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 skills add Stanshy/AgentHub --skill pre-deploygit clone --depth 1 https://github.com/Stanshy/AgentHubWrote 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/stanshy/agenthub/pre-deploy)<a href="https://agentmods.dev/skills/stanshy/agenthub/pre-deploy"><img src="https://agentmods.dev/badge/skills/stanshy/agenthub/pre-deploy/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/stanshy/agenthub/pre-deploy"><img src="https://agentmods.dev/badge/skills/stanshy/agenthub/pre-deploy.svg" alt="Reviewed on agentmods" width="80" 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 5.1 | $0.00012 | $0.00627 |
| Opus 5.5 | $0.00005 | $0.00251 |
| Sonnet 5.5 | $0.00002 | $0.00125 |
| Haiku 4.5 | $0.00001 | $0.00063 |
Grade A, and why
pre-deploy 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 1mo 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
預部署檢查
L1 提交 G5（部署就緒）前執行，產生預部署檢查報告。
使用方式
/pre-deploy [environment]
參數
$0: 目標環境（staging / production，預設 staging）$ARGUMENTS: 完整參數
自動檢查項
1. CI 狀態
- lint 通過（執行
npm run lint或等效指令） - type-check 通過（執行
npm run typecheck或等效指令） - 單元測試通過（執行
npm run test或等效指令） - build 成功（執行
npm run build或等效指令）
2. 環境變數
-
.env.example存在且有內容 - 所有程式碼中引用的環境變數都在
.env.example中列出 - production 環境設定已準備（CI workflow / docker-compose）
3. 資料庫
- 所有 migration 已生成（無 pending changes）
- seed 腳本可執行（如有）
4. Docker（如適用）
- Dockerfile 存在且語法正確
- docker-compose config 無語法錯誤
- .dockerignore 排除測試檔案
5. 安全
- 無硬編碼密碼或 API Key（grep 檢查）
- .env 不在 git 追蹤中
手動確認項（列出供 L1 確認）
- 回滾計畫已準備
- 監控/告警已設定
- 相關方已通知上線時間
輸出格式
# 預部署檢查報告
**環境**: {environment}
**日期**: {today}
**結果**: PASS / FAIL
## 自動檢查
| # | 項目 | 結果 | 備註 |
|---|------|------|------|
| 1 | lint | ✅/❌ | {detail} |
...
## 手動確認（待 L1 勾選）
- [ ] 回滾計畫
- [ ] 監控告警
- [ ] 通知相關方
## 結論
{PASS: 可提交 G5 / FAIL: 需修正以上 ❌ 項目}
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.
- 1mo ago First seen · 75 lines · 12 tokens per session scan A 0d6d3d66632d
pre-deploy is a skill published in the GitHub repository Stanshy/AgentHub (204 stars, last pushed 6mo ago), licensed MIT. It adds 12 tokens to every session and 627 once invoked, about $0.0000 per session on Opus 5.5. 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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