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 user-research-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/user-research-zh)<a href="https://agentmods.dev/skills/agiwish/hermes-skills-zh/user-research-zh"><img src="https://agentmods.dev/badge/skills/agiwish/hermes-skills-zh/user-research-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/user-research-zh"><img src="https://agentmods.dev/badge/skills/agiwish/hermes-skills-zh/user-research-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 | $0.00047 | $0.00805 |
| Opus 5 | $0.00023 | $0.00402 |
| Sonnet 5 | $0.00009 | $0.00161 |
| Haiku 4.5 | $0.00005 | $0.00081 |
Grade A, and why
user-research-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 12d 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
用户调研整理 (user-research-zh)
When to Use
- "帮我整理一下用户访谈"、"把这些反馈归类一下"
- 有大量原始用户反馈需要提炼
- 问卷结果需要转化为产品洞察
/user-research-zh [访谈记录 / 反馈内容]
Quick Reference
/user-research-zh [原始访谈记录或用户反馈]
可选参数：
--type=访谈 # 深度访谈记录整理（默认）
--type=问卷 # 问卷开放题归类
--type=反馈 # 产品反馈/投诉归类
--output=洞察 # 输出洞察报告
--output=痛点 # 只输出痛点优先级列表
Procedure
-
理解原始材料
- 调研目的是什么？
- 样本数量和用户类型？
- 是定性（访谈）还是定量（问卷）？
-
输出调研洞察报告
## 一、调研概况
- 调研目的：
- 样本：[N人，用户类型描述]
- 方式：[深度访谈 / 问卷 / 用户反馈]
- 时间：
## 二、核心发现（Top Insights）
1. **[洞察1标题]**
- 现象：[引用原始表述]
- 频次：[N/总数 提及]
- 背后原因：[推断或用户原话]
2. **[洞察2标题]**
...
## 三、痛点优先级矩阵
| 痛点 | 提及频次 | 影响程度 | 现有解法 | 优先级 |
|------|----------|----------|----------|--------|
| [痛点1] | 高 | 高 | 无 | 🔴 P0 |
| [痛点2] | 中 | 高 | 有但差 | 🟡 P1 |
## 四、用户分层
- **核心用户**：[特征描述，占比]
- **潜在用户**：[特征描述]
- **非目标用户**：[特征，为什么不是]
## 五、产品机会点
1. [机会点1]：[对应痛点] → [可能的产品方向]
2. [机会点2]：...
## 六、待验证假设
- [ ] [需要下一轮验证的假设]
- 原始引用标注
- 关键洞察要附上原始用户表述，增加可信度
Pitfalls
- 不要过度解读，用户说什么就是什么，推断要标注清楚
- 痛点频次要基于实际数据，不要说"很多用户"而不给数字
- 不要因为某个洞察"符合预期"就过度强调它
Verification
- 每个洞察有原始引用支撑
- 痛点有频次数据
- 区分了事实观察和主观推断
- 机会点来自洞察，不是凭空生成
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.
- 12d ago First seen · 94 lines · 47 tokens per session scan A 04f7eda11737
user-research-zh is a skill published in the GitHub repository AgiWish/hermes-skills-zh (5 stars, last pushed 3mo ago), licensed MIT. It adds 47 tokens to every session and 805 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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