A data lookup for changes in the number of shares held by an exchange-traded fund (ETF), a fund traded on a stock exchange. It returns starting and ending shares, purchases, redemptions, net changes, and change rates by date or period.

It helps review ETF share growth or decline, compare creation and redemption activity, and retrieve historical share-count records.

It avoids manually collecting and calculating how an ETF's share count changed over time. Results can be filtered by ETF, date range, and reporting period.

etf-share — Skill for Claude Code and Codex by FTShare-Lab

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 etf-share

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.

README.md

[![agentmods](https://agentmods.dev/badge/skills/ftshare-lab/ftshare-skill/etf-share/github.svg)](https://agentmods.dev/skills/ftshare-lab/ftshare-skill/etf-share)

Your own site

<a href="https://agentmods.dev/skills/ftshare-lab/ftshare-skill/etf-share"><img src="https://agentmods.dev/badge/skills/ftshare-lab/ftshare-skill/etf-share/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.

Your own site · 80×15

<a href="https://agentmods.dev/skills/ftshare-lab/ftshare-skill/etf-share"><img src="https://agentmods.dev/badge/skills/ftshare-lab/ftshare-skill/etf-share.svg" alt="Reviewed on agentmods" width="80" height="20"></a>

Per session 56 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.

When invoked 904 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.

Model	Per session	Once invoked
Fable 5.1	$0.00056	$0.00904
Opus 5	$0.00028	$0.00452
Sonnet 5	$0.00011	$0.00181
Haiku 4.5	$0.00006	$0.00090

Measured yesterday against content hash c7d05372bd70, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

etf-share 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 yesterday.

The scan reads SKILL.md. This mod also ships 1 executable file (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/sub-skills/etf-share/SKILL.md · 62 lines

What it actually says

ETF 份额变动

1. 接口描述

项目	说明
接口名称	ETF 份额（etf_share）
外部接口	`GET /api/v2/market/data/etf-share`
请求方式	GET（query 参数）
适用场景	按 ETF 代码分页查询份额变动：统计周期、统计日期、期末/期初份额、申购/赎回份额、份额净变动和份额变动率，支持按统计周期和日期范围筛选

2. 请求参数

参数名	类型	是否必填	描述	取值示例	备注
etf_code	string	是	ETF 代码	510300	兼容参数名 `fund_code`，建议使用 `etf_code`
stati_perd	string	否	统计周期	全部	`日`/`季度`/`年度`/`截止时点`/`半年`/`全部`；不传默认 `全部`
start_date	int	否	开始日期	20250101	YYYYMMDD，按 `trade_date` 过滤
end_date	int	否	结束日期	20260909	YYYYMMDD，按 `trade_date` 过滤；不早于 `start_date`
page	int	否	页码	1	从 1 开始，默认 1
page_size	int	否	每页条数	50	默认 50，最大 200
--all	-	否	自动翻页拉全量	-	仅本子 skill 扩展参数

3. 响应说明

外层固定为 code / message / data。data 为分页对象：items（列表）、total_pages、total_items。

items 元素：

字段名	类型	说明
trade_code	string	ETF 交易代码
statistics_period	string	统计周期
trade_date	int	统计日期 YYYYMMDD
fund_share	string	期末份额（份）
begin_shares	string / null	期初份额（份）
purchase_shares	string / null	申购份额（份）
redemption_shares	string / null	赎回份额（份）
shares_change	string / null	份额净变动（份）
shares_change_ratio	string / null	份额变动率（%）

4. 调用方式

python <RUN_PY> etf-share --etf-code 510300 --page 1 --page-size 5
python <RUN_PY> etf-share --etf-code 510300 --stati-perd 日 --start-date 20250101 --end-date 20260909
python <RUN_PY> etf-share --etf-code 510300 --all

<RUN_PY> 为主 SKILL.md 同级 run.py 的绝对路径。输出 JSON；HTTP 错误输出到 stderr 并以非零状态退出。

5. 注意事项

份额字段单位为份；数值字段以字符串形式返回，以保留小数精度。
start_date / end_date 可单独提供；同时提供时 start_date 不得晚于 end_date。
--all 会按 total_pages 自动翻页，把所有 items 合并为一个数组返回。

Files

What ships with it

1 file 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.

scripts/handler.py 4.5 KB runs code

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.

yesterday First seen · 62 lines · 56 tokens per session scan A c7d05372bd70

Subscribe to this mod's changes

etf-share is a skill published in the GitHub repository FTShare-Lab/FTShare-skill (64 stars, last pushed yesterday), licensed MIT. It adds 56 tokens to every session and 904 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 2026-09-11.

Analytics and metrics Finance and fintech agent agent-tools financial-data ftshare market-data quantitative-finance

defeatbeta-earnings-analysis

Create professional equity research earnings update reports (8-12 pages, 3,000-5,000 words) analyzing quarterly results for companies already under coverage. Fast-turnaround format focusing on beat/miss analysis, key metrics, updated estimates, and revised thesis. Includes 1-3 summary tables and 8-12 charts. Use when…

defeat-beta/defeatbeta-api · 112 tokens

sprr

Single PR reviewer for awesome-quant. Use when the user asks to review, validate, comment on, label, close, or merge one specific pull request that adds README.md entries. Triggers include "sprr", "review PR", "check PR", and "validate contribution".

wilsonfreitas/awesome-quant · 60 tokens

bprr

Bulk PR reviewer for awesome-quant. Use when the user asks to review all open PRs, review unreviewed PRs, bulk review, or mentions "bprr". Reviews open PRs lacking the reviewed label and presents a summary before any merge/comment/label action.

wilsonfreitas/awesome-quant · 61 tokens

update-pypi-dates

Refresh tracked PyPI last-updated dates in awesome-quant README.md. Use when the user asks to update PyPI dates, refresh PyPI metadata, or run update-pypi-dates.

wilsonfreitas/awesome-quant · 47 tokens

defeatbeta-earnings-preview

Build pre-earnings analysis with normalized baselines, weighted decision models, company-specific veto gates, scenario frameworks, catalysts, historical reactions, and options-implied moves. Use before a company reports quarterly earnings to prepare positioning notes or bilingual three-page PDF reports.

defeat-beta/defeatbeta-api · 60 tokens

defeatbeta-analyst

Professional financial analysis using 60+ market data APIs. Use for: company fundamentals (revenue, margins, EPS, balance sheet), valuation (P/E, P/B, P/S, PEG, DCF, intrinsic value), profitability (ROE, ROA, ROIC), growth trends (YoY revenue/earnings/FCF), earnings transcripts (key data, changes, guidance), industry…

defeat-beta/defeatbeta-api · 154 tokens