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Skills/finance-quant/National Team Position

National Team Position

REVIEW · 69
Community indexed

Claude Code skill:估计 A 股「国家队」(中央汇金) 宽基 ETF 持仓变动趋势 / Estimate China's national team (Central Huijin) broad-base ETF positioning

Downloads0
Stars39
Version1.0.0
Quality74/100 · Strong
Trust69/100 · Sandbox only
Audit82/100 · Needs review

Supply asset profile

Finance and quant workflows

Market data, SEC filings, portfolio analysis, quant research, backtesting, and risk workflows.

Browse track

Scenario

Finance and quant

I need my agent to analyze markets, financial data, filings, portfolios, and quant strategies.

Agent fit

Claude Code + CLI + Codex

Codex, Claude Code, Cursor, CLI, or custom agents.

Install

Ready

npx skills add Xiaoyuan-Liu/national-team-position

Maintenance

fresh

1d since push

Risk

Needs review

Low GitHub adoption signal

GitHub quality

39

74/100 quality · 77/100 trust

Coverage tags

FinanceFinance and quantfinance-quantClaude CodeETF

Review notes

Low GitHub adoption signal · Quality score needs review

Agent adoption scorecard

Trust, audit, and install readiness at a glance

These scores combine public repository metadata, OpenAgentSkill review signals, maintenance freshness, and install readiness. They are a shortlist signal, not a replacement for human review.

Quality

Strong
74

Solid option that is likely worth shortlisting for production workflows.

Trust

Sandbox only
69

Useful candidate with missing or mixed trust signals. Keep it in an isolated workspace until the outcome loop proves task fit.

Audit

Needs review
82

Install readiness, security metadata, maintenance, and adoption risk.

Trust Score v5

Human review before install

Run only in a sandbox and compare close alternatives before using it for real work.

PythonCodexClaude CodeCursorOpenAgentSkill CLI

Stars

39 GitHub stars

Repo activity

39 stars, 4 forks

Maintenance

1d since push

License

MIT

Install

npx skills add Xiaoyuan-Liu/national-team-position

Install safety

standard package or runtime install path

Permission surface

shell or command execution

Agent outcomes

No agent outcome data yet

Docs

Strong README/SKILL.md context

Risk summary

Review before production

  • Low GitHub adoption signal
  • Quality score needs review
  • GitHub adoption: 39 GitHub stars
  • Stars/forks activity: 39 stars, 4 forks; issue activity unavailable in current metadata

Install readiness

Install path available

  • Install path is available
  • Repository evidence is available
  • License is declared
  • No Agent Proven outcome evidence yet

Agent-readable metadata

Machine-readable decision data for this skill.

Use this block or the embedded JSON to decide whether an agent should install this skill, choose an alternative, or ask for human review first.

Open JSON

Suited tasks

  • Coding agents workflows
  • Claude Code teams
  • builders willing to evaluate younger projects
  • Inspect source files

Suited agents

PythonCodexClaude CodeCursorOpenAgentSkill CLICLI

Install decision

Command
npx skills add Xiaoyuan-Liu/national-team-position
Policy
review
Human review
yes

Trust and risk

Trust
69/100
Audit
82/100
Risk level
Needs review

Outcome loop

Endpoint
/api/agent/outcome
Event ID
resolve
Outcomes
5

Install command

npx skills add Xiaoyuan-Liu/national-team-position
Public auditEval reportResolve APIInstall handoff

Do not use when

  • teams that need a vendor-supported SLA
  • production agents without a repository review
  • Low GitHub adoption signal
  • No OpenAgentSkill engagement data yet
  • High-risk permission hints: Shell or command execution

Alternative

Quant Buddy Skills

22 stars

npx skills add pseudo-longinus/quant-buddy-skills

Agent safety v2

58/100 · Review before install

Reviewed with permission notesreview

Usable candidate, but the agent should surface permission and audit notes before installation.

Require human approval before installing into a real workspace.

Resolve via API

high

Shell or command execution

Skill metadata references terminal, CLI, shell, subprocess, or command execution workflows.

medium

Network access

Skill likely fetches remote pages, APIs, repositories, or external services.

  • High-risk permission hints: Shell or command execution
  • Low GitHub adoption signal

Install targets

Install this skill in your agent workflow

Copy the registry command or an agent-specific install prompt for Codex, Claude Code, and Cursor.

skill install

OpenAgentSkill CLI

Use the registry command when your workflow supports the OpenAgentSkill installer.

