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-cognitive-analysisgit 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-cognitive-analysis)<a href="https://agentmods.dev/skills/guofu-shiqu/ux-expert-skills/exp-cognitive-analysis"><img src="https://agentmods.dev/badge/skills/guofu-shiqu/ux-expert-skills/exp-cognitive-analysis/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-cognitive-analysis"><img src="https://agentmods.dev/badge/skills/guofu-shiqu/ux-expert-skills/exp-cognitive-analysis.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 | $0.00742 |
| Opus 5 | $0.00020 | $0.00371 |
| Sonnet 5 | $0.00008 | $0.00148 |
| Haiku 4.5 | $0.00004 | $0.00074 |
Grade A, and why
exp-cognitive-analysis 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
用户认知心理学分析
从认知负荷、心智模型、预期管理、控制感、损失厌恶、信任形成、记忆偏差七个维度检查体验设计。
触发条件
- 体验问题涉及用户理解困难
- 用户决策犹豫
- 信任不足
- 记忆偏差
- 情绪升级
- 需要判断用户是否看得懂、找得到、记得住、信得过、感到可控
核心能力
从以下七个维度检查体验设计：
1. 认知负荷（Cognitive Load）
- 信息是否超出用户工作记忆容量
- 是否可以有效拆分复杂信息
- 是否避免不必要的认知消耗
2. 心智模型（Mental Model）
- 用户体验是否符合已有心智模型
- 概念隐喻是否贴近用户认知
- 信息架构是否符合用户预期
3. 预期管理（Expectation Management）
- 是否清晰管理用户预期
- 系统状态是否及时反馈
- 等待时间是否有预期提示
4. 控制感（Sense of Control）
- 用户是否感到可控
- 是否提供撤销、返回、取消等操作
- 用户是否理解当前所在位置和下一步
5. 损失厌恶（Loss Aversion）
- 是否避免因损失厌恶导致的决策阻碍
- 是否合理利用损失厌恶推动正向行为
- 是否清晰呈现收益和损失
6. 信任形成（Trust Formation）
- 信任建立的信号是否充足
- 社会证明、专业背书是否合理运用
- 是否避免过度承诺导致信任破坏
7. 记忆偏差（Memory Bias）
- 体验设计是否考虑峰终定律
- 是否强化正面记忆、弱化负面记忆
- 是否创造可供分享的记忆锚点
输出格式
认知心理检查清单
【认知心理检查清单】
▸ 认知负荷：[高/中/低]，问题：[...]，建议：[...]
▸ 心智模型：[匹配/不匹配]，问题：[...]，建议：[...]
▸ 预期管理：[清晰/不清晰]，问题：[...]，建议：[...]
▸ 控制感：[强/弱]，问题：[...]，建议：[...]
▸ 损失厌恶：[合理/过度]，问题：[...]，建议：[...]
▸ 信任形成：[充足/不足]，问题：[...]，建议：[...]
▸ 记忆偏差：[考虑/未考虑]，问题：[...]，建议：[...]
体验策略建议
基于检查结果，输出针对性的体验优化策略建议。
使用方法
当体验问题涉及认知、心理、信任等层面时，调用本 skill 进行系统性的认知心理检查，找出深层次的设计问题。
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 · 81 lines · 41 tokens per session scan A 456c95e00253
exp-cognitive-analysis is a skill published in the GitHub repository guofu-shiqu/ux-expert-skills (2 stars, last pushed 2mo ago), licensed MIT. It adds 41 tokens to every session and 742 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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