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 infer-profile-dimensionsgit 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/infer-profile-dimensions)<a href="https://agentmods.dev/skills/tashangkd/tashan-cursor-skills/infer-profile-dimensions"><img src="https://agentmods.dev/badge/skills/tashangkd/tashan-cursor-skills/infer-profile-dimensions/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/infer-profile-dimensions"><img src="https://agentmods.dev/badge/skills/tashangkd/tashan-cursor-skills/infer-profile-dimensions.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 | $0.00049 | $0.01191 |
| Opus 5 | $0.00024 | $0.00596 |
| Sonnet 5 | $0.00010 | $0.00238 |
| Haiku 4.5 | $0.00005 | $0.00119 |
Grade A, and why
infer-profile-dimensions 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 9d 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 2a：AI 推断心理维度
前置检查
读取 profiles/[姓名].md，确认 采集阶段 为 basic_info_done。若基础信息不完整，先提示用户补充关键字段（研究阶段、领域、方法范式至少需要填写）。
检查「三、当前需求」章节是否已填写：
- 若尚未填写 → 先采集需求（问 Q-需求1、Q-需求2、Q-需求3，见
collect-basic-info/SKILL.md），再进行推断 - 若已填写 → 直接进入推断环节，将需求内容纳入综合解读的上下文参考
推断说明（告知用户）
AI 将根据你已提供的信息，对以下三个维度进行推断估算：
- 学术动机（AMS-GSR 28 的 7 个维度）
- 认知风格（RCSS 的横向整合 vs 垂直深度）
- 人格特征（Mini-IPIP 大五人格）
推断结果仅供参考，所有推断数据均会标注「（AI推断）」。
如需精确评估，随时可以改用标准量表。
推断逻辑
认知风格（RCSS）
从以下信息推断：
| 基础信息 | 推断依据 |
|---|---|
| 研究方法 = 数据驱动/计算 | 倾向整合型（I较高） |
| 研究方法 = 实验/理论 | 倾向深度型（D较高） |
| 交叉学科方向明确 | 横向整合分+2至+4 |
| 技术栈跨领域多样 | 横向整合分+2至+4 |
| 技术栈单一且深 | 垂直深度分+2至+4 |
| 合作网络跨机构/跨学科 | 横向整合+1至+2 |
给出 CSI 估算值和对应类型，标注置信度。
学术动机（AMS）
从以下信息推断：
| 基础信息 | 推断依据 |
|---|---|
| 研究阶段 = 博士生（前2年） | 无动机分可能偏高（适应期） |
| 有代表性学术产出 | 成就内在动机↑，求知内在动机↑ |
| 主动提到喜欢某个研究问题 | 求知内在动机↑ |
| 能力自评：论文写作低但执行力强 | 体验刺激↑，外部调节可能偏高 |
| 机构为国内顶级/竞争激烈 | 内摄调节可能偏高 |
给出各维度估算分（1-7）和 RAI 综合指数。
人格（Mini-IPIP）
从以下信息推断：
| 基础信息 | 推断依据 |
|---|---|
| 技术栈多样、跨学科 | 开放性/智力↑（4-5） |
| 合作网络广，主动外部合作 | 外向性偏高（3-4） |
| 独立工作为主，较少提及合作 | 外向性偏低（2-3） |
| 能力自评：项目管理高 | 尽责性偏高（4-5） |
| 能力自评：论文写作流畅 | 尽责性偏高 |
| 研究阶段压力大（博士中期） | 神经质可能偏高（3-4） |
输出格式
对每个维度：
- 给出估算分数
- 简要说明推断依据（1-2句）
- 标注置信度（高/中/低）
- 告知哪些维度推断置信度较低，建议用量表补测
示例格式：
**认知风格指数（CSI）**：+9（倾向整合型）
- 推断依据：计算建模方法 + 技术栈跨领域（Python/PyTorch/MATLAB）+ 有跨机构合作
- 置信度：中（建议后续用 RCSS 量表精确测量）
完成后操作
- 将所有推断结果写入
profiles/[姓名].md对应字段，标注（AI推断） - 将
采集阶段更新为inferred_done，数据来源更新为AI推断 - 生成综合解读时，将「三、当前需求」中的内容作为上下文：针对用户的主要时间占用和核心难点，在「适合的发展路径」中给出更具体的近期行动建议（参考
doc/tashan-profile-examples.md的格式） - 告知用户：
推断完成！你可以：
- 输入「查看画像」查看完整结果并进行审核
- 输入「我想填量表」随时对任意维度进行精确测量（将覆盖推断数据）
- 输入「修改」对任何字段进行修正
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.
- 9d ago First seen · 99 lines · 49 tokens per session scan A ced26fe47fa2
infer-profile-dimensions is a skill published in the GitHub repository TashanGKD/tashan-cursor-skills (20 stars, last pushed 5mo ago), licensed MIT. It adds 49 tokens to every session and 1,191 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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