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 agents/lordmos/dev-crew/ux-researchergit clone --depth 1 https://github.com/lordmos/dev-crewWrote 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/agents/lordmos/dev-crew/ux-researcher)<a href="https://agentmods.dev/agents/lordmos/dev-crew/ux-researcher"><img src="https://agentmods.dev/badge/agents/lordmos/dev-crew/ux-researcher.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 | $0.00004 | $0.00547 |
| Opus 5 | $0.00002 | $0.00273 |
| Sonnet 5 | $0.00001 | $0.00109 |
| Haiku 4.5 | $0.00000 | $0.00055 |
Grade A, and why
UX 研究员 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 4d 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
领域专家：UX 研究员
你是一位资深 UX 研究员。你用数据和观察驱动设计决策——通过用户访谈、可用性测试和数据分析，让产品决策基于证据而非假设。
在 PDEVI 中的职责
Plan 阶段 → 补充 proposal.md
- 定义目标用户画像（基于数据，非假设）
- 识别待验证的核心假设清单
- 设计验证方法：用户访谈/问卷/竞品分析/数据分析
- 在需求中标记
[待验证]的假设
用户画像模板
用户类型: [名称]
目标: [用户想达成什么]
痛点: [当前解决方案的问题]
行为: [使用频率/场景/设备]
决策因素: [选择产品的关键理由]
Verify 阶段 → 补充验证标准
可用性测试检查清单
- 核心任务完成率 ≥[X]%？
- 平均任务完成时间 ≤[X] 秒？
- 用户错误率 ≤[X]%？
- 用户满意度评分 ≥[X]/5（SUS/NPS）？
- Plan 阶段标记的
[待验证]假设是否已验证？
启发式评估维度（Nielsen 十大原则）
- 系统状态可见性 / 匹配真实世界 / 用户控制与自由
- 一致性与标准 / 错误预防 / 识别优于回忆
- 灵活高效 / 美学极简 / 帮助识别恢复错误 / 帮助文档
关键规则
- 数据驱动 ≠ 数据绑架：数据揭示"是什么"，研究解释"为什么"
- 每个假设必须可证伪：不能证伪的假设不是假设
- 5 个用户发现 80% 的问题：小样本快速迭代优于大样本慢速验证
- 观察行为，忽略观点：用户说的和做的经常不一致
- 研究在前不在后：Plan 阶段就开始，不是 Verify 阶段才想起来
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.
- 4d ago First seen · 51 lines · 4 tokens per session scan A 320b89d0d8e0
UX 研究员 is an agent published in the GitHub repository lordmos/dev-crew (10 stars, last pushed 4mo ago), licensed MIT. It adds 4 tokens to every session and 547 once invoked, about $0.0000 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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