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 AgiWish/hermes-skills-zh --skill tech-decision-zhgit clone --depth 1 https://github.com/AgiWish/hermes-skills-zhWrote 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/agiwish/hermes-skills-zh/tech-decision-zh)<a href="https://agentmods.dev/skills/agiwish/hermes-skills-zh/tech-decision-zh"><img src="https://agentmods.dev/badge/skills/agiwish/hermes-skills-zh/tech-decision-zh/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/agiwish/hermes-skills-zh/tech-decision-zh"><img src="https://agentmods.dev/badge/skills/agiwish/hermes-skills-zh/tech-decision-zh.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 | $0.00041 | $0.00761 |
| Opus 5 | $0.00020 | $0.00380 |
| Sonnet 5 | $0.00008 | $0.00152 |
| Haiku 4.5 | $0.00004 | $0.00076 |
Grade A, and why
tech-decision-zh 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.
What it actually says
技术决策记录 (tech-decision-zh)
When to Use
- "帮我写一份技术选型文档"、"这个决策需要留个记录"
- 选了某个技术方案，需要说清楚为什么
- 回顾历史决策，说明当时的背景和权衡
/tech-decision-zh [决策背景 + 方案描述]
Quick Reference
/tech-decision-zh [技术决策描述]
可选参数：
--status=提案 # 正在讨论中的方案
--status=已采纳 # 已落地执行的决策（默认）
--status=已废弃 # 被替代的历史决策
Procedure
-
收集决策信息（如不完整，追问）
- 要解决什么问题？
- 考虑过哪些备选方案？
- 最终选了什么，为什么？
- 已知的代价和风险是什么？
-
输出 ADR 文档
# ADR-[编号]: [决策标题]
**日期**：[YYYY-MM-DD]
**状态**：[提案 / 已采纳 / 已废弃]
**决策人**：[人名 / 团队]
## 背景
[用 2-3 句话描述当时面临的问题和约束条件。
不要写解法，只写为什么需要做决策。]
## 决策
我们决定：**[一句话说清楚选了什么]**
## 备选方案对比
| 方案 | 优点 | 缺点 | 排除原因 |
|------|------|------|----------|
| [方案A（已选）] | [优点] | [代价] | 已采纳 |
| [方案B] | [优点] | [缺点] | [为什么没选] |
| [方案C] | [优点] | [缺点] | [为什么没选] |
## 影响与代价
**正面影响**：
- [好处1]
- [好处2]
**已知代价**：
- [代价1，以及如何缓解]
- [代价2]
**遗留风险**：
- [风险1：触发条件 + 应对预案]
## 回顾触发条件
以下情况出现时，应重新评估这个决策：
- [条件1]
- [条件2]
Pitfalls
- 背景部分不要写解法，只写问题和约束
- 代价要如实记录，不能只写优点
- 备选方案要认真列出，不能全是稻草人选项
Verification
- 背景部分清楚说明了为什么要做这个决策
- 至少列出 2 个以上备选方案
- 代价和风险诚实记录
- 有回顾触发条件，方便未来重新评估
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 · 99 lines · 41 tokens per session scan A 2ae931e47b8d
tech-decision-zh is a skill published in the GitHub repository AgiWish/hermes-skills-zh (5 stars, last pushed 3mo ago), licensed MIT. It adds 41 tokens to every session and 761 once invoked, about $0.0002 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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