new-article

A guide for creating learning articles in the zero2Agent project. Articles use a standard directory, filename, front matter, numbering, and writing style.

In plain words
What is it for?
Use it to add tutorials, interview experience articles, or other educational content to modules such as Agent Basic, LangGraph, Claude Code, and SDK Frameworks.
Why use it?
It removes guesswork about where a new article belongs and how it should be structured. It also helps keep explanations consistent for developers learning agent engineering.

Skill for Claude CodeCodex

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 skills/ranxi2001/zero2agent/new-article
Any agent
npx skills add ranxi2001/zero2Agent --skill new-article
Clone the repo
git clone --depth 1 https://github.com/ranxi2001/zero2Agent

Made for: Claude Code, Codex.

Per session 124 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,467 The whole file, excluding the scripts and references it only reads on demand.
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 $0.00124 $0.01467
Opus 5 $0.00062 $0.00733
Sonnet 5 $0.00025 $0.00293
Haiku 4.5 $0.00012 $0.00147

Measured 2d ago against content hash 041db3075d7f, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

new-article 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 2d 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.

.claude/skills/new-article/SKILL.md · 145 lines

How it starts

The opening of the file, as written. The whole thing — 145 lines — stays where its author put it; the contents beside it link to each section on GitHub.

new-article:创建新文章

本技能用于在 zero2Agent 项目中创建符合项目风格的新学习文章。

项目约定

目录结构

{module-dir}/
└── {NN}-{slug}/
    └── index.md
  • {NN} 是两位数编号,如 010910
  • {slug} 是英文小写、用连字符连接,如 tool-calling-basics
  • 每篇文章独占一个子目录,主文件统一命名为 index.md

已有模块目录

模块 目录 已有文章数
Agent Basic learn-agent-basic/ 08 篇 (01–08)
Agent Survey learn-agent-survey/ 13 篇 (01–13)
Agent Training learn-agent-training/ 06 篇 (01–06)
Agent Interview learn-agent-interview/ 08 篇 (01–08),含面经实录
LangGraph learn-langgraph/ 07 篇 (01–07)
Claude Code learn-claude-code/ 12 篇 (01–12)
SDK Frameworks learn-sdk-frameworks/ 04 篇 (01–04)
OpenClaw learn-openclaw/ 09 篇 (01–09)
Final Project final-project/ 0 篇 (占位符)

Frontmatter 格式

---
layout: default
title: {文章标题(中文)}
description: {一句话描述,10–25 字}
eyebrow: {Module Name} / {NN}
---

eyebrow 示例:Agent Basic / 09LangGraph / 01

文章写作风格(必须遵守)

zero2Agent 的读者是懂代码、懂深度学习基础的开发者,但对 Agent 工程实践还不熟悉。写作时:

  1. 问题优先:先说“为什么要关心这个问题”,再讲概念和方案。不要一上来就定义。
  2. 工程视角:解释概念时,要说清楚它在系统里扮演什么角色,而不是给出教科书定义。
  3. 避免框架崇拜:不要把某个框架讲成“最佳答案”,要讲清楚它解决什么问题、有什么代价。
  4. 暴露真实复杂度:要主动提到“这里容易踩坑”、“Demo 能跑但生产不行”。
  5. 精炼、不废话:不加不必要的修饰语,每个段落有实际内容。
  6. 使用代码块和图表:需要展示执行流程时优先用 ```text 代码块而不是大段描述。需要正式图表时默认使用 ```mermaid,包括多阶段管线、对比关系、架构分层和复杂流程,并按 mermaid-check 验证兼容性。仅当 Mermaid 无法可靠表达所需布局,或用户明确要求可编辑 Draw.io 画布时,才使用 drawio-skill 生成 .drawio 源文件和渲染资产。
  7. 文末导航:在最后用 下一篇建议继续看: + 链接收尾(或说明尚无后续)。

文章结构模板

---
layout: default
title: {标题}
description: {一句话描述}
eyebrow: {Module} / {NN}
---

# {标题}

{开篇:1–3 句话,说明这个话题在实际工程中为什么重要 / 常见误解是什么}

## {核心概念或问题拆解}

{正文……}

## {深入一层:机制 / 设计原则 / 常见坑}

{正文……}

## {实践建议 或 典型误区}

{正文……}

## 小结

{用 3–5 个 bullet 提炼核心观点,不重复正文措辞}

下一篇建议继续看:

- [{下一篇标题}]({相对路径}/index.html)

面试模块特殊格式(learn-agent-interview)

该模块有两类文章,格式不同:

维度拆解文章(01–07)

按考察维度分类,每道题用“新手答 vs 高手答”对比格式:

## Q:{面试题}

> 来源:{公司/岗位}

**新手答**:"{浅层回答}"

**高手答**:

{深度回答,分层递进,带具体方案}

**差距在哪**:{分析新手和高手答案的差距,点出面试官真正在考什么}

Read the full file on GitHub · 145 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. 2d ago First seen · 145 lines · 124 tokens per session scan A 041db3075d7f

Subscribe to this mod's changes

new-article is a skill published in the GitHub repository ranxi2001/zero2Agent (367 stars, last pushed 3d ago), licensed MIT. It adds 124 tokens to every session and 1,467 once invoked, about $0.0006 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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