$ npx skills add Xiaoyuan-Liu/national-team-position

Agent resolve plan

Let an agent verify fit before installing.

The Resolve API returns the selected skill, alternatives, safety policy, audit notes, install target, and copy-paste prompt an agent can follow without scraping this page.

Open text plan

Resolve JSON

/api/agent/resolve?task=Use%20National%20Team%20Position%20for%20an%20agent%20workflow&agent=codex&max_risk=medium

Resolve text

/api/agent/resolve?task=Use%20National%20Team%20Position%20for%20an%20agent%20workflow&agent=codex&max_risk=medium&format=text

Install handoff

/api/skills/xiaoyuan-liu-national-team-position/install

Agent should check

  • Task fit and alternatives from Resolve API.
  • Audit score, trust score, and safety policy warnings.
  • Install target compatibility for Codex, Claude Code, Cursor, or CLI.

Copy prompt

Task: Use National Team Position in this workspace.
Resolve first: https://www.openagentskill.com/api/agent/resolve?task=Use%20National%20Team%20Position%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Review install handoff: https://www.openagentskill.com/api/skills/xiaoyuan-liu-national-team-position/install
Install command: npx skills add Xiaoyuan-Liu/national-team-position
Before running it, summarize audit warnings, required permissions, and the fallback skill if install is risky.

Agent handoff

Give an agent the install path, not another directory page.

Use the public install endpoint to fetch the command, safety checklist, target prompts, and canonical links for this skill.

Open install API

Install handoff

/api/skills/xiaoyuan-liu-national-team-position/install

LLM text format

/api/skills/xiaoyuan-liu-national-team-position/install?format=text

Find alternatives

/api/skills/search?q=National%20Team%20Position&limit=3

Agent prompt

Use National Team Position for this task. Review https://www.openagentskill.com/api/skills/xiaoyuan-liu-national-team-position/install, then install with: npx skills add Xiaoyuan-Liu/national-team-position

Registry metadata

Agent-readable profile for automatic skill selection.

This page exposes the same decision, trust, audit, use-case, and install signals through the Registry API, so agents can rank this skill without scraping the UI.

Open manifest

Manifest

/api/registry/manifest/xiaoyuan-liu-national-team-position

LLM text

/api/registry/manifest/xiaoyuan-liu-national-team-position?format=text

Install alias

/api/registry/install/xiaoyuan-liu-national-team-position

Recommend

/api/registry/recommend?task=Use%20National%20Team%20Position%20in%20an%20agent%20workflow&limit=3

Agent fit

73/100

Coding agents

Use-case tags

Coding agentsData analysisFinance and quant

Platforms

Python, Claude Code

Audit report

Needs review · 82/100

Review install readiness, maintenance, trust, quality, and metadata warnings before adding this skill to an agent workflow.

View audit reportView eval report

Agent decision cockpit

Companion skill for Coding agents

Shortlist this skill and compare it with close alternatives before production adoption.

73
Readiness
Shortlist
Stage

Role in stack

Companion skill

Primary fit

Coding agents

Trust label

Strong shortlist

Install path

Command ready

Use when

  • Coding agents workflows
  • Claude Code teams
  • builders willing to evaluate younger projects

Evidence

  • recent repository activity
  • install command or GitHub repo available
  • 74/100 quality profile

Review first

  • Low GitHub adoption signal
  • No OpenAgentSkill engagement data yet

Implementation path

  1. 1Install it in a sandbox agent and run one Coding agents task end to end.
  2. 2Compare output quality, latency, and failure behavior against at least one alternative.
  3. 3Promote it into production only after reviewing repository permissions, license, and maintenance signals.

Trust profile

Sandbox only

Useful candidate with missing or mixed trust signals. Keep it in an isolated workspace until the outcome loop proves task fit.

69
Trust score

GitHub adoption

CHECK

39 GitHub stars

Stars/forks activity

CHECK

39 stars, 4 forks; issue activity unavailable in current metadata

Recent maintenance

PASS

1d since push

License clarity

PASS

MIT

Good signals

  • AI review approved
  • Install path is available
  • Repository evidence is available
  • Recently maintained repository
  • Install command has no obvious high-risk pattern
  • Outcome loop is ready but needs first real agent run

Review before install

  • Low GitHub adoption signal
  • Quality score needs review
  • GitHub adoption: 39 GitHub stars
  • Stars/forks activity: 39 stars, 4 forks; issue activity unavailable in current metadata
  • No real agent outcome reports yet
  • Human review required before unattended installation

Recommended action

Run only in a sandbox and compare close alternatives before using it for real work.

