member-position-ranking

member-position-ranking is a skill for Claude Code, Codex from FTShare-Lab/FTShare-skill. It costs 106 tokens per session (842 once invoked), scanned A, original, MIT.

A futures-market lookup for ranking exchange members by their long or short positions in a chosen contract on a chosen trading day.

In plain words
What is it for?
Use it to compare members' position sizes, position changes, and net positions for a futures contract.
Why use it?
It removes the need to assemble member position rankings manually from futures-market data. You can also retrieve results page by page or fetch all pages.

Skill for Claude CodeCodex

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

Good fit Use it to compare members' position sizes, position changes, and net positions for a futures contract.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/ftshare-lab/ftshare-skill/member-position-ranking
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 member-position-ranking
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 member-position-ranking

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

Your own site · 80×15
<a href="https://agentmods.dev/skills/ftshare-lab/ftshare-skill/member-position-ranking"><img src="https://agentmods.dev/badge/skills/ftshare-lab/ftshare-skill/member-position-ranking.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 106 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 842 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 $0.00106 $0.00842
Opus 5 $0.00053 $0.00421
Sonnet 5 $0.00021 $0.00168
Haiku 4.5 $0.00011 $0.00084

Measured 6d ago against content hash 8eda097c64df, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-10, from the pricing page.

Security

Grade A, and why

member-position-ranking 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 6d ago.

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/member-position-ranking/SKILL.md · 78 lines

What it actually says

查询期货会员持仓排名

接口说明

项目 说明
接口名称 查询期货会员持仓排名
外部接口 GET /api/v2/market/data/member-position-ranking
请求方式 GET
适用场景 查询指定交易日、交易所、合约及方向的期货会员持仓排名

请求参数

参数名 类型 是否必填 描述 取值示例 备注
exchange string 交易所代码 DCE SHFE/DCE/CZCE
instrument_id string 合约代码 a2605 -
trade_date string 交易日 20260721 YYYYMMDD 或 YYYY-MM-DD
direction string 查询方向 long longshort,也接受常见中文和缩写别名
page int 页码 1 默认 1
page_size int 每页条数 50 默认 50,最大 200

执行方式

# 查某合约某日多头会员排名
python <RUN_PY> member-position-ranking --exchange DCE --instrument_id a2605 --trade_date 20260721 --direction long
# 查空头排名并翻全量
python <RUN_PY> member-position-ranking --exchange SHFE --instrument_id rb2610 --trade_date 20260721 --direction short --all

<RUN_PY> 为主 SKILL.md 同级的 run.py 绝对路径。

响应结构

返回 code/message/data,记录位于 data.records

{
  "code": 200,
  "message": "success",
  "data": {
    "pageNum": 1, "pageSize": 50, "total": 100, "pages": 2,
    "records": [
      {
        "variety": "a", "code": "a2605", "date": "2026-07-21",
        "direction": "long", "broker": "永安期货",
        "oi": 10000, "oi_chg": 200, "net_position": 5000
      }
    ]
  }
}

records 字段

字段 类型 说明
variety string 品种名称或代码
code string 合约代码
date string 交易日
direction string 持仓方向
broker string 期货会员名称
oi int64/null 持仓量
oi_chg int64/null 持仓量变化
net_position int64/null 净持仓

注意事项

  • exchange/instrument_id/trade_date/direction 四者均为必填。
  • direction 接受 long/short 及常见中文和缩写别名。
  • page_size 最大 200。
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.

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. 6d ago First seen · 78 lines · 106 tokens per session scan A 8eda097c64df

Subscribe to this mod's changes

member-position-ranking is a skill published in the GitHub repository FTShare-Lab/FTShare-skill (63 stars, last pushed 3d ago), licensed MIT. It adds 106 tokens to every session and 842 once invoked, about $0.0005 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 2026-09-03.

Related

Other skills, from other repositories

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