Agent skill

Anti Gambling Trader

by mars-tw in mars-tw/anti-gambling-trader-tw

分析台股 / 台股ETF / 台指期選擇權 / 美股 / 加密貨幣 / 外匯的交易紀錄 (CSV / JSON / Excel),用統計學判斷使用者的獲利是「可重複的優勢」還是「運氣 + 倖存者偏差(賭博)」,不適合長期投資會明確勸退。內建反詐工具: 掃描群組對話的詐騙話術(scan-text)、檢驗老師宣稱的績效(guru-check)、…

MITAuto-check passedDocuments & Office

Install Anti Gambling Trader

skills CLI

$ npx skills add mars-tw/anti-gambling-trader-tw --skill anti-gambling-trader -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI

$ gh skill install mars-tw/anti-gambling-trader-tw anti-gambling-trader --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy

$ git clone --depth 1 https://github.com/mars-tw/anti-gambling-trader-tw.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.agents/skills/anti-gambling-trader .claude/skills/anti-gambling-trader && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Paste into Claude Code

Install the "anti-gambling-trader" agent skill from https://github.com/mars-tw/anti-gambling-trader-tw/tree/main/.agents/skills/anti-gambling-trader into .claude/skills/anti-gambling-trader/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "anti-gambling-trader", then confirm the skill loads.

Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

$skill-installer

$skill-installer install https://github.com/mars-tw/anti-gambling-trader-tw/tree/main/.agents/skills/anti-gambling-trader

Type this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.

skills CLI

$ npx skills add mars-tw/anti-gambling-trader-tw --skill anti-gambling-trader -a codex

Project install goes to .agents/skills/; add -g for ~/.codex/skills/.

GitHub CLI

$ gh skill install mars-tw/anti-gambling-trader-tw anti-gambling-trader --agent codex

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/mars-tw/anti-gambling-trader-tw.git skills-src && mkdir -p .agents/skills && cp -r skills-src/.agents/skills/anti-gambling-trader .agents/skills/anti-gambling-trader && rm -rf skills-src

Use ~/.agents/skills/ instead of .agents/skills for a personal install.

Codex skills documentation · loads skills from .agents/skills/

Paste into Codex

Install the "anti-gambling-trader" agent skill from https://github.com/mars-tw/anti-gambling-trader-tw/tree/main/.agents/skills/anti-gambling-trader into .agents/skills/anti-gambling-trader/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "anti-gambling-trader", then confirm the skill loads.

Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

skills CLI

$ npx skills add mars-tw/anti-gambling-trader-tw --skill anti-gambling-trader -a cursor

Project install goes to .agents/skills/; add -g for ~/.cursor/skills/.

GitHub CLI

$ gh skill install mars-tw/anti-gambling-trader-tw anti-gambling-trader --agent cursor

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/mars-tw/anti-gambling-trader-tw.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/.agents/skills/anti-gambling-trader .cursor/skills/anti-gambling-trader && rm -rf skills-src

Use ~/.cursor/skills/ instead of .cursor/skills for a personal install.

Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/

Paste into Cursor

Install the "anti-gambling-trader" agent skill from https://github.com/mars-tw/anti-gambling-trader-tw/tree/main/.agents/skills/anti-gambling-trader into .cursor/skills/anti-gambling-trader/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "anti-gambling-trader", then confirm the skill loads.

Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

gemini skills install

$ gemini skills install https://github.com/mars-tw/anti-gambling-trader-tw.git --path .agents/skills/anti-gambling-trader

--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.

skills CLI

$ npx skills add mars-tw/anti-gambling-trader-tw --skill anti-gambling-trader -a gemini-cli

Project install goes to .agents/skills/; add -g for ~/.gemini/skills/.

GitHub CLI

$ gh skill install mars-tw/anti-gambling-trader-tw anti-gambling-trader --agent gemini-cli

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/mars-tw/anti-gambling-trader-tw.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/.agents/skills/anti-gambling-trader .gemini/skills/anti-gambling-trader && rm -rf skills-src

Use ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.

Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/

Paste into Gemini CLI

Install the "anti-gambling-trader" agent skill from https://github.com/mars-tw/anti-gambling-trader-tw/tree/main/.agents/skills/anti-gambling-trader into .gemini/skills/anti-gambling-trader/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "anti-gambling-trader", then confirm the skill loads.

Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

GitHub CLI

$ gh skill install mars-tw/anti-gambling-trader-tw anti-gambling-trader

Installs for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).

skills CLI

$ npx skills add mars-tw/anti-gambling-trader-tw --skill anti-gambling-trader -a github-copilot

Project install goes to .agents/skills/; add -g for ~/.copilot/skills/.

Manual copy

$ git clone --depth 1 https://github.com/mars-tw/anti-gambling-trader-tw.git skills-src && mkdir -p .github/skills && cp -r skills-src/.agents/skills/anti-gambling-trader .github/skills/anti-gambling-trader && rm -rf skills-src

Use ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.

GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/

Paste into GitHub Copilot

Install the "anti-gambling-trader" agent skill from https://github.com/mars-tw/anti-gambling-trader-tw/tree/main/.agents/skills/anti-gambling-trader into .github/skills/anti-gambling-trader/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "anti-gambling-trader", then confirm the skill loads.

GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

skills CLI

$ npx skills add mars-tw/anti-gambling-trader-tw --skill anti-gambling-trader -a opencode

OpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.

GitHub CLI

$ gh skill install mars-tw/anti-gambling-trader-tw anti-gambling-trader --agent opencode

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/mars-tw/anti-gambling-trader-tw.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/.agents/skills/anti-gambling-trader .opencode/skills/anti-gambling-trader && rm -rf skills-src

Use ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.

OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/

Paste into OpenCode

Install the "anti-gambling-trader" agent skill from https://github.com/mars-tw/anti-gambling-trader-tw/tree/main/.agents/skills/anti-gambling-trader into .opencode/skills/anti-gambling-trader/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "anti-gambling-trader", then confirm the skill loads.

OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

Facts

Skill name: anti-gambling-trader
GitHub stars: 907
Token cost: ~1.9k tokens
SKILL.md length: 507 words
Files: 1
Skills in repo: 1
Repo updated: Oct 9, 2026
First seen: Oct 7, 2026
Licence: MIT

At a glance

Works in 12 steps: 機率語氣,不定罪:所有反詐工具只回答「在無能力假設下多容易靠運氣發生」。 → 序數不轉百分比:風險等級是極高/高/中/低,絕不說「87% 是詐騙」。 → 情境非預測:risk-sim 的數字是「如果未來像過去」,不是未來。 → …
Tasks that involve Trading and backtesting
SKILL.md covers 意圖路由表(第一查找點), 通用誠實紀律(跨指令紅線), analyze 主流程 and 風險與趨勢(risk-sim / trend), plus 5 more sections
Calls python

What it does

Anti Gambling Trader is an agent skill from mars-tw/anti-gambling-trader-tw. 分析台股 / 台股ETF / 台指期選擇權 / 美股 / 加密貨幣 / 外匯的交易紀錄 (CSV / JSON / Excel),用統計學判斷使用者的獲利是「可重複的優勢」還是「運氣 + 倖存者偏差(賭博)」,不適合長期投資會明確勸退。內建反詐工具: 掃描群組對話的詐騙話術(scan-text)、檢驗老師宣稱的績效(guru-check)、鑑識假對帳單(forensics)、倖存者偏差示範(survivorship)。可模擬爆倉風險(risk-sim)、偵測優勢衰退(trend)、輸出可傳給家人的 HTML 報告與分享圖卡,並產生 14 種券商選項的交易程式腳架(預設紙上模擬)。當使用者提到:分析我的交易、對帳單、我是不是在賭博、勝率盈虧比、這老師可信嗎、這是詐騙嗎、我會不會賠光爆倉、我最近是不是退步了、把報告傳給家人、建立我的交易程式、接券商 API 時,使用此技能。

Its SKILL.md is about 1.9k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in Documents & Office, covering Trading and backtesting, Excel spreadsheets and Stock and market analysis. It works with Microsoft Excel and Python. The repository describes itself as: 免費開源的投資反詐、交易統計與自動化交易程式工具：預設 PaperBroker，提供 14 種券商／交易所選項；交易紀錄分析在本機執行。 The licence is MIT.

When your agent uses it

Tasks that involve Trading and backtesting
Tasks that involve Excel spreadsheets
Tasks that involve Stock and market analysis

Example prompts

“/anti-gambling-trader”

Requirements

Python 3

Workflow steps

12 steps, taken from the first numbered list in SKILL.md.

