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 agentmods add agents/xt765/langchain-chinese-comment/load_toolsgit clone --depth 1 https://github.com/xt765/LangChain-Chinese-CommentWrote 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/agents/xt765/langchain-chinese-comment/load_tools)<a href="https://agentmods.dev/agents/xt765/langchain-chinese-comment/load_tools"><img src="https://agentmods.dev/badge/agents/xt765/langchain-chinese-comment/load_tools.svg" alt="Measured on agentmods" 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 | $0.00000 | $0.00488 |
| Opus 5 | $0.00000 | $0.00244 |
| Sonnet 5 | $0.00000 | $0.00098 |
| Haiku 4.5 | $0.00000 | $0.00049 |
Grade A, and why
load_tools 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.
What it actually says
libs\langchain\langchain_classic\agents\load_tools.py
此文档提供了 libs\langchain\langchain_classic\agents\load_tools.py 文件的详细中文注释。该模块定义了如何动态加载 LangChain 预定义的工具。
功能描述
该模块是工具加载系统的代理层。它本身不包含具体的工具加载逻辑，而是利用 create_importer 将请求转发到 langchain_community。
动态导入机制
1. 实现逻辑
_importer = create_importer(
__package__,
fallback_module="langchain_community.agent_toolkits.load_tools",
)
def __getattr__(name: str) -> Any:
return _importer(name)
- create_importer: 创建一个智能导入器。
- fallback_module: 指定当在当前包找不到目标属性时，应跳转到的目标模块：
langchain_community.agent_toolkits.load_tools。 - getattr: Python 的特殊方法。当用户尝试访问模块中不存在的属性（如
load_tools）时，该方法会被触发，并由_importer完成实际的查找和加载。
2. 核心功能
该模块主要导出了以下（动态加载的）功能：
load_tools: 最核心的工具加载函数。允许通过字符串名称（如"arxiv","terminal","human"）快速实例化工具。get_all_tool_names: 获取所有支持的内置工具名称列表。
迁移与背景
- 解耦设计: 将具体工具实现移动到
langchain_community是 LangChain 0.1.0 架构调整的重要部分。 - 透明性: 对于开发者而言，从
langchain_classic.agents.load_tools导入load_tools仍然有效，但底层实际上是在运行社区包的代码。
使用建议
虽然旧路径仍然有效，但为了保持代码的现代性并减少动态查找开销，建议直接从社区包导入：
from langchain_community.agent_toolkits.load_tools import load_tools
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.
- 3d ago First seen · 45 lines · 0 tokens per session scan A 337e89958bb2
load_tools is an agent published in the GitHub repository xt765/LangChain-Chinese-Comment (20 stars, last pushed 1mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 488 tokens. 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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