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.
git clone --depth 1 https://github.com/cyijun/china-financial-servicesWrote 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.
[](https://agentmods.dev/agents/cyijun/china-financial-services/china-market-researcher)<a href="https://agentmods.dev/agents/cyijun/china-financial-services/china-market-researcher"><img src="https://agentmods.dev/badge/agents/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.
<a href="https://agentmods.dev/agents/cyijun/china-financial-services/china-market-researcher"><img src="https://agentmods.dev/badge/agents/cyijun/china-financial-services/china-market-researcher.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00064 | $0.00952 |
| Opus 5 | $0.00032 | $0.00476 |
| Sonnet 5 | $0.00013 | $0.00190 |
| Haiku 4.5 | $0.00006 | $0.00095 |
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.
How it starts
The opening of the file, as written. The whole thing — 49 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:
- 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.
- 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.
- Competitive landscape — 关键玩家、份额与定位、竞争方式、近期动向.
- Peer comps spread — A股可比公司估值表 (PE/PB/PS/ROE/增速) with consistent definitions and outlier flags.
- Ideas shortlist — 3-5个最能表达主题的个股，每个附一句话逻辑.
- Research note — 结构化研究纪要，可选幻灯片.
Workflow
- Scope and freeze evidence. Confirm sector/theme, angle, universe and
as_of; invokea-share-research-evidencebefore using historical facts. - 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. - Write overview. Invoke
sector-overview; use web/original sources for TAM and policy, and structured data only for fields it actually covers. - Audit ETF exposure when relevant. Invoke
industry-etf-researchfor 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. - Map companies. Invoke
competitive-analysisanda-share-company-underwriting; tie every moat or management claim to observable evidence. - Spread and triangulate peers. Pull same-date multiples and financials, invoke
comps-analysis, then usea-share-valuation-triangulationto expose method disagreement. - Run conditional specialist checks. Use
a-share-financial-forensicsfor earnings quality,a-share-earnings-deltafor event previews/reviews, anda-share-factor-validationfor screens or backtests. - Surface research candidates. Invoke
idea-generationonly as discovery; candidates are not recommendations. Record testable pillars witha-share-thesis-trackerwhen requested. - Red-team and assemble. Invoke
a-share-research-red-teambefore final note; usepptx-authoronly if slides are requested.
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.
- 12d ago First seen · 49 lines · 64 tokens per session scan A 4b993f572d23
china-market-researcher is an agent 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 952 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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