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.
npx skills add cyijun/china-financial-services --skill industry-etf-researchgit 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/skills/cyijun/china-financial-services/industry-etf-research)<a href="https://agentmods.dev/skills/cyijun/china-financial-services/industry-etf-research"><img src="https://agentmods.dev/badge/skills/cyijun/china-financial-services/industry-etf-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.
<a href="https://agentmods.dev/skills/cyijun/china-financial-services/industry-etf-research"><img src="https://agentmods.dev/badge/skills/cyijun/china-financial-services/industry-etf-research.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00090 | $0.00832 |
| Opus 5 | $0.00045 | $0.00416 |
| Sonnet 5 | $0.00018 | $0.00166 |
| Haiku 4.5 | $0.00009 | $0.00083 |
Grade A, and why
industry-etf-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 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.
What it actually says
行业 ETF 穿透研究
ETF是行业研究入口和市场验证载体，不是行业定义本身。指数方法、成分暴露和公司基本面分别取证，最后才做综合判断。
工作流
-
固定
as_of、研究问题、行业分类版本与边界。先读 references/methodology.md，把需求、供给、周期、政策和价值链驱动拆成可证伪问题。 -
建立ETF到跟踪指数的映射。不得从ETF简称猜指数；使用基金合同、招募说明书、交易所或指数公司材料核验。读取 references/china-data-map.md 选择数据源。
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审计指数暴露。取得当时有效的编制方案、成分和权重，计算集中度、指数重叠、行业匹配权重、收入纯度及覆盖率；历史研究不得用当前成分回填。
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沿价值链研究公司基本面。需求、供给、价格/利润、库存/产能、政策和估值分栏保存，不把规则分、概率、RPS或ETF涨幅当作基本面结论。行业驱动选择见 references/industry-driver-library.md。
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检查市场确认。分别观察ETF交易价格、复权净值、跟踪差/跟踪误差、成交额、成分广度、收盘价对NAV溢价、盘中价格对IOPV溢价和份额变化。份额变化只能形成“估算净申赎”，不能称为机构或主力资金流。
-
将结构化证据整理为 references/input-contract.md 的JSON，运行：
python3 scripts/build_industry_etf_snapshot.py --input evidence.json --output snapshot.json python3 scripts/validate_industry_etf_report.py snapshot.json -
用“基本面状态 × 市场确认状态”矩阵综合，不生成统一总分。结论必须同时列支持证据、反证、数据缺口和失效条件；格式见 references/report-contract.md。公式与口径见 references/metrics-and-formulas.md。
强制边界
- ETF名称相似不代表行业暴露相同；先核验指数规则和成分。
- 原始交易价格收益不冒充含分红总回报。优先用带公告可得时点的
adj_nav研究基金总回报；AKShare动态qfq/hfq只能用于非严格PIT现状研究并标明口径。 - 收盘NAV溢价与盘中IOPV溢价分列；不同时间戳不得混算。
- 指数权重、行业归属和财务数据都保留可得时点。无历史快照时明确写
unverified，不得伪造PIT。 - 不输出买卖、目标价、轮动、仓位、胜率或概率建议；需要公司层深挖时调用
a-share-company-underwriting，需要证据审计时调用a-share-research-evidence和a-share-research-red-team。
What ships with it
8 files 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.
- references/china-data-map.md 2.8 KB
- references/industry-driver-library.md 2.1 KB
- references/input-contract.md 2.5 KB
- references/methodology.md 3.5 KB
- references/metrics-and-formulas.md 2.3 KB
- references/report-contract.md 1.2 KB
- scripts/build_industry_etf_snapshot.py 32 KB runs code
- scripts/validate_industry_etf_report.py 9.4 KB runs code
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 · 33 lines · 90 tokens per session scan A 3feeb78ee00e
industry-etf-research is a skill published in the GitHub repository cyijun/china-financial-services (19 stars, last pushed 19d ago), licensed Apache-2.0. It adds 90 tokens to every session and 832 once invoked, about $0.0005 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.
Other skills, from other repositories
hithink-finance
A routing guide for accessing Chinese A-share financial data, including prices, company reports, valuations, funds, indices, sectors, and local data storage.
hithink-finance-fund
A command-line guide for querying fund information, including profiles, managers, holdings, prices, returns, financial data, news, and exchange-traded fund snapshots. A command-line tool is a program controlled by typed terminal commands.
hithink-finance-data
A local data-management skill for the HiThink Finance command-line tool and its DuckDB database. DuckDB is a database stored in a local file.
hithink-finance-market
A command-line tool entry for retrieving ordinary Chinese A-share market data, including snapshots, historical price bars, trading calendars, adjustment factors, and company actions.
hithink-finance-special-data
A command-line tool entry for retrieving special Chinese market lists and event data, such as limit-up stocks, limit-down stocks, unusual moves, hot stocks, and Dragon-Tiger records.
hithink-finance-futures
A command-line data source for public futures-market information, including contracts, positions, warehouse receipts, basis, trading schedules, and price charts. Futures are agreements to buy or sell an asset at a set future date.