Agent skill

Industry Deep Explainer

by digoal in digoal/blog

系统性'讲透'一个行业的深度分析技能。覆盖产业链分布、利润分布、代表企业、人货场、供需连接, 并推演不合理点、机会点、入局策略(产品/客群/商业模式/定价)、竞争对手与合作伙伴。触发场景: 讲透/分析XX行业、XX产业链、XX行业机会、如何进入XX行业、XX赛道分析、我想做XX怎么切入等。输出图文并茂的深度分析报告到当前项目 markdown/ 目录。

GPL-2.0Auto-check passedDocuments & Office

Install Industry Deep Explainer

skills CLI
$ npx skills add digoal/blog --skill industry-deep-explainer -a claude-code

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

GitHub CLI
$ gh skill install digoal/blog industry-deep-explainer --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/industry-deep-explainer .claude/skills/industry-deep-explainer && 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
industry-deep-explainer
GitHub stars
8.6k
Token cost
~987 tokens
SKILL.md length
350 words
Files
6 (incl. references)
Skills in repo
98
Repo updated
First seen
Licence
GPL-2.0

At a glance

系统性'讲透'一个行业的深度分析技能。覆盖产业链分布、利润分布、代表企业、人货场、供需连接, 并推演不合理点、机会点、入局策略(产品/客群/商业模式/定价)、竞争对手与合作伙伴。触发场景: 讲透/分析XX行业、XX产业链、XX行业机会、如何进入XX行业、XX赛道分析、我想做XX怎么切入等。输出图文并茂的深度分析报告到当前项目 markdown/ 目录。

  • Works in 9 steps: 输入确认 → 信息搜集与核验 → 六维分析 → …
  • Documents & Office work in your project
  • SKILL.md covers 何时使用本 skill, 与相邻 skill 的边界, 工作流程 (5 步) and 核心原则, plus 2 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Industry Deep Explainer is an agent skill from digoal/blog. 系统性'讲透'一个行业的深度分析技能。覆盖产业链分布、利润分布、代表企业、人货场、供需连接, 并推演不合理点、机会点、入局策略(产品/客群/商业模式/定价)、竞争对手与合作伙伴。触发场景: 讲透/分析XX行业、XX产业链、XX行业机会、如何进入XX行业、XX赛道分析、我想做XX怎么切入等。输出图文并茂的深度分析报告到当前项目 markdown/ 目录。

Its SKILL.md is about 990 tokens, which your agent loads only when the skill is triggered. The skill folder holds 7 other files, including reference files (for example `agents/openai.yaml`, `references/data-sources.md` and `references/framework.md`).

It sits in Documents & Office. 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

  • Documents & Office work in your project

Example prompts

  • “/industry-deep-explainer”

Workflow steps

9 steps, taken from the step headings in SKILL.md.

  1. 输入确认
  2. 信息搜集与核验
  3. 六维分析
  4. 推演三大件
  5. 输出文档
  6. 推演有据
  7. 必引用的理论框架
  8. 视觉规范
  9. 数据时效

What it can do on your machine

Read from SKILL.md and the folder at commit 69fb793. 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.

    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

Industry Deep Explainer loads about 987 tokens when it runs, and up to ~11k if it reads all its reference files. Until then it costs about 50 tokens; SKILL.md has 350 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~50
When it runs · the whole SKILL.md, loaded when a task matches
~987
With references · SKILL.md plus every file in references/, read only if the agent opens them
~11k

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 passed

The automated check found no risky patterns in SKILL.md.

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 69fb793, republished under its GPL-2.0 licence (© digoal). 350 words, ~987 tokens.

Download SKILL.mdSave it as .claude/skills/industry-deep-explainer/SKILL.md (or your agent's skills folder). This skill also uses 5 other files; get the full folder from GitHub.
name
industry-deep-explainer
description
系统性'讲透'一个行业的深度分析技能。覆盖产业链分布、利润分布、代表企业、人货场、供需连接, 并推演不合理点、机会点、入局策略(产品/客群/商业模式/定价)、竞争对手与合作伙伴。触发场景: 讲透/分析XX行业、XX产业链、XX行业机会、如何进入XX行业、XX赛道分析、我想做XX怎么切入等。输出图文并茂的深度分析报告到当前项目 markdown/ 目录。

Industry Deep Explainer — 行业深度讲透

何时使用本 skill

当用户提出以下任一需求时, 立即触发本 skill:

