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 3-statement-modelgit 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/3-statement-model)<a href="https://agentmods.dev/skills/cyijun/china-financial-services/3-statement-model"><img src="https://agentmods.dev/badge/skills/cyijun/china-financial-services/3-statement-model/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/3-statement-model"><img src="https://agentmods.dev/badge/skills/cyijun/china-financial-services/3-statement-model.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 | $0.00072 | $0.00516 |
| Opus 5.5 | $0.00029 | $0.00206 |
| Sonnet 5.5 | $0.00014 | $0.00103 |
| Haiku 4.5 | $0.00007 | $0.00052 |
Grade A, and why
3-statement-model 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股三表预测模型
工作流
- 调用
a-share-research-evidence和a-share-financial-forensics冻结财务版本、合并范围、累计/单季口径及会计政策。 - 至少导入三年年度和八个季度原始三表，保留
ann_date、f_ann_date、end_date、report_type和更新标志。 - 先建收入量价、毛利、费用、税率、折旧摊销、资本开支和营运资本驱动，再联动三表。
- 利润表流入留存收益；非现金项目、营运资本和投资融资活动流入现金流；期末现金回到资产负债表。
- 债务计划按工具列期初、借入、偿还、利率、利息和期末；循环引用必须显式、可关闭并有收敛检查。
- 政府补助、非经常损益、减值、股权激励、租赁、少数股东和关联交易按重要性单列。
- 建立基础、压力、乐观驱动，不以历史增速直接外推，不赋主观精确概率。
检查与交付
- 工作簿至少包含
Sources、Inputs、三张报表、Schedules、Checks。 - 检查资产=负债+权益、现金流净变动=现金变动、留存收益、固定资产、债务和利息勾稽。
- 计算单元格使用公式，硬编码输入有来源或
[ASSUMPTION]。 - 调用
xlsx-author生成文件，再调用audit-xls；未运行公式引擎时标记formula_execution_unverified。
输出模型、驱动表、勾稽结果、情景和未验证项，不给评级或交易动作。
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 · 26 lines · 72 tokens per session scan A 9f01576c48d3
3-statement-model is a skill published in the GitHub repository cyijun/china-financial-services (21 stars, last pushed 2mo ago), licensed Apache-2.0. It adds 72 tokens to every session and 516 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.
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