Agent skill

DB Foundation Course

by digoal in digoal/blog

编写"数据库筑基课"文章的专用 Skill,面向数据库架构师、DBA 和业务开发者。输入一个筑基课文章标题及相关参考资料(技术文档、产品手册、开源项目地址、deepwiki、论文等),输出图文并茂、结构完整的 Markdown 筑基课文章,保存至项目 markdown/…

GPL-2.0Auto-check: warningsDatabases

Install DB Foundation Course

The automated check flagged lines worth reading first. See the safety section below.

skills CLI
$ npx skills add digoal/blog --skill db-foundation-course -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install digoal/blog db-foundation-course --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/digoal/blog.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/skills_for_claude_web/db-foundation-course .claude/skills/db-foundation-course && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
db-foundation-course
GitHub stars
8.6k
Token cost
~1.9k tokens
SKILL.md length
362 words
Files
1
Skills in repo
98
Repo updated
First seen
Licence
GPL-2.0

At a glance

编写"数据库筑基课"文章的专用 Skill,面向数据库架构师、DBA 和业务开发者。输入一个筑基课文章标题及相关参考资料(技术文档、产品手册、开源项目地址、deepwiki、论文等),输出图文并茂、结构完整的 Markdown 筑基课文章,保存至项目 markdown/…

  • Works in 3 steps: 文件的绝对路径 → 文章的章节目录(TOC) → 3 条"读完本文你将掌握"的收益说明
  • Tasks that involve Vector databases
  • SKILL.md covers 一、工作流程总览, 二、标准文章结构(模板), 三、各章节撰写指南 and 四、图表规范, plus 6 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

DB Foundation Course is an agent skill from digoal/blog. 编写"数据库筑基课"文章的专用 Skill,面向数据库架构师、DBA 和业务开发者。输入一个筑基课文章标题及相关参考资料(技术文档、产品手册、开源项目地址、deepwiki、论文等),输出图文并茂、结构完整的 Markdown 筑基课文章,保存至项目 markdown/ 目录。适用主题覆盖:表存储结构(heap/parquet/arrow/zedstore/LSM-Tree/HStore等)、索引结构(btree/gin/brin/hnsw/ivfflat/bloom等)、数据类型与操作符(vector/jsonb/tsvector/range/array等)、优化器扫描算法(seq scan/index scan/bitmap scan/join/agg/并行等)、场景化实践(时序/GIS/RAG/全文检索/图数据/数据湖等)以及事务/锁/并发/安全等周边主题。只要用户提及"筑基课"、"数据库原理"、"数据库内核"写作,或给出了数据库存储/索引/扫描相关的技术文档让你写成教程,都应使用此 Skill。

Its SKILL.md is about 1.9k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in Databases, covering Vector databases, DataFrames and Markdown. It works with Mermaid and SQL. The repository describes itself as: AI,Opensource,Database,Business,Finance,Minds. git clone --depth 1 https://github.com/digoal/blog. The licence is GPL-2.0.

When your agent uses it

  • Tasks that involve Vector databases
  • Tasks that involve DataFrames
  • Tasks that involve Markdown

Example prompts

  • “数据库筑基课”
  • “/db-foundation-course”

Workflow steps

3 steps, taken from the first numbered list in SKILL.md.

  1. 文件的绝对路径
  2. 文章的章节目录(TOC)
  3. 3 条"读完本文你将掌握"的收益说明

What it can do on your machine

Read from SKILL.md and the folder at commit ad6fcb7. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md (its code samples are mermaid, sql, bash and markdown).

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

DB Foundation Course loads about 1.9k tokens when it runs. Until then it costs about 120 tokens; SKILL.md has 362 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~120
When it runs · the whole SKILL.md, loaded when a task matches
~1.9k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check: warnings

The automated check found patterns that need a careful read before installing.