  • "讲透 / 深度分析 / 拆解一下 XX 行业"
  • "XX 行业的产业链 / 上下游 / 价值链"
  • "XX 行业有什么机会 / 痛点 / 不合理"
  • "如何进入 / 切入 XX 行业 / XX 赛道"
  • "我想做 XX 创业, 该怎么做"
  • "用投行 + 战略顾问的视角拆解 XX 行业"
  • "XX 行业的人货场、供需连接"

与相邻 skill 的边界

Skill视角输出
industry-chain-analyst投行分析师上市公司产业链、护城河、风险
industry-insight-writer中立顾问近 1 个月动态公众号文 (≤4 屏)
本 skill (industry-deep-explainer)战略顾问 + 创业者产业链 + 利润 + 人货场 + 入局推演 + 图文并茂深度报告

本 skill 的核心差异化是 "从看行业到切入行业" 的完整推演链, 重点在"如何进入"。

工作流程 (5 步)

Step 1 — 输入确认
  • 用户给出行业名(必需)
  • 如有, 确认三个偏好: 目标读者(投资人/创业者/打工人/学生)、输出语言(默认中文)、重点章节(默认全章节)
Step 2 — 信息搜集与核验

重要: 训练数据可能过时, 必须联网搜索。优先使用 mcp__MiniMax__web_search (用户配置约束)。

执行 5~8 次精准搜索, 覆盖:

"{行业} 产业链 上下游 {当前年份}"
"{行业} 市场规模 增速 集中度 {当前年份}"
"{行业} 竞争格局 头部企业 市占率"
"{行业} 上游 原材料 核心零部件 价格"
"{行业} 终端 消费者 用户画像 渠道"
"{行业} 政策 监管 风险 近期"
"{行业} 龙头 毛利率 财报 估值"
"{行业} 创业 切入 新进入者 机会"

详见 references/data-sources.md。

Step 3 — 六维分析

按 references/framework.md 展开 6 个维度的深度分析:

  1. 产业链与利润分布 — 上下游节点、代表企业、微笑曲线
  2. 供需与连接 — 供给侧、需求侧、连接侧的拆解
  3. 人货场 — 用户画像、产品矩阵、触点场景
  4. 代表企业 — 商业模式、护城河、财务
  5. 代表产品 — 价值主张、定价、迭代
  6. 推演 — 不合理点、机会点、入局策略、竞品、合作伙伴
Step 4 — 推演三大件

按 references/framework.md §推演方法论 严格推演:

  • 不合理点: 信息不对称、效率低、利润分配失衡
  • 机会点: 不合理点对应的可解方案
  • 入局策略: 6 问清单 — 产品/服务、客群、商业模式、定价、市场天花板、竞争与合作
Step 5 — 输出文档

按 references/output-template.md 模板生成最终报告:

  • 路径: markdown/{行业名}-行业深度分析.md (无 markdown 目录则创建)
  • 长度: 6000-12000 字
  • 视觉: mermaid + ASCII + 外部 SVG (按 references/visualization-guide.md 规范)

核心原则

1. 推演有据
  • 每个判断都要有依据: 引用数据(年份+来源)、历史事件、公开财报、学术理论
  • 避免空洞: 不说"市场很大", 说"2025 年市场规模 1500 亿元(艾媒咨询), 年增速 25%"
  • 对立思考: 每个机会都列出反例, 每个优势都列出局限
  • 可执行: 推演出的策略要能落到具体动作(找谁、卖什么、怎么收钱)
1.1 数据自洽性检查 (硬性约束, 落地前必做)

任何涉及 CAGR / 复合增速 / 5 年期增长率 的数据, 写入 markdown 前必须做一次数值复核:

首值 × (1 + r)^n = 末值

例: 数据说"2024 $970 亿 → 2029 $730 亿, CAGR 38%", 代入: 970 × 1.38^5 = 970 × 5.4 = 5238 亿, 与末值 730 差 7 倍, 必有错。

三类常见自相矛盾:

  1. 数字打架: 同一句话里首末值与 CAGR 不自洽
  2. 口径混淆: 把"AI 软件市场"和"生成式 AI 子市场"当成同一回事
  3. 单位错位: 美元/人民币/亿元/亿美元混用, 1000 倍误差

发现矛盾立即重查原始来源, 不要靠"感觉差不多"放过。

Show full SKILL.md (121 more words)Show less
2. 必引用的理论框架

推演时优先调用以下成熟理论(在合适位置自然提及, 不堆砌):

