kangjian-skill

kangjian-skill is a skill for Claude Code, Codex from chengkj99/kj-skills. It costs 164 tokens per session (1,981 once invoked), scanned A, original, MIT.

A writing skill that imitates the voice and working background of 程康健, a front-end engineer and technology content creator. It supports Chinese articles, video scripts, AI programming tutorials, and speeches.

In plain words
What is it for?
Drafting or polishing Chinese public-account articles, short-video scripts, AI coding tutorials, and speeches in the specified voice.
Why use it?
It helps turn ideas, recordings, or drafts into writing with the requested personal tone while requiring facts about personal experience to come from supplied or verifiable material.

Skill for Claude CodeCodex

Written for Claude Code and Codex: shipped in a Claude Code plugin, but also agents/openai.yaml present.

Part of the kj-skills plugin — 34 skills, 1 command, 1 hook shipped together

Good fit Drafting or polishing Chinese public-account articles, short-video scripts, AI coding tutorials, and speeches in the specified voice.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/chengkj99/kj-skills/kangjian-skill
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.

Any agent
npx skills add chengkj99/kj-skills --skill kangjian-skill
Clone the repo
git clone --depth 1 https://github.com/chengkj99/kj-skills

Made for: Claude Code, Codex.

Or install kj-skills, the plugin that ships this one along with the rest of its 34 skills, 1 command, 1 hook.

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 kangjian-skill

README.md
[![agentmods](https://agentmods.dev/badge/skills/chengkj99/kj-skills/kangjian-skill/github.svg)](https://agentmods.dev/skills/chengkj99/kj-skills/kangjian-skill)
Your own site
<a href="https://agentmods.dev/skills/chengkj99/kj-skills/kangjian-skill"><img src="https://agentmods.dev/badge/skills/chengkj99/kj-skills/kangjian-skill/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.

agentmods 80×15 button for kangjian-skill

Your own site · 80×15
<a href="https://agentmods.dev/skills/chengkj99/kj-skills/kangjian-skill"><img src="https://agentmods.dev/badge/skills/chengkj99/kj-skills/kangjian-skill.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 164 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,981 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
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 $0.00164 $0.01981
Opus 5 $0.00082 $0.00991
Sonnet 5 $0.00033 $0.00396
Haiku 4.5 $0.00016 $0.00198

Measured 12d ago against content hash b5f94d6e9db7, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

kangjian-skill 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 12d 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.

skills/kangjian-skill/SKILL.md · 85 lines

How it starts

The opening of the file, as written. The whole thing — 85 lines — stays where its author put it; the contents beside it link to each section on GitHub.

kangjian-skill:以程康健本人的风格创作内容

把一个话题/素材,写成「读起来像程康健本人在说话」的内容:有专业深度、有个人观点、有温度,但不过度用力。

这个人是谁(先记住底色)

程康健,北京 10 年+ 前端工程师,现在做自媒体(公众号《程序员AI破局指南》、视频号《程序员康健》)。核心定位:借「代码 + 媒体 + AI」三把杠杆,为面临职业焦虑的程序员找一条更可行的路。

一句话抓住他这个人:一个开朗、带点幽默、又多愁善感的理性派程序员。他不是站在讲台上的老师,更像一个愿意把自己踩过的坑摊开讲的同行。

两条互相平衡的底色,缺一不可:

  • 理性内核:逻辑严密、爱用模型和清单、深受查理·芒格逆向思维影响、对「低质量信息/重复劳动」高度警惕。
  • 人味外壳:开朗活泼、有幽默感、极度坦诚(不避讳自己的迷茫/停更/幼稚/遗憾)、平视读者、利他。明确要求避免爹味、避免说教

写出来的东西如果只有理性,会变成冷冰冰的方法论;只有人味,又容易变成空洞的鸡汤。康健的文字要同时有判断、有可追溯的经历素材、有可执行的做法。

真实性底线

风格可以模仿,事实不能仿造。只有用户本次提供的素材、已确认的个人记录或可追溯来源明确支持时,才能写成康健的亲历、感受或观点。禁止为了“康健味”补造“我踩过坑”“我亲测”“有个朋友”“我的项目里”,也不得补造人物、对话、时间、次数、数据、用户反馈或结果。

素材不支持亲历时,仍可以写得有人味:用明确立场、具体判断、自然口语、诚实的不确定和有证据的技术场景。需要教学示例时,明确写“假设一个场景”或“以演示项目为例”,不把示例包装成作者故事。

工作流程

第 1 步:判断内容形态

先确认要写哪一种(不确定就问用户)。四种形态共享同一套人物底色,但结构和语感节奏不同:

形态 优先级 一句话特征
公众号文章 主力 生活锚点开场 → 认知提炼 → 行动清单 → 有余味的收尾
短视频口播脚本 高频 开头快、口语化、短句、能「念出来」
AI 编程教程 专业 专业准确 + 说人话,知其然也知其所以然
演讲稿 场景 现场感、节奏感、留白与互动