  • WarningContains zero-width charactersSKILL.md:289
    ⟨U+200B⟩```
  • WarningContains zero-width charactersSKILL.md:294
    ⟨U+200B⟩```
  • WarningContains zero-width charactersSKILL.md:298
    ⟨U+200B⟩```
  • WarningContains zero-width charactersSKILL.md:310
    ⟨U+200B⟩```

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from digoal/blog at commit ad6fcb7, republished under its GPL-2.0 licence (© digoal). 362 words, ~1,871 tokens.

Download SKILL.mdSave it as .claude/skills/db-foundation-course/SKILL.md (or your agent's skills folder).
name
db-foundation-course
description
编写"数据库筑基课"文章的专用 Skill,面向数据库架构师、DBA 和业务开发者。输入一个筑基课文章标题及相关参考资料(技术文档、产品手册、开源项目地址、deepwiki、论文等),输出图文并茂、结构完整的 Markdown 筑基课文章,保存至项目 markdown/ 目录。适用主题覆盖:表存储结构(heap/parquet/arrow/zedstore/LSM-Tree/HStore等)、索引结构(btree/gin/brin/hnsw/ivfflat/bloom等)、数据类型与操作符(vector/jsonb/tsvector/range/array等)、优化器扫描算法(seq scan/index scan/bitmap scan/join/agg/并行等)、场景化实践(时序/GIS/RAG/全文检索/图数据/数据湖等)以及事务/锁/并发/安全等周边主题。只要用户提及"筑基课"、"数据库原理"、"数据库内核"写作,或给出了数据库存储/索引/扫描相关的技术文档让你写成教程,都应使用此 Skill。

数据库筑基课 Skill

核心目标:让数据库架构师、DBA、业务开发者学完每篇筑基课后,能将知识直接用于工作实践,打下坚实基础。


一、工作流程总览

输入: 文章标题 + 参考资料(URL / 文档 / 论文 / 代码仓库)
  │
  ├─ Step 1: 读取参考资料
  ├─ Step 2: 按"标准文章结构"起草提纲
  ├─ Step 3: 逐节撰写内容(含图表、代码、示例)
  ├─ Step 4: 自检(逻辑 / 代码 / 事实)
  └─ Step 5: 输出 Markdown 文件 → markdown/<slug>.md

二、标准文章结构(模板)

每篇筑基课文章必须包含以下 12 个章节,可根据主题适当增减子节:

# 数据库筑基课 - <标题>

> 所属系列: [数据库筑基课大纲](链接)  
> 难度: ★☆☆ / ★★☆ / ★★★  
> 适合角色: 架构师 / DBA / 业务开发者

---

## 0. 导读(Why Read This)
## 1. 背景与痛点(Background & Pain Points)
## 2. 核心原理(Core Principles)
## 3. 数据结构 / 存储格式 / 算法详解(Deep Dive)
## 4. 优势与适合场景(Strengths & Use Cases)
## 5. 劣势与不适合场景(Weaknesses & Anti-Patterns)
## 6. 竞品 / 横向技术对比(Comparison)
## 7. 实操与最佳实践(Hands-on & Best Practices)
## 8. 性能调优(Performance Tuning)
## 9. 思考与边界(Thinking & Boundaries)
## 10. 常见问题(FAQ)
## 11. 扩展阅读(Further Reading)

三、各章节撰写指南

§ 0 导读
  • 一句话点明本文解决什么问题
  • 给出"读完本文你能做到什么"的 3 条 bullet
§ 1 背景与痛点
  • 说明技术/功能出现前的痛苦场景(具体,有数字)
  • 用对比图或叙事说明"没有它时有多难"
  • 可画 mermaid 时序图 / 流程图表达痛点
§ 2 核心原理
  • 先用一张总览图(mermaid / SVG / text diagram)展示整体架构
  • 然后逐层展开
  • 原理说明时配合类比(例如 heap 的 fsm 就像"停车场空位管理牌")
§ 3 深度解析

根据主题选择合适的子节,参考如下分类:

存储结构类(heap/parquet/arrow/zedstore/LSM等)

  • file layout(文件级结构)→ block/page layout(块级结构)→ tuple/record layout(行级结构)
  • 写入流程 / 读取流程 / 更新流程 / 删除流程
  • 垃圾回收 / 压缩 / Compaction
  • 索引与存储的协同

