ftshare-market-data

ftshare-market-data is a skill for Claude Code, Codex from FTShare-Lab/FTShare-skill. It costs 59 tokens per session (1,661 once invoked), scanned A, original, MIT.

A collection of tools for retrieving financial and economic data from Chinese, Hong Kong, and United States markets. It covers items such as stock lists, prices, charts, company financial statements, funds, indexes, bonds, news, and macroeconomic data.

In plain words
What is it for?
Use it to query market listings, quotes, historical candlestick data, valuations, IPOs, trades, index constituents, company reports, financial news, and economic indicators.
Why use it?
It removes the need to find and call separate market-data interfaces for each asset or question. A shared command-line entry point routes requests to the relevant data operation.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Use it to query market listings, quotes, historical candlestick data, valuations, IPOs, trades, index constituents, company reports, financial news, and economic indicators.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/ftshare-lab/ftshare-skill/ftshare-market-data
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 FTShare-Lab/FTShare-skill --skill ftshare-market-data
Clone the repo
git clone --depth 1 https://github.com/FTShare-Lab/FTShare-skill

Made for: Claude Code, Codex.

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 ftshare-market-data

README.md
[![agentmods](https://agentmods.dev/badge/skills/ftshare-lab/ftshare-skill/ftshare-market-data/github.svg)](https://agentmods.dev/skills/ftshare-lab/ftshare-skill/ftshare-market-data)
Your own site
<a href="https://agentmods.dev/skills/ftshare-lab/ftshare-skill/ftshare-market-data"><img src="https://agentmods.dev/badge/skills/ftshare-lab/ftshare-skill/ftshare-market-data/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 ftshare-market-data

Your own site · 80×15
<a href="https://agentmods.dev/skills/ftshare-lab/ftshare-skill/ftshare-market-data"><img src="https://agentmods.dev/badge/skills/ftshare-lab/ftshare-skill/ftshare-market-data.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 59 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,661 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. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
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 $0.00059 $0.01661
Opus 5.5 $0.00024 $0.00664
Sonnet 5.5 $0.00012 $0.00332
Haiku 4.5 $0.00006 $0.00166

Measured 9d ago against content hash b9b3c32f7c25, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

ftshare-market-data 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 9d ago.

The scan reads SKILL.md. This mod also ships 33 executable files (run.py, sub-skills/10jqk-board-list/scripts/handler.py, sub-skills/abnormal-trading-details/scripts/handler.py, …), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

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.

ftshare-market-data/SKILL.md · 91 lines

How it starts

The opening of the file, as written. The whole thing — 91 lines — stays where its author put it; the contents beside it link to each section on GitHub.

FTShare Market Data Skills

本 skill 是统一路由入口。子 skill 位于 sub-skills/,由同目录的 run.py 动态发现和执行。

调用

python <RUN_PY> <子skill名> [参数...]

<RUN_PY> 是本文件同级的 run.py 绝对路径。不带参数运行会列出当前可用子 skill。

认证与请求约束

  • 所有请求必须提供 FTSHARE_API_KEY 环境变量。
  • handler 将其作为 FTSHARE_API_KEY 请求头发送,并设置 Content-Type: application/json。
  • 未设置凭据时,handler 在发起请求前以非零状态退出。
  • 默认基础地址为 https://market.ft.tech/gateway,可通过 FTSHARE_BASE_URL 覆盖。
  • 请求使用各子 skill 文档声明的 /api/v1、/api/v2、/api/v3 或 /api/v4 路由;handler 会限制请求 scheme 和 host 与基础地址一致。

