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.
npx skills add zhaixin244-wq/fnw --skill deeptutor-setupgit clone --depth 1 https://github.com/zhaixin244-wq/fnwWrote 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/zhaixin244-wq/fnw/deeptutor-setup)<a href="https://agentmods.dev/skills/zhaixin244-wq/fnw/deeptutor-setup"><img src="https://agentmods.dev/badge/skills/zhaixin244-wq/fnw/deeptutor-setup/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/zhaixin244-wq/fnw/deeptutor-setup"><img src="https://agentmods.dev/badge/skills/zhaixin244-wq/fnw/deeptutor-setup.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 | $0.00076 | $0.01624 |
| Opus 5 | $0.00038 | $0.00812 |
| Sonnet 5 | $0.00015 | $0.00325 |
| Haiku 4.5 | $0.00008 | $0.00162 |
Grade B, and why
deeptutor-setup scanned grade B with 1 finding 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 9d 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.
Reads agent configuration directoriesmediumAgent snooping
.claude/, .codex/, .gemini/ hold keys, settings and other credentials a mod has no legitimate need for.
cat .claude/tools/DeepTutor/.env 2>/dev/null | grep -c "YOUR_.*_API_KEY_HERE" && echo "KEY_MISSING" || echo "KEY_CONFIGURED" How it starts
The opening of the file, as written. The whole thing — 157 lines — stays where its author put it; the contents beside it link to each section on GitHub.
DeepTutor Setup
任务
检测 DeepTutor 部署状态，未部署时自动完成安装配置。确保 deeptutor CLI 可用且 API key 已配置。
前置条件
| 条件 | 检测命令 | 说明 |
|---|---|---|
| Python 3.11+ | python --version |
后端运行时 |
| Git | git --version |
克隆仓库（仅首次） |
| 网络连接 | ping github.com |
下载依赖 |
执行步骤
Step 1: 检测部署状态
按以下顺序检测，记录每步结果：
# 1.1 检测 DeepTutor 目录是否存在
ls .claude/tools/DeepTutor/
# 1.2 检测 Python venv 是否存在
ls .claude/tools/DeepTutor/.venv/Scripts/python.exe 2>/dev/null && echo "VENV_OK" || echo "VENV_MISSING"
# 1.3 检测 deeptutor CLI 是否可用
.claude/tools/DeepTutor/deeptutor.bat --help 2>/dev/null && echo "CLI_OK" || echo "CLI_MISSING"
# 1.4 检测 .env 是否存在且已配置 API key
cat .claude/tools/DeepTutor/.env 2>/dev/null | grep -c "YOUR_.*_API_KEY_HERE" && echo "KEY_MISSING" || echo "KEY_CONFIGURED"
状态判定：
| 状态 | 条件 | 动作 |
|---|---|---|
| ✅ 完全就绪 | 目录 + venv + CLI + API key 均存在 | 跳到 Step 5 输出报告 |
| ⚠️ 部分就绪 | 目录存在但 venv/CLI/key 缺失 | 从缺失步骤开始 |
| ❌ 未部署 | 目录不存在 | 从 Step 2 开始完整部署 |
Step 2: 克隆仓库（如目录不存在）
cd .claude/tools/ && git clone https://ghfast.top/https://github.com/HKUDS/DeepTutor.git 2>&1
镜像备选（ghfast.top 失败时）：
https://gitclone.com/github.com/HKUDS/DeepTutor.githttps://hub.gitclone.com/github.com/HKUDS/DeepTutor.git- 直连：
https://github.com/HKUDS/DeepTutor.git
超时：120 秒。超时后尝试下一个镜像。
Step 3: 安装依赖（如 venv/CLI 不存在）
cd .claude/tools/DeepTutor
# 创建 venv
python -m venv .venv
# 激活 venv 并安装
source .venv/Scripts/activate && pip install -e ".[server]" 2>&1 | tail -10
超时：300 秒。使用清华 PyPI 镜像加速。
验证：
.claude/tools/DeepTutor/deeptutor.bat --help
Step 4: 配置 .env（如 API key 未配置）
cd .claude/tools/DeepTutor && cp .env.example .env
默认配置（LLM + Embedding）：
| 配置项 | 默认值 | 说明 |
|---|---|---|
| LLM_BINDING | xiaomi_mimo |
小米 MIMO |
| LLM_MODEL | mimo-v2.5-pro |
模型名 |
| LLM_HOST | https://api.xiaomimimo.com/v1 |
API 端点 |
| EMBEDDING_BINDING | siliconflow |
硅基流动 |
| EMBEDDING_MODEL | BAAI/bge-large-zh-v1.5 |
中文向量模型 |
| EMBEDDING_HOST | https://api.siliconflow.cn/v1/embeddings |
Embedding 端点 |
| EMBEDDING_DIMENSION | 1024 |
向量维度 |
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.
- 9d ago First seen · 157 lines · 76 tokens per session scan B 413e9609ddee
deeptutor-setup is a skill published in the GitHub repository zhaixin244-wq/fnw (29 stars, last pushed 3mo ago), licensed MIT. It adds 76 tokens to every session and 1,624 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it B with 1 finding (reads agent configuration directories). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
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