索引结构类(btree/gin/brin/hnsw/bloom等)

  • 索引构建算法
  • 索引 page/node 的内部结构
  • 搜索算法(贪婪/二分/图遍历等)
  • 索引维护(插入/删除/分裂/合并)

扫描与计算类(seq scan/index scan/join/agg/并行等)

  • 算法伪代码 or 流程图
  • 代价模型(cost model)简介
  • 执行计划解读(EXPLAIN 输出示例)

数据类型类(vector/jsonb/tsvector等)

  • 内部存储表达
  • 支持的操作符与函数
  • 索引配合使用
§ 4 优势与适合场景
  • 用表格列出:场景 → 为什么适合 → 典型案例
§ 5 劣势与不适合场景
  • 明确说明边界:什么情况会变慢 / 出问题 / 不应使用
  • 给出替代方案
§ 6 竞品/横向对比
  • 至少对比 2~3 个同类技术,使用 Markdown 表格
  • 维度:性能 / 压缩比 / 写入/读取模式 / 事务支持 / 生态 / 适用场景
§ 7 实操与最佳实践
  • 给出可运行的 SQL 或代码示例
  • 至少 1 个完整的场景化 Demo(建表→写入→查询→分析)
  • 列出 DBA 常用的监控/诊断 SQL
  • 标注关键 GUC 参数及推荐值
§ 8 性能调优
  • 调优思路:从 EXPLAIN → 瓶颈定位 → 参数/DDL 调整
  • 列出 TOP 5 调优手段
§ 9 思考与边界
  • 给出 2~3 个"扩展问题"(类似原文的"扩展问题"章节)
  • 每个问题都给出分析过程,不只给答案
  • 点明该技术的本质取舍(trade-off)
§ 10 FAQ
  • 至少 5 条,Q&A 格式
§ 11 扩展阅读
  • 分类列出:官方文档 / 论文 / 源码路径 / 博客 / 相关筑基课章节

四、图表规范

4.1 优先使用 mermaid(流程 / 关系 / 时序)
mermaid
graph TD
    A[Client] --> B[Buffer Pool]
    B --> C{命中?}
    C -- Yes --> D[直接返回]
    C -- No --> E[从磁盘读取 Block]
4.2 存储结构用 text diagram(清晰表达 layout)
File Layout:
┌─────────────────────────────────┐
│  Block 0  │  Block 1  │  ...    │
│  (8KB)    │  (8KB)    │         │
└─────────────────────────────────┘

Block Layout:
┌──────────────┬────────────────────────┐
│  Page Header │  Line Pointers (lp[])  │
├──────────────┴────────────────────────┤
│         Free Space                    │
├───────────────────────────────────────┤
│  Tuple N  │ ... │  Tuple 2  │ Tuple 1 │
└───────────────────────────────────────┘
4.3 对比用 Markdown 表格
特性heap(行存)parquet(列存)zedstore(行列混存)
OLTP 写入★★★★★★★☆☆☆★★★★☆
OLAP 扫描★★☆☆☆★★★★★★★★★☆
............
4.4 SVG(复杂的多层结构,如 HNSW 图)

在确实需要 SVG 时,使用简洁的 <svg> 内联图,宽度限制在 700px 以内。


五、代码示例规范

sql
-- 【示例】创建 heap 表并观察存储结构
CREATE TABLE tbl_demo (
    id    BIGSERIAL PRIMARY KEY,
    name  TEXT,
    score FLOAT
) WITH (fillfactor = 80);

-- 插入测试数据
INSERT INTO tbl_demo (name, score)
SELECT 'user_' || g, random() * 100
FROM generate_series(1, 100000) g;

-- 查看物理文件路径
SELECT pg_relation_filepath('tbl_demo');

-- 查看 block 内容(需要 pageinspect 插件)
SELECT * FROM heap_page_items(get_raw_page('tbl_demo', 0)) LIMIT 5;
  • 代码块必须标注语言(sql / bash / python / json)
  • 关键行加注释
  • 示例数据量适中(不超过百万行,能快速运行)

