china-macro-overview

china-macro-overview is a skill for Claude Code from cyijun/china-financial-services. It costs 70 tokens per session (592 once invoked), scanned A, original, Apache-2.0.

A research workflow for describing China’s macroeconomic conditions at a specific point in time using official statistics and traceable market data. It covers growth, inflation, credit, liquidity, exchange rates, and policy transmission without giving trading advice.

In plain words
What is it for?
It helps produce macroeconomic background, policy-transmission analysis, industry scenarios, evidence checks, and clearly sourced figures for China-focused research.
Why use it?
It keeps data aligned by publication date, definition, unit, and revision history. This reduces misleading conclusions caused by mixing incompatible series or using later information for an earlier analysis.

Skill for Claude Code

Written for Claude Code: shipped in a Claude Code plugin.

Part of the financial-analysis plugin — 1 skill shipped together

Good fit It helps produce macroeconomic background, policy-transmission analysis, industry scenarios, evidence checks, and clearly sourced figures for China-focused research.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/cyijun/china-financial-services/china-macro-overview
Install

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.

Any agent
npx skills add cyijun/china-financial-services --skill china-macro-overview
Clone the repo
git clone --depth 1 https://github.com/cyijun/china-financial-services

Made for: Claude Code.

Or install financial-analysis, the plugin that ships this one along with the rest of its 1 skill.

Wrote 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.

agentmods badge for china-macro-overview

README.md
[![agentmods](https://agentmods.dev/badge/skills/cyijun/china-financial-services/china-macro-overview/github.svg)](https://agentmods.dev/skills/cyijun/china-financial-services/china-macro-overview)
Your own site
<a href="https://agentmods.dev/skills/cyijun/china-financial-services/china-macro-overview"><img src="https://agentmods.dev/badge/skills/cyijun/china-financial-services/china-macro-overview/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.

agentmods 80×15 button for china-macro-overview

Your own site · 80×15
<a href="https://agentmods.dev/skills/cyijun/china-financial-services/china-macro-overview"><img src="https://agentmods.dev/badge/skills/cyijun/china-financial-services/china-macro-overview.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 70 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 592 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00070 $0.00592
Opus 5 $0.00035 $0.00296
Sonnet 5 $0.00014 $0.00118
Haiku 4.5 $0.00007 $0.00059

Measured 12d ago against content hash 3d6d9e99735a, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade A, and why

china-macro-overview 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.

plugins/financial-analysis/skills/china-macro-overview/SKILL.md · 28 lines

What it actually says

中国宏观环境分析

工作流

  1. 明确as_of、研究频率、数据截止期和允许的发布滞后,保存每个序列的发布日期与版本。
  2. 原始统计优先国家统计局、人民银行、财政部、海关总署和交易所;Tushare只作结构化便利层。
  3. 分别检查增长、价格、信用、流动性、财政、地产、外贸、汇率和市场定价,不用单一指标概括周期。
  4. 区分水平、同比/环比、趋势、预期差和基数效应;季调、名义/实际、存量/流量不得混用。
  5. 利率分别获取:shiborshibor_lpr以及china-market-datachina_yield_curve。国债曲线优先yc_cb;无权限时,到期收益率标准期限可降级到AKShare bond_china_yield,近3个月即期或非标准期限可用bond_china_close_return。LPR、SHIBOR和美国国债收益率不能替代中国长期无风险利率。
  6. 写出政策工具到实体/行业的因果链、时滞、支持证据、替代解释和最小验证数据。
  7. 构造基础、偏弱、偏强情景,列驱动和可观察触发器,不赋精确概率,不自动映射行业涨跌。

数据边界

  • yc_cb、公告全文等接口可能有单独权限;6000积分不是实时权限证明。
  • 每次曲线请求显式指定到期或即期口径;标准历史AKShare接口没有即期曲线,不能静默替代。
  • 只使用当时已发布的统计批次;后续修订必须作为新版本保留。
  • 来源冲突先核对定义、季调、单位、频率和发布日期,不做多源平均。

输出

输出研究时点、数据日历、增长/通胀/信用/流动性诊断、政策传导、行业暴露、情景、反证和待验证项。每个数字附来源、期间、发布日期和抓取时间;不提供超配/低配、久期或交易动作。

Changes

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.

  1. 12d ago First seen · 28 lines · 70 tokens per session scan A 3d6d9e99735a

Subscribe to this mod's changes

china-macro-overview is a skill published in the GitHub repository cyijun/china-financial-services (19 stars, last pushed 18d ago), licensed Apache-2.0. It adds 70 tokens to every session and 592 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.