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 guofu-shiqu/ux-expert-skills --skill exp-jtbd-extractiongit clone --depth 1 https://github.com/guofu-shiqu/ux-expert-skillsWrote 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/guofu-shiqu/ux-expert-skills/exp-jtbd-extraction)<a href="https://agentmods.dev/skills/guofu-shiqu/ux-expert-skills/exp-jtbd-extraction"><img src="https://agentmods.dev/badge/skills/guofu-shiqu/ux-expert-skills/exp-jtbd-extraction/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/guofu-shiqu/ux-expert-skills/exp-jtbd-extraction"><img src="https://agentmods.dev/badge/skills/guofu-shiqu/ux-expert-skills/exp-jtbd-extraction.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 | $0.00045 | $0.00489 |
| Opus 5 | $0.00023 | $0.00244 |
| Sonnet 5 | $0.00009 | $0.00098 |
| Haiku 4.5 | $0.00005 | $0.00049 |
Grade A, and why
exp-jtbd-extraction 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
JTBD 用户任务提炼
从用户行为、表达和选择中提炼功能任务、情绪任务和社会任务，识别用户真正想完成的进步是什么。
触发条件
- 需要理解用户表面行为背后的真实动机
- 用户行为与预期不一致
- 需要发现用户真正想完成的进步
- 需要识别用户当前的替代方案和阻力
核心能力
从以下维度提炼 JTBD：
- 情境描述 — 用户在什么具体情境下产生了这个需求
- 功能任务（Functional Job） — 用户想要完成的具体功能性目标："帮我..."
- 情绪任务（Emotional Job） — 用户想要感受到的情绪状态："让我感到..."
- 社会任务（Social Job） — 用户想要在他人眼中呈现的形象："让我看起来..."
- 当前替代方案 — 用户目前用什么方式来完成这个任务
- 当前阻力 — 是什么阻碍了用户更好地完成这个任务
- 体验机会 — 基于 JTBD 可以创造的体验价值
输出格式：JTBD 卡片
【JTBD 卡片】
▸ 情境描述：
[用户在什么具体情境下产生了这个需求]
▸ 三层任务拆解：
功能任务：[帮我...]
情绪任务：[让我感到...]
社会任务：[让我看起来...]
▸ 当前替代方案：
[用户目前用什么方式来完成这个任务]
▸ 当前阻力：
[是什么阻碍了用户更好地完成这个任务]
▸ 体验机会：
[基于 JTBD 可以创造的体验价值]
使用方法
当用户行为或需求不明确时，调用本 skill 提炼 JTBD，理解用户真正的需求和动机，为后续的设计和策略提供方向。
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 · 55 lines · 45 tokens per session scan A 3afd4754a8d9
exp-jtbd-extraction is a skill published in the GitHub repository guofu-shiqu/ux-expert-skills (2 stars, last pushed 2mo ago), licensed MIT. It adds 45 tokens to every session and 489 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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