Quality profile

Strong candidate for agent workflows

Solid option that is likely worth shortlisting for production workflows.

74
GitHub stars
39
Freshness
1d ago
Install ready
Yes
License
MIT
Check before install: Low GitHub adoption signal

Workflow fit

Use this skill in these scenarios

Build and ship code

Coding agents

I need a coding agent that can understand a repository, edit code, and review pull requests.

Analyze datasets

Data analysis

I need my agent to analyze CSV data, produce insights, and explain trends.

Analyze markets

Finance and quant

I need my agent to analyze markets, financial data, filings, portfolios, and quant strategies.

Stack fit

Add it to a complete workflow

Inspect, patch, and verify code

Coding review agent

A stack for software agents that inspect repositories, review pull requests, generate tests, and turn findings into shippable patches.

Operate and verify web apps

Browser QA agent

A stack for agents that navigate products, fill forms, take screenshots, and verify real user flows across web applications.

Scrape, clean, and reuse web data

Web data pipeline

A practical stack for agents that crawl public pages, extract clean content, normalize data, and hand it to downstream research or RAG workflows.

Alternative shortlist

Compare before you install

Similar skills in this category, ranked with the same readiness and quality signals.

Compare all

Quant Buddy Skills

A reusable AI agent skill for quantitative analysis of A-share, HK, and US stocks, including market data, fundamentals, screening, factor calculation, and backtesting.

Prototype
Ready69
Quality70
Stars22

Overview

# national-team-position · 国家队持仓估计

一个 [Claude Code](https://claude.com/claude-code) Agent Skill:通过追踪上交所核心**宽基 ETF 份额**变化,估计中国 A 股「国家队」(中央汇金)的持仓变动与结构轮动,并生成可视化图表。

> A Claude Code Agent Skill that estimates China's "national team" (Central Huijin) broad-base ETF positioning by tracking Shanghai Stock Exchange ETF share changes, and renders charts.

## 它能做什么

- 覆盖六大上交所宽基:**沪深300 / 上证50 / 中证500 / 中证1000 / 中证A500 / 科创50** - 追踪 ETF **份额**(而非规模,已排除价格涨跌干扰),更真实地反映净买卖行为 - 输出一张**六合一总图** + 六张**各指数单图**(每张 = 该宽基份额 + 对应指数价格双轴)+ JSON 数据 - 能区分「真减仓」与「换仓轮动」(例如沪深300 见顶后资金是否流向新发的中证A500)

### 示例输出

![六合一总图:各宽基 ETF 份额 vs 对应指数走势](assets/overview.png)

> 上图为 2023 至今的六合一总图:每格的彩色线是该宽基的 ETF 份额(左轴,估计国家队持仓),灰线是对应指数价格(右轴)。

| 文件 | 内容 | |------|------| | `national_team_overview.png` | 六合一总图(2×3) | | `national_team_hs300/sse50/csi500/csi1000/csiA500/star50.png` | 各指数单图 | | `national_team_position.json` | 各宽基份额时间序列 + 全宽基合计 |

## 安装

本仓库即一个独立 skill,直接克隆到 Claude Code 的 skills 目录:

```bash git clone https://github.com/Xiaoyuan-Liu/national-team-position.git \ ~/.claude/skills/national-team-position ```

安装依赖:

