deeptutor

A rule set for investigating and evaluating graduate advisers, including their research groups and student outcomes. It uses different web sources depending on whether the university is in mainland China or elsewhere.

In plain words
What is it for?
Researching potential advisers, comparing labs, evaluating graduate-study choices, selecting region-specific sources, and producing reports in the user’s language.
Why use it?
It provides a structured way to compare advisers while requiring sourced claims and acknowledging missing information.

Cursor rule for Cursor

Install

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.

agentmods
npx agentmods add rules/jiadizhunine/deeptutor/deeptutor
Clone the repo
git clone --depth 1 https://github.com/jiadizhunine/deeptutor

Made for: Cursor.

Per session 354 This file is loaded in full into every session.
When invoked 354 The same file — it is already loaded in full.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5 $0.00354 $0.00354
Opus 5 $0.00177 $0.00177
Sonnet 5 $0.00071 $0.00071
Haiku 4.5 $0.00035 $0.00035

Measured 3d ago against content hash d6909daa2d35, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

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 3d 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.

.cursor/rules/deeptutor.mdc · 33 lines

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

  1. Student outcomes are the #1 signal — weight trajectory evidence above publication metrics
  2. Language matches input — Chinese input = full Chinese report, English input = full English report
  3. Region detection — Mainland China uses 知乎/小木虫/百度学术; International uses Reddit/RateMyProfessors/LinkedIn
  4. Every claim needs a source — no unsourced assertions
  5. 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:

  1. WebFetch (default)
  2. If fails → wr html <URL> (better HTTP headers)
  3. If fails → wr html <URL> --js (full browser rendering)
  4. 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.

Changes

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.

  1. 3d ago First seen · 33 lines · 354 tokens per session scan A d6909daa2d35

Subscribe to this mod's changes

deeptutor is a cursor rule published in the GitHub repository jiadizhunine/deeptutor (28 stars, last pushed 1mo ago), licensed MIT. It adds 354 tokens to every session, about $0.0018 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.