deeptutor AGENTS.md

deeptutor AGENTS.md is an instructions file for Codex, OpenCode from jiadizhunine/deeptutor. It costs 3,612 tokens per session, scanned A, original, MIT.

Repository instructions for DeepTutor, an academic-advisor investigation system for evaluating graduate-school professors. It investigates publications, co-authors, student outcomes, lab culture, and possible exploitation risks, then produces an HTML report.

In plain words
What is it for?
Use them to evaluate potential graduate-school advisors and generate a Chinese or English report about their research record, students, lab, and risks.
Why use it?
They define how an agent should investigate and compare professors instead of relying only on publication counts.

Instructions file for CodexOpenCode

Written for Codex and OpenCode: the file is AGENTS.md. Also seen: mentions Claude Code; mentions AGENTS.md; mentions Codex.

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 instructions/jiadizhunine/deeptutor/agents-md
Clone the repo
git clone --depth 1 https://github.com/jiadizhunine/deeptutor

Made for: Codex, OpenCode.

Wrote 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.

agentmods badge for deeptutor AGENTS.md

README.md
[![agentmods](https://agentmods.dev/badge/instructions/jiadizhunine/deeptutor/agents-md.svg)](https://agentmods.dev/instructions/jiadizhunine/deeptutor/agents-md)
Your own site
<a href="https://agentmods.dev/instructions/jiadizhunine/deeptutor/agents-md"><img src="https://agentmods.dev/badge/instructions/jiadizhunine/deeptutor/agents-md.svg" alt="Measured on agentmods" height="20"></a>
Per session 3,612 This file is loaded in full into every session.
When invoked 3,612 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 5.1 $0.03612 $0.03612
Opus 5 $0.01806 $0.01806
Sonnet 5 $0.00722 $0.00722
Haiku 4.5 $0.00361 $0.00361

Measured 6d ago against content hash 95a061eefd54, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-05, from the pricing page.

Security

Grade A, and why

deeptutor AGENTS.md 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 6d 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.

AGENTS.md · 244 lines

How it starts

The opening of the file, as written. The whole thing — 244 lines — stays where its author put it; the contents beside it link to each section on GitHub.

DeepTutor — Academic Advisor Investigation System

Single source of truth for agents.md compliant tools (Codex CLI, OpenCode, OpenClaw, Aider, Cline, Continue, etc.). For Claude Code and Cursor, see SKILL.md and .cursor/rules/deeptutor.mdc — both reference this file's workflow.

Comprehensive professor evaluation tool for graduate-school decisions. Investigates publications, co-author networks, student trajectories (the single most predictive signal), lab culture, and exploitation/PUA risk. Produces a standalone Chinese or English .html report.

Core principle: Your ceiling = your seniors' ceiling. A professor whose students thrive is gold; one whose students vanish is a red flag — regardless of publication metrics.


What this repo is

This is not a traditional code project — it is an AI "skill" / agent prompt-pack. There is nothing to build or npm install. When a user asks the assistant to evaluate a professor, the assistant should:

  1. Detect language and region from the user's input.
  2. Run the 10-phase investigation workflow below (or the 6-phase Lite variant for lower-capability models).
  3. Output structured JSON, then render to HTML via scripts/generate_report.py.

The Python scripts in scripts/ are self-contained helpers — their enabled network path uses only Python's standard library. The fetcher pins each validated hostname to the public IPs returned by one DNS lookup, and search_social.py must reuse that fetcher rather than opening URLs independently. Its curl_cffi and Playwright interfaces fail closed because this integration cannot prove that every optional network path preserves the same boundary. The bundled fetcher intentionally refuses local/private/link-local targets.


When to trigger

Activate this workflow whenever a user asks to investigate, evaluate, or compare graduate advisors. Trigger phrases include:

  • Chinese: 调查导师, 评估教授, 选导师, 导师怎么样, 能不能跟这个老师读研, 这个导师push吗, 帮我看看XX老师, 对比这几个导师
  • English: investigate this advisor, should I join this lab, evaluate professor, is this prof good, rate my potential advisor, review this PI, compare these advisors
  • Implicit: user provides <professor name> + <institution> with any evaluation intent.

Read the full file on GitHub · 244 lines

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. 6d ago First seen · 244 lines · 3,612 tokens per session scan A 95a061eefd54

Subscribe to this mod's changes

deeptutor AGENTS.md is an instructions file published in the GitHub repository jiadizhunine/deeptutor (29 stars, last pushed 1mo ago), licensed MIT. It adds 3,612 tokens to every session, about $0.0181 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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