  • 迈克尔·波特《竞争战略》— 五力模型、价值链
  • 施振荣《微笑曲线》— 利润在两端(研发+品牌), 制造在底
  • 克莱顿·克里斯滕森《创新者的窘境》— 颠覆式创新
  • 杰弗里·摩尔《跨越鸿沟》— 早期市场到主流市场的鸿沟
  • 阿尔·里斯、杰克·特劳特《定位》— 用户心智占位
  • 魏朱尔、克里斯多夫《商业模式新生代》— 商业模型画布
  • 大卫·蒂斯《掠夺者、国家与市场》— 价值网
  • 巴尼《资源基础观》— VRIN 资源
3. 视觉规范
  • mermaid 优先: 流程图、时序图、关系图、桑基图(利润分布)、象限图
  • ASCII text: 简单层次结构、对比表格、矩阵
  • 外部 SVG (复杂视觉图): 战略地图、生态图、价值网络、用户体验地图
    • 必须保存为独立 .svg 文件 (放在 markdown/svg/ 子目录)
    • 在 markdown 中用 <img src="./svg/{name}.svg" width="800"> 引用
    • 不在 markdown 中内嵌大段 SVG 代码

完整可视化规范与范例见 references/visualization-guide.md。

4. 数据时效
  • 标注数据年份
  • 凡涉及 IPO 状态、估值、市占率、企业经营情况, 必须用 web 搜索验证, 不能只凭训练记忆
  • 见用户 [记忆: web 搜索验证财务事实]

资源文件

输出检查清单 (写作前自查)

完成报告前, 逐项打勾:

  • 产业链全景图 (mermaid flowchart)
  • 利润分布图 (mermaid sankey 或 ASCII 微笑曲线)
  • 至少 3 个上游/中游/下游代表企业 (含数据)
  • 人货场三章都有, 不偏废
  • 不合理点 ≥ 3 个, 每个对应 ≥ 1 个机会
  • 入局策略回答 6 问 (产品/客群/模式/定价/市场/竞争)
  • 合作伙伴清单含合作模式
  • 每个核心数据标注年份+来源
  • 引用了至少 2 个理论框架
  • 视觉元素 ≥ 5 个 (mermaid + ASCII + SVG 组合)

© digoal, GPL-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 5 other files (references) in skills/industry-deep-explainer of digoal/blog.

  • SKILL.md
  • agents/openai.yaml
  • references/data-sources.md
  • references/framework.md
  • references/output-template.md
  • references/visualization-guide.md

Open the folder on GitHubat commit 69fb793

Compare with similar skills

Industry Deep Explainer 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.

Industry Deep Explainer compared with similar skills
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Questions about Industry Deep Explainer

What does Industry Deep Explainer do?

系统性'讲透'一个行业的深度分析技能。覆盖产业链分布、利润分布、代表企业、人货场、供需连接, 并推演不合理点、机会点、入局策略(产品/客群/商业模式/定价)、竞争对手与合作伙伴。触发场景: 讲透/分析XX行业、XX产业链、XX行业机会、如何进入XX行业、XX赛道分析、我想做XX怎么切入等。输出图文并茂的深度分析报告到当前项目 markdown/ 目录。. Industry Deep Explainer is an agent skill from digoal/blog.

When should I use Industry Deep Explainer?

Industry Deep Explainer fits situations like: documents & Office work in your project.

How do I install Industry Deep Explainer in Claude Code?

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

How do I install Industry Deep Explainer in Codex?

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

Can I use Industry Deep Explainer 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 industry-deep-explainer -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/industry-deep-explainer, .gemini/skills/industry-deep-explainer, .github/skills/industry-deep-explainer and .opencode/skills/industry-deep-explainer in your project.

What does Industry Deep Explainer need to run?

SKILL.md names no scripts, command-line tools or credentials: Industry Deep Explainer is instructions for the agent only.

Does Industry Deep Explainer 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 Industry Deep Explainer safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Industry Deep Explainer use?

Industry Deep Explainer 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 Industry Deep Explainer use?

About 987 tokens (SKILL.md is roughly 3.9k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 9.6k tokens, read only when the agent opens those files.

What are the alternatives to Industry Deep Explainer?

Skills that share tags, products or a category with Industry Deep Explainer: Markdown Article Formatter (JimLiu/baoyu-skills, 26k stars), Markitdown (ImCa0/just-laws, 781 stars), Obsidian Markdown (Atmosphere/atmosphere, 3.8k stars) and DOCX (rvdbreemen/OTGW-firmware, 207 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Industry Deep Explainer?

digoal (a GitHub user) maintains it in digoal/blog, which has 8,587 GitHub stars. The repository holds 98 skills in this directory. The repository was last updated on September 28, 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.