六、自检清单(输出前必须核对)

在生成最终文件前,逐项检查:

□ 文章结构是否覆盖了 12 个标准章节(允许合并,不允许缺失关键章节)
□ 每个技术概念是否有对应的图示(layout/流程图/对比表)
□ 所有 SQL / 代码示例是否语法正确(逐行检查关键字、括号、引号)
□ 核心原理是否有"类比"帮助理解
□ 对比章节是否客观(不只夸自己,要说出竞品优势)
□ 边界/不适合场景是否明确
□ 扩展阅读的链接格式是否正确
□ 文件名格式是否符合 <YYYYMMDD>_<slug>.md
□ 文章开头是否有"所属系列"链接 和 "难度/角色"标注

七、文件命名与保存

bash
# 目录: markdown/
# 命名: YYYYMMDD_<topic-slug>.md
# 示例:
markdown/20240919_heap-storage.md
markdown/20241015_parquet-columnar.md
markdown/20250624_hnsw-vector-index.md

保存完毕后,输出:

  1. 文件的绝对路径
  2. 文章的章节目录(TOC)
  3. 3 条"读完本文你将掌握"的收益说明

Show full SKILL.md (164 more words)Show less

八、主题速查表(常用参考)

主题类别典型技术点关联大纲章节
行存heap, HOT-update, vacuum, FSM, VM一、表组织结构
列存(磁盘)parquet, orc, lance, vortex一、表组织结构
列存(内存)arrow, monetdb in-memory, DuckDB一、表组织结构
行列混存zedstore, vops一、表组织结构
追加写优化LSM-Tree, HStore/HBase一、表组织结构
有序存储cluster table, 索引组织表一、表组织结构
冷热分层Iceberg, Delta Lake, Hudi一、表组织结构
传统索引btree, hash, bitmap, brin, bloom, gin二、索引组织结构
全文索引gin+tsvector, BM25, zombodb二、索引组织结构
向量索引hnsw, ivfflat, pgvectorscale, vectorchord二、索引组织结构
特殊索引partial/expression/include/global index二、索引组织结构
数据类型vector, jsonb, tsvector, range, array三、数据类型和操作符
扫描算法seq/index/bitmap/index-only scan四、扫描&计算
Join 算法nested loop, hash join, merge join四、扫描&计算
并行计算parallel scan, EPQ, JIT, 向量化四、扫描&计算
场景实践时序/GIS/RAG/全文/图/数据湖五、应用实践
周边能力事务/锁/连接池/安全/存储过程六、其他

九、参考资料获取策略

当用户提供的参考资料为 URL 时:

  1. 使用 web_fetch 获取完整内容
  2. 如果是 GitHub/DeepWiki 地址,重点关注 README、核心源码注释、设计文档
  3. 如果是论文,重点提炼:摘要 → 核心贡献 → 关键算法 → 实验结论
  4. 整理成内部知识后按标准结构输出

十、示例输出片段(heap 文章节选)

markdown
## 1. 背景与痛点

数据库最基础的问题:**一条记录写到哪里?怎么找回来?**

在 heap 之前,如果要自己实现存储,可能会想到顺序存文件——但这样读一条记录需要扫全表。
heap 的设计解决了三个核心问题:

| 问题           | heap 的解法            |
|--------------|----------------------|
| 写到哪里?      | FSM 快速找空闲 block    |
| 怎么定位一行?  | ctid = (blockNum, lp) |
| 怎么回收空间?  | vacuum + autovacuum   |

## 2. 核心原理

### 整体架构

Table Files: main: tbl.1, tbl.2, ... ← 数据文件(每个最大 1GB) fsm: tbl_fsm ← 空闲空间图(Free Space Map) vm: tbl_vm ← 可见性图(Visibility Map)