常用示例

python <RUN_PY> stock-description-all --symbol-id 600000.SH --page 1 --page-size 1
python <RUN_PY> stock-realtime-minute-kline --symbols 600519.SH 000001.SZ
python <RUN_PY> stock-minutes --symbol 600519.SH --since-ts-millis 1787189400000 --until-ts-millis 1787191200000
python <RUN_PY> stock-minute-seal --trade-date 20260923 --symbol 000560.SZ
python <RUN_PY> etf-realtime-day-kline --symbols 510300.SH
python <RUN_PY> index-minutes --symbol 000300.SH --since-ts-millis 1787189400000 --until-ts-millis 1787191200000
python <RUN_PY> stock-reports --stock-code 600036.SH --page 1 --page-size 20
python <RUN_PY> stock-announcements --stock-code 600000.SH --page 1 --page-size 20
python <RUN_PY> stock-prospectuses --stock-code 600000.SH --page 1 --page-size 20
python <RUN_PY> stock-candlesticks-batch --symbols 600519.SH,600036.SH --interval-unit Day --since-ts-millis 1787000000000 --until-ts-millis 1787191200000
python <RUN_PY> etf-candlesticks-batch --symbols 510300.XSHG,159915.XSHE --interval-unit Day --since-ts-millis 1787000000000 --until-ts-millis 1787191200000
python <RUN_PY> index-candlesticks-batch --symbols 000300.XSHG,399001.XSHE --interval-unit Day --since-ts-millis 1787000000000 --until-ts-millis 1787191200000
python <RUN_PY> futures-kline --symbol A2605.DCE --interval daily --limit 5
python <RUN_PY> futures-kline-batch --symbols A2605.DCE,M2605.DCE --interval daily --limit 5
python <RUN_PY> futures-minutes --symbol A2605.DCE --interval 5min --start 1787000000000 --end 1787191200000 --limit 5
python <RUN_PY> futures-realtime-day-kline --symbols A2605.DCE,M2605.DCE
python <RUN_PY> etf-pcf-infos --symbol 510300.SH --trade-date 20260909
python <RUN_PY> etf-net-value --etf-code 510300 --nav-date 20260909
python <RUN_PY> etf-share --etf-code 510300 --page 1 --page-size 5
python <RUN_PY> etf-announcements --etf-code 159915 --page 1 --page-size 5
python <RUN_PY> etf-component-details --symbol 510300.SH
python <RUN_PY> stock-dividends-effective --symbol 600519.XSHG --page 1 --page-size 20
python <RUN_PY> executive-holdings-changes --stock-code 600519 --page 1 --page-size 20
python <RUN_PY> eastmoney-shareholder-changes --symbol 股东增持 --page 1 --page-size 20
python <RUN_PY> ashare-code-change --trade-code 001872.SZ
python <RUN_PY> ashare-code-change-timeline
python <RUN_PY> ashare-status-change --trade-code 600848.SH --change-type 上市
python <RUN_PY> stock-st-history --symbol 600735.SH,000004.SZ
python <RUN_PY> nth-trade-date --n 5
python <RUN_PY> continuous-auction-volume --trade-date 20260918 --page 1 --page-size 50
python <RUN_PY> news-reaction-snapshot --symbol 600519.SH --start-date 20260818 --end-date 20260828 --lookback-hours 48 --page 1 --page-size 5
python <RUN_PY> semantic-search-news --query 人工智能
python <RUN_PY> stock-candlesticks-daily --trade-date 20261008 --page 1 --page-size 500
python <RUN_PY> ths-board-constituents --board-name 军工 --page 1 --page-size 100
python <RUN_PY> stock-tech-factor --symbol 000001.SZ --trade-date 20261012 --category trend

Read the full file on GitHub · 91 lines

Files

What ships with it

60 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.

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. 9d ago Changed · +7 lines b9b3c32f7c25
  2. 25d ago Changed · +1 lines ade1d64dd186
  3. 1mo ago Changed · +9 lines aa255622bd4a
  4. 1mo ago Changed · +1 lines f031eaba64be
  5. 1mo ago Changed · +1 lines 53c7c25d6392
  6. 1mo ago Changed · +1 lines 928caf4eb2f1
  7. 1mo ago Changed · +8 lines c3688297e85c
  8. 1mo ago Changed · +4 lines ba78869a7255
  9. 1mo ago Changed · -1,024 lines · -150 tokens per session cd9ccc6188bb
  10. 1mo ago First seen · 1,083 lines · 209 tokens per session scan A 492e4722ccd2

Subscribe to this mod's changes

ftshare-market-data is a skill published in the GitHub repository FTShare-Lab/FTShare-skill (64 stars, last pushed 5d ago), licensed MIT. It adds 59 tokens to every session and 1,661 once invoked, about $0.0002 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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