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.
git clone --depth 1 https://github.com/jiadizhunine/deeptutorWrote 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/rules/jiadizhunine/deeptutor/deeptutor)<a href="https://agentmods.dev/rules/jiadizhunine/deeptutor/deeptutor"><img src="https://agentmods.dev/badge/rules/jiadizhunine/deeptutor/deeptutor/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/rules/jiadizhunine/deeptutor/deeptutor"><img src="https://agentmods.dev/badge/rules/jiadizhunine/deeptutor/deeptutor.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 | $0.00354 | $0.00354 |
| Opus 5.5 | $0.00142 | $0.00142 |
| Sonnet 5.5 | $0.00071 | $0.00071 |
| Haiku 4.5 | $0.00035 | $0.00035 |
Grade A, and why
deeptutor 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 1mo 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
DeepTutor — Academic Advisor Investigation System
When the user asks to investigate, evaluate, or compare graduate advisors (e.g., "调查导师", "evaluate professor", "should I join this lab"), follow the full DeepTutor workflow defined in SKILL.md.
Key Rules
- Student outcomes are the #1 signal — weight trajectory evidence above publication metrics
- Language matches input — Chinese input = full Chinese report, English input = full English report
- Region detection — Mainland China uses 知乎/小木虫/百度学术; International uses Reddit/RateMyProfessors/LinkedIn
- Every claim needs a source — no unsourced assertions
- No fabrication — if info unavailable, say so
Web Access Strategy (Chinese Universities)
Chinese .edu.cn sites frequently return 404 due to URL restructuring. Use this fallback chain:
WebFetch(default)- If fails →
wr html <URL>(better HTTP headers) - If fails →
wr html <URL> --js(full browser rendering) - If fails → re-search for current URL via
wr deep "教授名 大学 课题组"
For social platforms (知乎, 小红书): use wr social "query" --platform=zhihu,xiaohongshu instead of individual WebFetch calls.
Full Workflow Reference
See SKILL.md for the complete 10-phase investigation workflow, scoring dimensions, and report template.
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.
- 1mo ago First seen · 33 lines · 354 tokens per session scan A d6909daa2d35
deeptutor is a cursor rule published in the GitHub repository jiadizhunine/deeptutor (31 stars, last pushed 3mo ago), licensed MIT. It adds 354 tokens to every session, about $0.0014 per session on Opus 5.5. 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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