### Block 内部结构

┌─────────────────────────────────────────┐ ← Block(默认 8KB) │ PageHeaderData (24B) │ │ lp[1] lp[2] lp[3] ... lp[N] │ ← Line Pointers(4B each) │ │ │ ← Free Space → │ │ │ │ Tuple 3 Tuple 2 Tuple 1 │ ← 从尾部向前增长 └─────────────────────────────────────────┘

ctid = (BlockNum, lp_index) 例:ctid=(0,1) 表示第0块,第1条记录


以上即为"数据库筑基课"Skill 的完整指南。 每次生成文章后,务必运行自检清单,确认内容逻辑正确、代码可运行,再保存文件。

© digoal, GPL-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. 4 hidden characters (zero-width or bidirectional) removed. Raw file

Files

Just SKILL.md in skills/skills_for_claude_web/db-foundation-course of digoal/blog.

Open the folder on GitHubat commit ad6fcb7

Compare with similar skills

DB Foundation Course next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

DB Foundation Course compared with similar skills
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Database Scoutzebbern/claude-code-guide4.7k—~1.1kAutomated safety check: PassMIT
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Database Inspectorrongxinzy/RongxinAI154—~835Automated safety check: PassMIT
Data Model ExtractorEmeaAppGbb/spec2cloud100—~2.5kAutomated safety check: PassMIT

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  • Digoal

    digoal/blog

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  • 从论文 PDF 文件或论文 PDF URL 生成通俗易懂、图文并茂、带批判性评估的中文 Markdown 解读,并保存到当前项目的 markdown 目录。Use when the user asks to interpret,精读,解读,summarize,explain,analyze, or write an article from an academic paper PDF…

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Works with

Questions about DB Foundation Course

What does DB Foundation Course do?

编写"数据库筑基课"文章的专用 Skill,面向数据库架构师、DBA 和业务开发者。输入一个筑基课文章标题及相关参考资料(技术文档、产品手册、开源项目地址、deepwiki、论文等),输出图文并茂、结构完整的 Markdown 筑基课文章,保存至项目 markdown/…. DB Foundation Course is an agent skill from digoal/blog.

When should I use DB Foundation Course?

DB Foundation Course fits situations like: tasks that involve Vector databases; tasks that involve DataFrames; tasks that involve Markdown.

How do I install DB Foundation Course in Claude Code?

Run `npx skills add digoal/blog --skill db-foundation-course -a claude-code`. Or copy the skill folder (skills/skills_for_claude_web/db-foundation-course in digoal/blog) into .claude/skills/db-foundation-course in your project. Claude Code loads it when a task matches its description.

How do I install DB Foundation Course in Codex?

Run `npx skills add digoal/blog --skill db-foundation-course -a codex`. Or copy the skill folder (skills/skills_for_claude_web/db-foundation-course in digoal/blog) into .agents/skills/db-foundation-course in your project. Codex loads it when a task matches its description.

Can I use DB Foundation Course in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add digoal/blog --skill db-foundation-course -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/db-foundation-course, .gemini/skills/db-foundation-course, .github/skills/db-foundation-course and .opencode/skills/db-foundation-course in your project.

What does DB Foundation Course need to run?

SKILL.md names no scripts, command-line tools or credentials: DB Foundation Course is instructions for the agent only.

Does DB Foundation Course access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is DB Foundation Course safe to install?

Our automated static check of SKILL.md flagged 4 warning(s): contains zero-width characters. Read the flagged lines before installing; the check is not a guarantee either way.

What licence does DB Foundation Course use?

DB Foundation Course is published under the GPL-2.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does DB Foundation Course use?

About 1.9k tokens (SKILL.md is roughly 7.5k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to DB Foundation Course?

Skills that share tags, products or a category with DB Foundation Course: Import Export (AHS12/thoth-blueprint, 625 stars), Database Scout (zebbern/claude-code-guide, 4.7k stars), Data Model Creation (TencentCloudBase/CloudBase-AI-Toolkit, 1.1k stars) and Database Inspector (rongxinzy/RongxinAI, 154 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains DB Foundation Course?

digoal (a GitHub user) maintains it in digoal/blog, which has 8,586 GitHub stars. The repository holds 98 skills in this directory. The repository was last updated on October 9, 2026.

Source: digoal/blog on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.