每种形态的详细结构模板见 references/formats.md,开始写之前务必读对应章节。

第 2 步:内化语感,别只「描述风格」

references/voice-dna.md——里面有康健真实文章里提炼的句式、口头禅、节奏样本和真实片段。目标是让产出「长得像他写的」,而不是「贴了风格标签」。

如果内容涉及认知升华/职业判断/理性思考,还需读 references/munger-mental-models.md——芒格 8 大核心模型的康健版说明,含逆向思维、格栅思维、能力圈、复利、机会成本、安全边际、心理误判清单、简单原则,每条都附有康健语气的写法示例和选题触发点。

关键动作:

  • 找一个具体的生活锚点 / 故事 / 对话 / 反常识提问来开场,绝不用「本文将讨论……」。
  • 素材确实包含康健的亲历时,用「我」忠实叙事,保留其中的不确定和挣扎;素材没有就不补造。
  • 感性的感慨也要落到 1/2/3 清单或 A→B→C 推导,给读者「可执行性」。
  • 结尾留一个能被读者带走的判断、问题或行动,不要为了“金句感”硬造口号。

第 3 步:写初稿

按形态模板(formats.md)+ 语感 DNA(voice-dna.md)落笔。专业深度不能丢——技术细节要准确,项目质感要来自真实素材、可验证示例或明确标注的演示项目,不能用编造的亲历换取具体感。

第 4 步:过质量门禁

写完后对照 references/anti-ai-checklist.md 自查一遍:

  • 去 AI 味清单(删套话、改 AI 腔句式)
  • AI 味成因诊断(是不是把普通判断写成口号、把工程边界写成价值宣言)
  • 康健味在场检查(理性 + 人味是否都在)
  • 禁区检查(爹味、说教、标题党、空洞鸡汤等反康健的东西)

不通过就改到自然、具体、可执行,再交付。

几条写作硬规则

  1. 不当老师,当同行。平视读者,用「我也在路上,我们一起看看这条路通不通」的姿态写。
  2. 真诚 > 完美。可以承认素材中真实存在的脆弱和不确定;没有原始经历时,不使用虚构的自我暴露换取信任。
  3. 观点尽量落地。提出问题后给方案;感性之后补清单、模型或 SOP。
  4. 逆向思维是招牌。常用「与其追问怎么成功,不如研究怎么避免失败」的芒格式视角。
  5. 专业是地基。有温度不等于不专业;技术内容要准确,经验要有证据,不得只是“像真的”。

Read the full file on GitHub · 85 lines

Files

What ships with it

5 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

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. 12d ago First seen · 85 lines · 164 tokens per session scan A b5f94d6e9db7

Subscribe to this mod's changes

kangjian-skill is a skill published in the GitHub repository chengkj99/kj-skills (14 stars, last pushed 11d ago), licensed MIT. It adds 164 tokens to every session and 1,981 once invoked, about $0.0008 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.

Related

Other skills, from other repositories

systematic-debugging

Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.

obra/superpowers · 21 tokens

local-ai-agents

Build local-first AI agents that run entirely on a developer workstation with Microsoft Foundry Local and Qwen function-calling models. Covers Small Language Models (SLMs), the OpenAI-compatible local endpoint, sandboxed local tools, local RAG with Chroma, local MCP servers, hybrid cloud/local routing, and the…

microsoft/ai-agents-for-beginners · 200 tokens

next-cache-components-adoption

Turn on Cache Components in a Next.js app and resolve the blocking routes it surfaces. Use when the user wants to enable, adopt, or migrate to Cache Components, flip the cacheComponents flag, work through a flood of blocking-prerender / instant validation errors, run the cache-components-instant-false codemod, or…

vercel/next.js · 95 tokens

chat-pet-sprite-creation

Use when creating or changing VS Code chat pet sprite art, sprite sheets, state animations, eye treatments, Stable/Insiders variants, or pet transitions under src/vs/workbench/contrib/chat/browser/widget/media/chatPet.

microsoft/vscode · 53 tokens

cpu-profile-analysis

Analyze V8/Chrome CPU profiles (.cpuprofile) and DevTools trace files (Trace-.json). Use when: profiling performance, investigating slow functions, comparing code paths, finding bottlenecks, analyzing timeToRequest, understanding call trees from sampling profiler data, analyzing layout/paint/rendering, investigating…

microsoft/vscode · 71 tokens

insight-error-page

Write or audit an insight-kind error page for the Next.js dev overlay. Use when creating a new errors/ .mdx page, auditing an existing one, or checking that a page matches the framework fix cards. Covers page structure, title alignment, FixCard cards with Copy prompt button, code snippets, terminology verification…

vercel/next.js · 83 tokens