course-campaign

course-campaign is a skill for Claude Code, Codex from chengkj99/kj-skills. It costs 146 tokens per session (2,628 once invoked), scanned A, original, MIT.

A workflow coordinator for writing several chapters of a course in order. It passes each chapter's material to a separate course-writing skill while tracking chapter order, continuity, and progress.

In plain words
What is it for?
Use it when writing at least three chapters from an existing chapter list and reference materials, with optional output, style, and milestone instructions.
Why use it?
It prevents long course-writing jobs from skipping chapters, losing context between chapters, or restarting after an interruption. It saves progress so unfinished work can resume.

Skill for Claude CodeCodex

Written for Claude Code and Codex: argument-hint in frontmatter, but also agents/openai.yaml present. Also seen: mentions Claude Code.

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

Good fit Use it when writing at least three chapters from an existing chapter list and reference materials, with optional output, style, and milestone instructions.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/chengkj99/kj-skills/course-campaign
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 course-campaign
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 course-campaign

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

Your own site · 80×15
<a href="https://agentmods.dev/skills/chengkj99/kj-skills/course-campaign"><img src="https://agentmods.dev/badge/skills/chengkj99/kj-skills/course-campaign.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 146 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,628 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. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
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 $0.00146 $0.02628
Opus 5 $0.00073 $0.01314
Sonnet 5 $0.00029 $0.00526
Haiku 4.5 $0.00015 $0.00263

Measured 12d ago against content hash fdedc6178340, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade A, and why

course-campaign 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/course-campaign/SKILL.md · 174 lines

How it starts

The opening of the file, as written. The whole thing — 174 lines — stays where its author put it; the contents beside it link to each section on GitHub.

course-campaign:整门课程的批量章节编排

把「一份章节清单 + 各章参考材料」按顺序逐章写完。本技能是编排层(工头),每一章的正文都交给 course-generator(执行层/工人)去写;本技能只负责四件工人管不了的事:

  1. 顺序管理——按清单逐章推进,不跳号、不漏章。
  2. 上下文衔接——写下一章前先读上一章结尾,让章节自然接龙。
  3. 进度持久化——每章写完落盘进度,中途中断后能从断点恢复,不从头重来。
  4. 里程碑维护——到指定节点提示 / 执行 /compact,避免上下文爆掉。

适用边界(先确认是不是该用我)

  • ✅ 用我:要连续写多章(≥3 章),已有章节清单和各章材料路径,想一轮跑完。
  • ❌ 不用我:只写一章 → 直接用 course-generator;还没定章节 → ai-programming-topic-planner 先做选题。

输入(缺什么先问,别瞎补)

  1. 课程名称(必需)——如「Claude Code 从入门到精通」。
  2. 章节清单(必需)——每条含:章节编号、标题、参考材料路径、(可选)附加要求。
  3. 输出路径(建议)——章节正文落盘目录。不给就沿用课程已有结构,或问用户。
  4. 里程碑规则(可选)——在哪几章写完后 compact、compact 时保留什么。不给则用默认(见下「上下文管理」)。
  5. 风格基线(可选)——要对齐的已有章节(如「严格对齐 CC-001~CC-004」)。会作为附加要求透传给 course-generator。

启动时的第一件事:建 / 读进度文件

每次被调用,先确认进度文件存在并读它,据此决定从哪一章接着写:

  • 进度文件路径:<输出目录>/.course-campaign-progress.md
  • 不存在 → 按章节清单初始化它(全部标 pending),从第一章开始。
  • 已存在 → 读出 done / pending从第一个非 done 的章节继续,已完成的不重写。

进度文件的字段、状态机、初始化模板见 references/state-and-manifest.md

这一步是「中途可恢复」的根。哪怕对话被 compact、被中断、隔天再来,只要读到这个文件就知道写到哪了。

主循环:每章固定四步(一步都不能省)

对清单里每一个尚未完成的章节,依次执行 A→B→C→D:

Step A:读上一章结尾(第一章跳过)

  • 从进度文件找到上一章的输出文件路径,Read 它的最后两段
  • 记住它引出下一章的方式(是抛了个问题?留了个悬念?点了下一章的名?)。
  • 这决定本章结尾要怎么「接上一章的话茬」,以及开头能不能顺势承接。

如果上一章不是本技能写的(比如清单从 CC-005 起、CC-004 是别人写的),同样去读 CC-004 的结尾,把语感和接龙方式摸清楚。

Step B:调用 course-generator 写本章

Skill 调起 course-generator把下列信息整理成一段清晰的输入传给它(course-generator 是单章引擎,不知道整门课的存在,所有衔接信息都要你喂):

  • 课程名称:<课程名>
  • 章节编号 + 标题:清单里的本章条目
  • 参考材料:清单里本章的材料路径(直接给路径,让 course-generator 自己 Read / 搜料)
  • 输出路径:本章落盘的完整路径
  • 附加要求(关键,把衔接信息塞这里):
    • 「结尾须自然引出下一章:<下一章编号 + 标题>」
    • 「开头承接上一章结尾:<Step A 记到的引出方式>」(第一章无)
    • 「风格严格对齐 <风格基线,如 CC-001~CC-004>」
    • 清单里本章自带的其它附加要求

等 course-generator 真正把文件写完再继续,不要并行抢跑下一章——衔接依赖前一章已落盘。

Step C:更新进度文件

course-generator 交付后:

  • 把本章状态从 pending 改成 done,记上输出文件路径、字数、章节类型。
  • 这是断点续写的存档点,必须每章都写

Read the full file on GitHub · 174 lines

Files

What ships with it

2 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 · 174 lines · 146 tokens per session scan A fdedc6178340

Subscribe to this mod's changes

course-campaign is a skill published in the GitHub repository chengkj99/kj-skills (14 stars, last pushed 11d ago), licensed MIT. It adds 146 tokens to every session and 2,628 once invoked, about $0.0007 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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