 指令使用 PowerShell。
- 原始 Gem 資料夾唯讀，不建立、修改、重新命名或刪除其中任何檔案。
- 不把 Gem 內容、知識檔、Drive ID、盤點 JSON 或產生的私人 Skill 推送到本 repo。
- 掃描前先顯示目標資料夾並取得同意。
- 找不到資料夾時，不做全磁碟深度掃描；引導使用者在檔案總管／Finder 手動選取。
- 列出用途時只摘要，不逐字公開完整 Gem 指令。
- 升級前先讓使用者選 Gem；不得自動升級全部。
- 每個選定 Gem 都要顯示「原用途、保留規則、建議加值、輸入、輸出、風險」。
- Skill 名稱使用小寫英數與連字號，長度不超過 64。
- 產物儲存在原始 Gem 資料夾外；預設為專案內
.agents/skills/<name>/。 - 安裝到全域技能目錄、覆蓋同名 Skill 或推送 Git 前，必須再次確認。
完成定義
- Drive 已安裝並登入。
- Gem 路徑由工具找到或使用者明確提供。
- 所有可解析 Gem 的用途清單已交付。
- 使用者已明確挑選要升級的 Gem 與加值能力。
- 產生的 Skill 通過驗證，且回報實際儲存位置。
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.
- 5d ago First seen · 42 lines · 626 tokens per session scan A b7df9ddf2321
gem-to-skill-kit AGENTS.md is an instructions file published in the GitHub repository mathruffian-dot/gem-to-skill-kit (5 stars, last pushed yesterday), licensed MIT. It adds 626 tokens to every session, about $0.0031 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 2026-08-31.
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