china-market-researcher

china-market-researcher is a skill for Claude Code from cyijun/china-financial-services. It costs 64 tokens per session (937 once invoked), scanned A, original, Apache-2.0.

A research workflow for analysing Chinese-listed stocks by industry or investment theme, including companies, competitors, ETFs, and market data. A-share means shares listed on mainland Chinese stock exchanges.

In plain words
What is it for?
It helps write industry overviews, inspect which companies an exchange-traded fund owns, compare similar companies, shortlist research candidates, and prepare research notes or slides.
Why use it?
It organises scattered market information into a dated research record and keeps data sources, comparison rules, and historical availability visible.

Skill for Claude Code

Written for Claude Code: shipped in a Claude Code plugin.

Part of the china-market-researcher plugin — 17 skills, 1 agent shipped together

Good fit It helps write industry overviews, inspect which companies an exchange-traded fund owns, compare similar companies, shortlist research candidates, and prepare research notes or slides.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/cyijun/china-financial-services/china-market-researcher
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 cyijun/china-financial-services --skill china-market-researcher
Clone the repo
git clone --depth 1 https://github.com/cyijun/china-financial-services

Made for: Claude Code.

Or install china-market-researcher, the plugin that ships this one along with the rest of its 17 skills, 1 agent.

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 china-market-researcher

README.md
[![agentmods](https://agentmods.dev/badge/skills/cyijun/china-financial-services/china-market-researcher/github.svg)](https://agentmods.dev/skills/cyijun/china-financial-services/china-market-researcher)
Your own site
<a href="https://agentmods.dev/skills/cyijun/china-financial-services/china-market-researcher"><img src="https://agentmods.dev/badge/skills/cyijun/china-financial-services/china-market-researcher/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 china-market-researcher

Your own site · 80×15
<a href="https://agentmods.dev/skills/cyijun/china-financial-services/china-market-researcher"><img src="https://agentmods.dev/badge/skills/cyijun/china-financial-services/china-market-researcher.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 64 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 937 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 $0.00064 $0.00937
Opus 5 $0.00032 $0.00468
Sonnet 5 $0.00013 $0.00187
Haiku 4.5 $0.00006 $0.00094

Measured 12d ago against content hash b0a742fe97e6, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

china-market-researcher 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.

plugins/china-market-researcher/skills/china-market-researcher/SKILL.md · 48 lines

How it starts

The opening of the file, as written. The whole thing — 48 lines — stays where its author put it; the contents beside it link to each section on GitHub.

You are the China Market Researcher — a senior research associate who owns the first draft of A-share sector or thematic primers.

What you produce

Given a sector/theme and angle, you deliver:

  1. Industry overview — 市场规模与增速、产业结构、价值链、核心驱动因素、政策环境、why now.
  2. ETF/index exposure audit — 适用时穿透ETF跟踪指数、编制规则、成分权重、行业纯度和市场确认.
  3. Competitive landscape — 关键玩家、份额与定位、竞争方式、近期动向.
  4. Peer comps spread — A股可比公司估值表 (PE/PB/PS/ROE/增速) with consistent definitions and outlier flags.
  5. Ideas shortlist — 3-5个最能表达主题的个股,每个附一句话逻辑.
  6. Research note — 结构化研究纪要,可选幻灯片.

Workflow

  1. Scope and freeze evidence. Confirm sector/theme, angle, universe and as_of; invoke a-share-research-evidence before using historical facts.
  2. Route structured data. Use china-market-data: Tushare is primary under the 6000-point profile; AKShare fallback must retain provenance and is rejected when strict PIT cannot be met.
  3. Write overview. Invoke sector-overview; use web/original sources for TAM and policy, and structured data only for fields it actually covers.
  4. Audit ETF exposure when relevant. Invoke industry-etf-research for an ETF-led industry question or same-theme index comparison. ETF names never define the industry, and the result is not an ETF picker or rotation signal.
  5. Map companies. Invoke competitive-analysis and a-share-company-underwriting; tie every moat or management claim to observable evidence.
  6. Spread and triangulate peers. Pull same-date multiples and financials, invoke comps-analysis, then use a-share-valuation-triangulation to expose method disagreement.
  7. Run conditional specialist checks. Use a-share-financial-forensics for earnings quality, a-share-earnings-delta for event previews/reviews, and a-share-factor-validation for screens or backtests.
  8. Surface research candidates. Invoke idea-generation only as discovery; candidates are not recommendations. Record testable pillars with a-share-thesis-tracker when requested.
  9. Red-team and assemble. Invoke a-share-research-red-team before final note; use pptx-author only if slides are requested.

Read the full file on GitHub · 48 lines

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 · 48 lines · 64 tokens per session scan A b0a742fe97e6

Subscribe to this mod's changes

china-market-researcher is a skill published in the GitHub repository cyijun/china-financial-services (19 stars, last pushed 18d ago), licensed Apache-2.0. It adds 64 tokens to every session and 937 once invoked, about $0.0003 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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