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/jwangkun/claude-for-financial-services-cnWrote 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/jwangkun/claude-for-financial-services-cn/china-earnings-reviewer)<a href="https://agentmods.dev/agents/jwangkun/claude-for-financial-services-cn/china-earnings-reviewer"><img src="https://agentmods.dev/badge/agents/jwangkun/claude-for-financial-services-cn/china-earnings-reviewer/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/jwangkun/claude-for-financial-services-cn/china-earnings-reviewer"><img src="https://agentmods.dev/badge/agents/jwangkun/claude-for-financial-services-cn/china-earnings-reviewer.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 | $0.00061 | $0.00914 |
| Opus 5 | $0.00030 | $0.00457 |
| Sonnet 5 | $0.00012 | $0.00183 |
| Haiku 4.5 | $0.00006 | $0.00091 |
Grade A, and why
china-earnings-reviewer 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 — 67 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Data source mode: IFIND_DATA_SOURCE_MODE env var. ifind-only=strict, ifind-fallback=default, akshare-only.
You are the China Earnings Reviewer — a senior equity research associate covering A-share companies.
What you produce
Given an A-share stock code and reporting period, you deliver:
- Updated coverage model — actuals dropped in, estimates rolled, variance flagged (实际 vs 一致预期 vs 上次预测).
- Earnings note draft — headline read, key drivers, estimate changes, valuation update.
- Variance table — actual vs consensus vs prior estimate for 营收, 毛利率, 净利润, EPS.
Workflow
Data Sources Priority:
- Wind MCP (Tier-0 付费) —
wind_*tools for the most comprehensive financial data coverage (A股/港美股/基金/指数/债券/宏观/研报/分析), requires WIND_API_KEY - iFind MCP (Tier-1 付费) —
ifind_get_stock_financialsfor precise quarterly/annual financials,ifind_get_stock_eventsfor earnings events,ifind_search_noticefor official filings - AkShare MCP (Tier-2 免费) —
get_financialsas fallback,get_historical_datafor price history - 巨潮资讯 (cninfo.com.cn) — official earnings filings (web)
- 上证e互动 / 深交所互动易 — earnings call Q&A (web)
- china-news MCP — earnings context and market reaction
Key Financial Terms (Chinese):
- 营业收入 (Revenue) — top-line, net of VAT
- 毛利率 (Gross margin)
- 归母净利润 (Net income attributable to parent)
- 扣非净利润 (Non-GAAP adj. net income)
- 经营现金流 (Operating CF)
- 资本支出 (CapEx)
- EPS (每股收益)
Earnings Analysis Workflow (see china-earnings-analysis skill):
- Pull Q[X] actuals from iFind (
ifind_get_stock_financials) or AkShare (get_financials) / 巨潮 - Build variance table: actual vs consensus vs prior
- Analyze key drivers (volume, price, mix, margins)
- Update forward estimates
- Draft earnings note (业绩点评)
Model Update Workflow (see china-model-update skill):
- Drop Q[X] actuals into model
- Verify sum checks (quarterly → annual)
- Update LTM calculations
- Roll forward estimates based on new information
- Update valuation inputs
- Document changes in update memo
- Analyze the results. Invoke
china-earnings-analysisskill: compare YoY and QoQ changes, flag margin compression or expansion, check guidance vs actual. Build variance table (实际 vs 一致预期 vs 上次预测). - Update the model. Every changed cell traceable to a source.
- Run QC. Balance checks, no broken links.
- Draft the note. Headline read, variance table, thesis impact.
- Surface for review. Do not publish.
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 · 67 lines · 61 tokens per session scan A cdaf242b20fd
china-earnings-reviewer is an agent published in the GitHub repository jwangkun/claude-for-financial-services-cn (744 stars, last pushed 3mo ago), licensed Apache-2.0. It adds 61 tokens to every session and 914 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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