```bash pip install akshare matplotlib pandas ```

> macOS 自带中文字体;Linux 需自备中文字体(如 `fonts-noto-cjk`),否则图中中文会显示为方块。

## 使用

在 Claude Code 中直接说「**看看国家队持仓**」「**国家队最近在加仓还是减仓**」即可自动触发, 或手动执行脚本:

```bash # 推荐看 2023 至今,完整覆盖「建仓 → 轮动 → 撤离」 python ~/.claude/skills/national-team-position/scripts/national_team_position.py \ --start 2023-01-01 --output-dir ./ ```

| 参数 | 说明 | |------|------| | `--start` / `--end` | 日期范围 `YYYY-MM-DD`,默认 2024-01-01 ~ 今天 | | `--output-dir` | 输出目录,默认当前目录 | | `--freq` | 采样频率 `weekly`(默认)/ `monthly` | | `--data-only` | 仅输出 JSON,不画图 |

## 原理

中央汇金是宽基 ETF 的绝对控盘方,其申赎会直接体现在 ETF **份额**上。脚本按周(或按月)从 上交所 ETF 份额接口(经 [AKShare](https://github.com/akfamily/akshare) 封装的 `fund_etf_scale_sse`, 一次调用即返回当日全部 ETF)采样各宽基份额,并叠加各指数日线走势。

## 局限与免责声明

### 为什么只统计上交所、不含深交所(创业板、深市中证1000 / A500 等)

**这不是「深市没有数据」,而是沪深两个交易所的公开披露机制不同。** 本工具依赖 AKShare 封装的交易所官方 ETF 份额接口,而两市接口能力不对等:

| | 上交所 `fund_etf_scale_sse`

Platform Compatibility

pythonFULL

Technical Details

Version
1.0.0
License
MIT
Last Updated
7/20/2026
Published
7/20/2026

Frameworks & Tools

Python

Decision snapshot

Companion skill

73
Ready
Shortlist
Stage

recent repository activity

Audit snapshot

Install review

Install and adoption review

82
Needs review
Security
83/100
Maintenance
100/100
Install
92/100
Open full auditOpen eval report

Agent-proven evidence

Agent Proven evidence

Outcome reports after resolve, review, install, and one narrow run.

0
Proven
Needs first agent runAuto-install: review firstLast: Unknown
Success rate
—
Recent failure
—
Outcomes
0
Output quality
—
Failed
0
Not relevant
0
Installs
0
Risk blocked
0
Setup needed
0
Production
0

No agent outcome data yet. The first agent run can report success, setup needs, risk blocks, failure, or not-relevant through /api/agent/outcome.

Agent-Proven rankingOutcome contract

Install

Add to agent workflow

Free and open source. Review the audit before production use.

Compare AlternativesAuto-resolve PlanView on GitHubDocumentation

Growth loop

Share kit

X

Scenario-led draft for National Team Position, ready for a manual X post.

Curator note
Finance agents don't need louder takes. They need sources, data, and a repeatable research path.

National Team Position helps turn market noise into source-backed analysis an...

39 stars

https://www.openagentskill.com/skills/xiaoyuan-liu-national-team-position?ref=x
#AIAgents
Open X draft
Optional reply with install command
Listing + install path for National Team Position:
https://www.openagentskill.com/skills/xiaoyuan-liu-national-team-position?ref=x

Install: npx skills add Xiaoyuan-Liu/national-team-position
Open reply draft

Listing source

Community indexed

Claimable

This listing was indexed from public sources and is not marked official until a maintainer claim is approved.

Creator
Xiaoyuan-Liu
Source
Xiaoyuan-Liu/national-team-position
Indexed by
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Attribution links to the public repository or creator profile. Creators can claim the listing to update ownership signals.

Claim this skill

Owner claim

Claim this skill listing

This community indexed listing is attributed to Xiaoyuan-Liu but is not marked official yet. Claim it to add a verified owner signal and make future launch, install, and audit updates easier to trust.

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Show the canonical listing, current trust and audit signals, and real Agent Proven evidence where developers evaluate the repository.

[![Listed on OpenAgentSkill](https://www.openagentskill.com/api/badge/xiaoyuan-liu-national-team-position?metric=listed&label=Listed)](https://www.openagentskill.com/skills/xiaoyuan-liu-national-team-position)
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[![Agent Proven](https://www.openagentskill.com/api/badge/xiaoyuan-liu-national-team-position?metric=proven&label=Agent%20Proven)](https://www.openagentskill.com/skills/xiaoyuan-liu-national-team-position)
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Author

X

Xiaoyuan-Liu

@xiaoyuan-liu

Tags

Claude CodeETFChina A-sharescentral huijinagent skill

Platform Fit

Claude Code

Health Signals

GitHub stars
39
Quality score
46/100
Last GitHub push
Jul 20, 2026
Framework hints
1
OpenAgentSkill views
0
Install copies
0
Outbound clicks
0

Community Signal

Share whether this skill looks useful for your agent workflow. Aggregated feedback improves rankings over time.

Trust & Safety

Sandbox only

69
  • GitHub adoption39 GitHub starsCHECK
  • Stars/forks activity39 stars, 4 forks; issue activity unavailable in current metadataCHECK
  • Recent maintenance1d since pushPASS
  • License clarityMITPASS
  • README/SKILL.md completenessMetadata includes enough usage and workflow contextPASS
  • Dependency/runtime riskcommand execution surface, external package install surfaceINFO

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