knowledge-map

knowledge-map is a skill for Claude Code, Codex from chengkj99/kj-skills. It costs 264 tokens per session (2,535 once invoked), scanned A, original, MIT.

A research-and-layout tool that turns a topic into a single-page visual knowledge map: a structured overview of concepts, tools, stages, and workflows.

In plain words
What is it for?
Use it to create a screenshot-ready HTML map for a field, learning route, toolkit, process, or practical workflow after researching the topic.
Why use it?
It helps organise a broad subject into a readable whole instead of leaving you with disconnected notes or an empty diagram.

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 Use it to create a screenshot-ready HTML map for a field, learning route, toolkit, process, or practical workflow after researching the topic.

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

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

Your own site · 80×15
<a href="https://agentmods.dev/skills/chengkj99/kj-skills/knowledge-map"><img src="https://agentmods.dev/badge/skills/chengkj99/kj-skills/knowledge-map.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 264 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,535 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 $0.00264 $0.02535
Opus 5 $0.00132 $0.01267
Sonnet 5 $0.00053 $0.00507
Haiku 4.5 $0.00026 $0.00253

Measured 9d ago against content hash 401bf50ed321, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-08, from the pricing page.

Security

Grade A, and why

knowledge-map 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 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.

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/knowledge-map/SKILL.md · 144 lines

How it starts

The opening of the file, as written. The whole thing — 144 lines — stays where its author put it; the contents beside it link to each section on GitHub.

knowledge-map · 知识地图生成

把一个主题做成像「一人公司最强 skills 组合」那样的高信息密度全景图:深色背景、彩色卡片网格、阶段流程条、实战工作流、底部建议框。输出是一个自包含单文件 HTML,双击即可在浏览器打开,可直接截图导出为长图/海报。

框架源文件:skill 内置 assets/template.html,随 skill 分发、自包含、零外部依赖。模板内置渲染引擎,你只需填一个 DATA 配置对象,视觉风格(配色、排版、列数自适应)由框架统一保证。


输入收集

  • 必填:主题(如「AI 副业」「前端工程师学习路线」「大模型应用开发全景」)。
  • 可选:副标题/定位语、想覆盖的维度清单、配色主题(dark / midnight / ink,默认 dark)。

只给主题就够了——不要反问用户"你想分哪几个维度"。本 skill 的职责就是替用户把结构规划好。只有当用户主动给了维度清单时才采用其结构。


生成流程

第 1 步:3-5 轮知识调研(核心,不可跳过)

知识地图的价值在于信息密度和准确性,凭空编造的条目会让地图沦为空架子。所以动手画图前,必须用 WebSearch(必要时配合 WebFetch 读取关键页面)对主题做 3-5 轮递进式调研。每轮聚焦一个目的,前一轮的发现指导后一轮的检索词:

  1. 第 1 轮 — 框架/链路:这个主题的核心是什么?业内通常分成哪几个阶段/维度?有没有公认的流程或框架?目的是定出主网格的 4-6 个列(维度)和顶部阶段流程条。
  2. 第 2 轮 — 维度填充:针对第 1 轮定出的每个维度,搜索该维度下具体有哪些工具/技能/步骤/概念/资源。目的是填满每列的条目(每列建议 3-5 条)。
  3. 第 3 轮 — 实战组合:这个领域有哪些公认的"打法/工作流/学习路径/最佳实践组合"?目的是填底部的实战工作流面板。
  4. 第 4-5 轮 — 校验与补强(按需):核对术语是否准确、是否有遗漏的重要维度或过时信息、有没有更权威的提法;补充"使用建议 / 适用场景 / 核心优势"等底部建议框内容。

调研约束:

  • WebSearch 实打实地查,不要凭记忆编。优先权威来源(官方文档、领域头部博客、知名从业者),对过时信息保持警惕,使用用户环境当前日期判断时效。
  • 三轮的递进关系就是 框架 → 维度 → 打法:先定骨架,再填血肉,最后补实战组合,缺一不可。

第 1.5 步:汇报维度清单,等用户确认(硬性检查点,不可跳过)

调研完成后先停下来,不要直接画图。用简洁的列表向用户汇报规划结果,让用户有机会增删调整:

主题定位:<一句话>
配色主题:<dark / midnight / ...>
计划维度(主网格 N 列):
  1. <维度名> —— <该列将放哪些条目,列出条目短名>
  2. ...
阶段流程条:<N 个阶段>
实战工作流:<有/无,若有列出工作流名>
增强标签 / 建议框:<有/无>

然后明确问一句「这个维度规划 OK 吗?需要调整哪里?」收到用户确认(或调整意见处理完)后,才进入第 2 步生成。 只有当用户在最初就明说「不用确认/直接出图/一步到位」时,才跳过本检查点。

第 2 步:组织内容到 DATA 结构

把调研结果映射到模板的 DATA 对象(字段见下方「DATA 数据契约」)。要点:

  • 维度列数 4-6 列最佳,过多会拥挤、过少显单薄。
  • 条目用「短名 + 一行小字说明」:短名是关键词/工具名/概念名,说明是 4-12 字的白话注解。
  • 命名规则:英文工具名、产品名、技术术语、API/函数名一律保留英文原文(如 Next.jsLangChainpgvectorseo-audit),不要硬译成中文;说明小字一律用中文。标题、副标题、维度名、流程文案、建议框等叙述性文字也用中文。这样既专业可检索,又对中文读者友好。
  • 阶段流程条与主网格的列通常一一对应,但流程强调"先后顺序",网格强调"内容清单"。
  • 工作流、标签区、建议框是可选模块,内容不足时可设为 [],框架会自动跳过该区块。
  • 文案去 AI 腔:说人话、具体、有信息量,避免"综上所述""值得注意"等套话。

第 3 步:生成 HTML 文件

  1. 读取 assets/template.html
  2. 用组织好的内容整体替换模板中 const DATA = {...}; 这一段(保留前后的注释和渲染引擎不动)。
  3. 设置 DATA.theme 为用户选的主题(默认 dark)。
  4. 保存到当前工作目录,命名 knowledge-map-<主题简写>.html(主题用简短英文或拼音,避免空格和特殊字符)。

Read the full file on GitHub · 144 lines

Files

What ships with it

3 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. 9d ago First seen · 144 lines · 264 tokens per session scan A 401bf50ed321

Subscribe to this mod's changes

knowledge-map is a skill published in the GitHub repository chengkj99/kj-skills (14 stars, last pushed 7d ago), licensed MIT. It adds 264 tokens to every session and 2,535 once invoked, about $0.0013 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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