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 TashanGKD/tashan-cursor-skills --skill review-profilegit clone --depth 1 https://github.com/TashanGKD/tashan-cursor-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/tashangkd/tashan-cursor-skills/review-profile)<a href="https://agentmods.dev/skills/tashangkd/tashan-cursor-skills/review-profile"><img src="https://agentmods.dev/badge/skills/tashangkd/tashan-cursor-skills/review-profile/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/tashangkd/tashan-cursor-skills/review-profile"><img src="https://agentmods.dev/badge/skills/tashangkd/tashan-cursor-skills/review-profile.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 | $0.00039 | $0.00854 |
| Opus 5 | $0.00019 | $0.00427 |
| Sonnet 5 | $0.00008 | $0.00171 |
| Haiku 4.5 | $0.00004 | $0.00085 |
Grade A, and why
review-profile 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 8d 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
Phase 4：科研数字分身审核
前置检查
读取 profiles/[姓名].md，了解当前填写情况：
- 哪些字段已有实测数据
- 哪些字段是 AI 推断（标注「AI推断」的）
- 哪些字段尚未填写
展示格式
以结构化、易读的方式展示画像，按以下顺序：
1. 基础身份摘要（一行一项）
2. 能力雷达（文字版，6个维度评分）
3. 当前需求摘要
- 列出主要时间占用事项（1-3条）
- 列出核心难点（1-3条）
- 列出最想改变的一件事
- 若该章节为空，提示用户：「当前需求尚未填写，建议补充以获得更有针对性的发展建议。」
4. 认知风格结论
- 呈现 CSI 数值和类型名称
- 一句话特征描述
- 若为推断，加粗标注 （AI推断，建议后续用量表确认）
5. 动机结构摘要
- 展示 7 个维度分数（用简单条形图文字表示）
- 展示 RAI 综合指数和解读
- 若为推断，加粗标注
6. 人格特征摘要
- 展示 5 个维度分数和水平标签
- 若为推断，加粗标注
7. AI 综合解读（若尚未生成，现在生成）
- 核心驱动模式（2-3句）
- 发展风险提示（2-3条）
- 适合发展路径（1-2个方向）
审核交互流程
展示完毕后，逐维度询问用户：
以上是你的完整科研数字分身。请逐项告诉我：
1. 基础身份信息是否准确？
2. 能力自评是否反映了你的实际情况？
3. 当前需求描述是否符合你现在的真实状态？
4. 认知风格描述（[类型名]）符合你的感受吗？
5. 动机结构描述是否与你的实际体验一致？
6. 人格特征描述是否准确？
7. 综合解读中有没有让你觉得「不对」的地方？
你可以直接说「第3点不对，我认为...」，我会立即更新。
处理用户反馈
| 用户反馈类型 | 处理方式 |
|---|---|
| 「准确」/ 「基本准确」 | 在审核记录中标记该维度为「用户确认」，更新 review_done |
| 「不准确，修改为…」 | 读取 update-profile/SKILL.md 更新对应字段 |
| 「我想重新填某个量表」 | 读取对应量表 Skill，重新施测后覆盖数据 |
| 「某个维度我不确定」 | 记录为「待确认」，提示可后续补充 |
完成审核后操作
- 在
## 八、审核记录中写入本次审核日期、反馈摘要和处理结果 - 将采集阶段更新为
review_done - 更新
最后更新日期 - 告知用户：
科研数字分身审核完成！你的科研数字分身已建立。
后续你可以随时：
- 说「补充/修改[某个字段]」更新内容
- 说「重新填写[量表名]」用新数据更新某个维度
- 说「查看画像」获取最新版本
画像文件保存在：profiles/[姓名].md
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.
- 8d ago First seen · 94 lines · 39 tokens per session scan A b90f32fc8112
review-profile is a skill published in the GitHub repository TashanGKD/tashan-cursor-skills (20 stars, last pushed 5mo ago), licensed MIT. It adds 39 tokens to every session and 854 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 2026-09-03.
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