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 a-share-thesis-trackergit 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/a-share-thesis-tracker)<a href="https://agentmods.dev/skills/cyijun/china-financial-services/a-share-thesis-tracker"><img src="https://agentmods.dev/badge/skills/cyijun/china-financial-services/a-share-thesis-tracker/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/a-share-thesis-tracker"><img src="https://agentmods.dev/badge/skills/cyijun/china-financial-services/a-share-thesis-tracker.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 | $0.00079 | $0.00611 |
| Opus 5.5 | $0.00032 | $0.00244 |
| Sonnet 5.5 | $0.00016 | $0.00122 |
| Haiku 4.5 | $0.00008 | $0.00061 |
Grade A, and why
a-share-thesis-tracker 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 1mo 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
A股可证伪论点追踪
模式
build：首次建立论点。update：新财报、公告、行业或估值信息出现后更新。audit：检查论点是否被改写、只记录支持证据或遗漏失效条件。
工作流
- 先读取
a-share-research-evidence证据包。更新模式必须读旧版本，禁止事后改写。 - 用一至两句话写核心论点，并列三至五个可验证支柱；每个支柱有指标、频率和失效条件。
- 写至少三个不同类别的反证或失败路径；未知事项单列。
- 记录估值锚的模型版本、范围和假设；估值变化不能替代基本面证据。
- 建立验证事件日历，区分论点验证事件和短期股价事件。
- 每条新证据记录发生时间、市场可得时间、来源、影响支柱和状态变化。结构化数据必须保留
china-market-data元信息。 - 支柱状态使用
supported、mixed、weakened、broken或unknown，不给综合健康分。 - 输出变化、最强反方、下一检查时间和待补证据。
- 需要本地持久化时使用
scripts/append_thesis_record.py追加JSONL哈希链；脚本强制最小schema，并在同一排他文件锁内完成旧链校验与追加，避免并发写产生分叉。它提供篡改可检测性，不等同于WORM存储、签名或多人权限控制。
硬约束
- 股价涨跌不自动证明论点对错。
- 风险至少覆盖需求、供给/竞争、资产负债表、政策、治理和会计中的适用类别。
- 版本历史不可静默覆盖。
- 不输出自动加仓、减仓、止损或退出指令。
输出契约
输出核心论点、支柱表、反证/失效表、估值锚、催化剂、更新日志、当前状态、最强反方和下一步取证。
需要持久化结构时读取references/thesis-record-schema.md。
What ships with it
2 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.
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.
- 1mo ago First seen · 38 lines · 79 tokens per session scan A 6020d5b73bdb
a-share-thesis-tracker is a skill published in the GitHub repository cyijun/china-financial-services (21 stars, last pushed 2mo ago), licensed Apache-2.0. It adds 79 tokens to every session and 611 once invoked, about $0.0003 per session on Opus 5.5. 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
a-share-data
A data lookup skill for mainland Chinese A-shares, meaning stocks traded on China's Shanghai and Shenzhen exchanges. It covers prices, history, indicators, company events, sectors, concepts, market news, and macroeconomic data.
a-share-paper-trading
A simulated stock-trading and backtesting system for mainland Chinese A-shares. Simulated trading uses pretend orders and money, while backtesting evaluates a strategy against past data.
a-share-strategy-allmarket-multi-swing-defensive
A stock-market decision aid for liquid stocks across China's full market. It uses a trend-pullback strategy to produce possible buy and sell signals and can fetch current price snapshots, but it does not backtest or place orders.
macd-second-golden-cross
A trading-analysis guide for Chinese A-share stocks using MACD, an indicator built from moving averages to show momentum. It focuses on a bullish divergence followed by a second crossover below the zero line.
tuige-shortline-trading
A Chinese-language rulebook for short-term stock trading in the Chinese A-share market. It organizes market conditions, stock selection, chart setups, exit rules, and position discipline.
通达信TQ
A connection between Python strategy files and TdxQuant, TongdaXin's platform for securities data analysis and quantitative investment research. It uses the platform's tqcenter.py module to interact with the TongdaXin client.