industry-chain-research

industry-chain-research is a skill for Claude Code, Codex from Haochenhust/ch-skills. It costs 126 tokens per session (1,428 once invoked), scanned A, original, MIT.

A step-by-step research method for breaking an industry theme into its supply chain, finding bottlenecks, checking candidate companies, and assessing the market stage.

In plain words
What is it for?
Use it for supply-chain analysis, industry research, bottleneck analysis, and investment research on industry opportunities.
Why use it?
It connects broad industry trends with specific companies while testing technical, competitive, financial, and market risks.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Use it for supply-chain analysis, industry research, bottleneck analysis, and investment research on industry opportunities.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/haochenhust/ch-skills/industry-chain-research
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 Haochenhust/ch-skills --skill industry-chain-research
Clone the repo
git clone --depth 1 https://github.com/Haochenhust/ch-skills

Made for: Claude Code, Codex.

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 industry-chain-research

README.md
[![agentmods](https://agentmods.dev/badge/skills/haochenhust/ch-skills/industry-chain-research/github.svg)](https://agentmods.dev/skills/haochenhust/ch-skills/industry-chain-research)
Your own site
<a href="https://agentmods.dev/skills/haochenhust/ch-skills/industry-chain-research"><img src="https://agentmods.dev/badge/skills/haochenhust/ch-skills/industry-chain-research/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 industry-chain-research

Your own site · 80×15
<a href="https://agentmods.dev/skills/haochenhust/ch-skills/industry-chain-research"><img src="https://agentmods.dev/badge/skills/haochenhust/ch-skills/industry-chain-research.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 126 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,428 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 $0.00126 $0.01428
Opus 5 $0.00063 $0.00714
Sonnet 5 $0.00025 $0.00286
Haiku 4.5 $0.00013 $0.00143

Measured 11d ago against content hash 2388382bd6f8, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade A, and why

industry-chain-research 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 11d 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/industry-chain-research/SKILL.md · 106 lines

How it starts

The opening of the file, as written. The whole thing — 106 lines — stays where its author put it; the contents beside it link to each section on GitHub.

产业链研究(Industry Chain Research)

从一个宏观趋势出发,沿产业链逐层下钻,定位瓶颈环节和具体标的,最终输出可执行的投资研究报告。

方法论来源

前 RISC-V Foundation 成员、AI 研究科学家的公开方法 + 王鹏景气度投资四阶段模型。

工作流

四个阶段,每阶段结束后与用户确认方向再继续。

Phase 1 — 产业链地图(Chain Mapping)

用户给出宏观趋势/主题。AI 执行:

  1. web-access skill 搜索最新产业动态
  2. 拆解完整产业链(上游原材料 → 中游制造 → 下游应用)
  3. 标注每个环节供需状态:充裕 / 紧平衡 / 瓶颈
  4. 输出 Mermaid 产业链地图

交互点:展示地图,问用户对哪个瓶颈环节最感兴趣。

Phase 2 — 瓶颈下钻(Bottleneck Drill-down)

对用户选定的环节深入拆解:

  1. 子产业链结构(核心零部件、工艺、材料)
  2. 哪一段最难扩产?为什么?
  3. 全球和 A 股供应商清单:公司名、代码、市值、市占率、核心客户
  4. 是否已进入头部客户供应链?

输出:候选公司清单(聚焦 A 股上市公司)。

Phase 3 — 交叉验证(Cross Validation)

对每个候选标的做五维验证(详见 REFERENCE.md):

  1. 瓶颈持续性 — 技术替代风险?替代方案进展?
  2. 竞争壁垒 — 壁垒来源?追赶者距离?
  3. 收入兑现 — 订单→收入周期?新业务占比?
  4. 风险因素 — 减持/增发?地缘?管理层?
  5. 估值合理性 — 当前 price in 几年?下行空间?

输出:风险验证摘要,标注每个标的为 强烈关注 / 值得跟踪 / 暂时回避

Phase 4 — 市场阶段判断(Phase Assessment)

判断市场对该产业的认知阶段,给出对应的选股建议:

阶段 市场特征 策略
1 分歧期 趋势初现,多空争论 买龙头,确定性优先
2 共识期 逻辑被验证,资金涌入 找供需错配最大的细分环节
3 压制期 预期透支,估值高位 只看二线弹性或新催化
4 泡沫期 全民讨论,故事代替逻辑 回避或只做交易

输出 — 研究报告

汇总 Phase 1-4 内容,生成结构化报告,用 lark-doc skill 发布到飞书云文档。

报告结构见 REFERENCE.md

数据源

wechat-article-feeds(微信公众号文章)

本地存储路径:apps/天演资本/wechat-article-feeds/{公众号名称}/{YYYY-MM-DD}-{标题}.md

订阅了 ~22 个财经类公众号(猫哥读研报、调研纪要更新、聪明投资者、搬砖小组 等),每篇文章含 YAML frontmatter(title, author, date, URL, summary)+ Markdown 正文。

在产业链研究中的用法

  • Phase 1(产业链地图):搜索公众号文章中关于目标产业的分析,获取国内视角的产业链拆解和景气度判断
  • Phase 2(瓶颈下钻):搜索特定环节的深度研报、调研纪要,获取一手的供需数据和公司调研信息
  • Phase 3(交叉验证):用不同公众号的分析交叉印证,避免单一信源偏见

搜索方式:直接用 Grep 工具在 apps/天演资本/wechat-article-feeds/ 目录下搜索关键词。

东方财富研报中心(券商研报)

通过 web-access skill 访问东方财富研报中心,获取券商研报原文和摘要。

搜索入口https://reportapi.eastmoney.com/report/list?industryCode=&pageSize=50&industry=关键词&beginTime=起始日期&endTime=结束日期

在产业链研究中的用法

  • Phase 1(产业链地图):搜索行业研报,获取券商对产业链的专业拆解和景气度评级
  • Phase 2(瓶颈下钻):搜索细分环节的深度研报,获取供需数据、产能统计、公司覆盖
  • Phase 3(交叉验证):查看目标公司的最新研报,获取盈利预测、目标价、风险提示

Read the full file on GitHub · 106 lines

Files

What ships with it

1 file 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. 11d ago First seen · 106 lines · 126 tokens per session scan A 2388382bd6f8

Subscribe to this mod's changes

industry-chain-research is a skill published in the GitHub repository Haochenhust/ch-skills (9 stars, last pushed 2mo ago), licensed MIT. It adds 126 tokens to every session and 1,428 once invoked, about $0.0006 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 2026-08-31.

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