Borrowing it
Nothing to install: this file belongs to jiadizhunine/deeptutor. 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/jiadizhunine/deeptutor/main/AGENTS.mdgit 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/instructions/jiadizhunine/deeptutor/agents-md)<a href="https://agentmods.dev/instructions/jiadizhunine/deeptutor/agents-md"><img src="https://agentmods.dev/badge/instructions/jiadizhunine/deeptutor/agents-md/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/instructions/jiadizhunine/deeptutor/agents-md"><img src="https://agentmods.dev/badge/instructions/jiadizhunine/deeptutor/agents-md.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 | $0.03612 | $0.03612 |
| Opus 5.5 | $0.01445 | $0.01445 |
| Sonnet 5.5 | $0.00722 | $0.00722 |
| Haiku 4.5 | $0.00361 | $0.00361 |
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 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.
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.mdand.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:
- Detect language and region from the user's input.
- Run the 10-phase investigation workflow below (or the 6-phase Lite variant for lower-capability models).
- 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.
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 · 244 lines · 3,612 tokens per session scan A 95a061eefd54
deeptutor AGENTS.md is an instructions file published in the GitHub repository jiadizhunine/deeptutor (31 stars, last pushed 3mo ago), licensed MIT. It adds 3,612 tokens to every session, about $0.0144 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.
Other instructions, from other repositories
vscode buildNext.instructions.md
Working notes and architecture documentation for the new esbuild-based build system in build/next. Use when making changes to the new build pipeline (transpile/bundle commands, NLS plugin, source-map handling, resource copying, or self-hosting watch tasks).
next.js AGENTS.md
AGENTS.md instructions for vercel/next.js, covering next.js development guide, codebase structure, monorepo overview, core package: packages/next and other important packages.
vscode oss-third-party-notices.instructions.md
Instructions for microsoft/vscode, covering vs code oss third-party-notices pipeline, architecture, pipeline flow in ci, cache eligibility and rollout and applying the notice (cutover).
langchain AGENTS.md
AGENTS.md instructions for langchain-ai/langchain, covering global development guidelines for the langchain monorepo, corridor security analysis, project architecture and context, monorepo structure and development tools & commands.
vscode copilot-instructions.md
Copilot instructions for microsoft/vscode, covering vs code copilot instructions, project overview, root folders, core architecture (src/ folder) and built-in extensions (extensions/ folder).
vscode model-prompts.instructions.md
Model-specific prompt authoring and registry guidelines.