Borrowing it
Nothing to install: this file belongs to ZimoLiao/scholaraio. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/ZimoLiao/scholaraio/main/.claude/skills/insights/SKILL.mdgit clone --depth 1 https://github.com/ZimoLiao/scholaraioWrote 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/zimoliao/scholaraio/insights)<a href="https://agentmods.dev/skills/zimoliao/scholaraio/insights"><img src="https://agentmods.dev/badge/skills/zimoliao/scholaraio/insights/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/zimoliao/scholaraio/insights"><img src="https://agentmods.dev/badge/skills/zimoliao/scholaraio/insights.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00033 | $0.00336 |
| Opus 5 | $0.00016 | $0.00168 |
| Sonnet 5 | $0.00007 | $0.00067 |
| Haiku 4.5 | $0.00003 | $0.00034 |
Grade A, and why
insights 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 11d 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
Research Observatory
分析用户的研究行为数据，发现阅读规律和遗漏的相关论文。
执行逻辑
scholaraio insights [--days N] # 默认分析过去30天
输出内容
- 搜索热词 Top 10 — 最常出现在搜索查询中的词
- 最常阅读论文 Top 10 — 按
show命令调用次数统计 - 阅读量趋势 — 按周统计的阅读事件数量（ASCII 柱状图）
- 推荐邻近论文 — 基于最近7天阅读记录的语义邻居，但尚未阅读过的
- 活跃工作区 — 当前工作区及其论文数量
前置条件
需要先累积一定量的使用数据（search、usearch、vsearch 和 show 命令会自动记录事件到 data/metrics.db）。
示例
用户说："我最近都在看哪些方向的论文？"
→ 执行 insights --days 30
用户说："看看我过去一周的阅读记录"
→ 执行 insights --days 7
用户说："推荐一些我可能还没读过的相关论文"
→ 执行 insights --days 14（关注第4项"推荐邻近论文"输出）
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.
- 11d ago First seen · 38 lines · 33 tokens per session scan A 5e246715ad20
insights is a skill published in the GitHub repository ZimoLiao/scholaraio (570 stars, last pushed 11d ago), licensed MIT. It adds 33 tokens to every session and 336 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 2026-08-30.
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