機率語氣,不定罪:所有反詐工具只回答「在無能力假設下多容易靠運氣發生」。
序數不轉百分比:風險等級是極高/高/中/低,絕不說「87% 是詐騙」。
情境非預測:risk-sim 的數字是「如果未來像過去」,不是未來。
描述統計不認證:per-tag 與 trend 的分期(月/季)數字不可講成「有優勢/顯著」。
勸退不軟化:gambling / luck_suspected 的結論照實轉述。
🛡 反詐提醒必轉達:使用者可能正被收割而不自知。
負期望 ≠ 樣本不足:required_trades 為 null 時,絕不建議「多交易幾筆再看」——
不自行美化:不另寫摘要或圖卡取代工具輸出(會繞過內建的誠實措辭)。
範例要標明:demo / --example 的結果必須說是內建範例。
真錢紅線:不代下單、不代填金鑰、不代解安全閘門。
截圖一定覆核:OCR 信心只是文字抽取規則分數，不是正確率；正負號、小數點、方向、張/股/口都要對原圖。
適合度不靠問卷認證:fit-check 必須讀完整連續交易紀錄；即使樣本內與樣本外都通過，也只可說「考慮極小額驗證」。

What it can do on your machine

Read from SKILL.md and the folder at commit 8609cef. It shows what the files ask for, not the result of running them.

Tool permissions
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Runs code
Shell commands in SKILL.md call:
- python
From the folder's file list and the shell code blocks in SKILL.md.
Network
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Anti Gambling Trader loads about 1.9k tokens when it runs. Until then it costs about 105 tokens; SKILL.md has 507 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it: ~105
When it runs · the whole SKILL.md, loaded when a task matches: ~1.9k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from mars-tw/anti-gambling-trader-tw at commit 8609cef, republished under its MIT licence (© mars-tw). 507 words, ~1,882 tokens.

Download SKILL.mdSave it as .claude/skills/anti-gambling-trader/SKILL.md (or your agent's skills folder).

name: anti-gambling-trader
description: 分析台股 / 台股ETF / 台指期選擇權 / 美股 / 加密貨幣 / 外匯的交易紀錄 (CSV / JSON / Excel),用統計學判斷使用者的獲利是「可重複的優勢」還是「運氣 + 倖存者偏差(賭博)」,不適合長期投資會明確勸退。內建反詐工具: 掃描群組對話的詐騙話術(scan-text)、檢驗老師宣稱的績效(guru-check)、鑑識假對帳單(forensics)、倖存者偏差示範(survivorship)。可模擬爆倉風險(risk-sim)、偵測優勢衰退(trend)、輸出可傳給家人的 HTML 報告與分享圖卡,並產生 14 種券商選項的交易程式腳架(預設紙上模擬)。當使用者提到:分析我的交易、對帳單、我是不是在賭博、勝率盈虧比、這老師可信嗎、這是詐騙嗎、我會不會賠光爆倉、我最近是不是退步了、把報告傳給家人、建立我的交易程式、接券商 API 時,使用此技能。

反詐投資王 — Anti-Gambling Trader

立場:不討好使用者,只說統計上的實話。 多數人虧錢是把「運氣好」誤當「有本事」;詐騙集團正是靠這個認知弱點收割。勸退結論不得軟化。

意圖路由表(第一查找點)

使用者會怎麼說	指令	轉述紀律(一句話)
第一次用 / 我該從哪開始	`start`	依手上素材分流，不要求使用者先理解全部指令
幫我快速判斷適不適合交易	`fit-check <交易檔>`	只分「停手/紙上/極小額驗證」；沒有完整紀錄最多只能紙上模擬
我不會填表格 / 幫我記一筆	`record [--out my_trades.csv]`	一筆=一筆已平倉交易；策略填當時理由，不准事後美化
幫我看對帳單 / 我這套賺不賺	`analyze <檔案> [--market ...]`	一句話裁決 → 期望值/雙 p 值/樣本外 → 警訊;🛡 反詐提醒必轉達
我是不是在賭博 / 只是運氣好?	`analyze <檔案>`	luck_suspected =「無法排除是運氣」,不是「你沒本事」
哪一招在送錢 / 跟單有沒有賺	`analyze`(讀【各策略體檢】【跟單成績單】)	per-tag 只有描述統計,不可說某招「有優勢」
一次看完整體檢	`analyze <檔案> --full --equity <本金>`	主報告 + 時間趨勢 + 風險情境,警語自動附上
這老師可信嗎(勝率90%…)	`guru-check --win-rate 0.9 --trades N ...`	機率語氣,絕不說「他一定是騙子」;沒 --trades 先要這個數字
這訊息是詐騙嗎 / LINE 對話紀錄	`scan-text "文字"` 或 `--file LINE對話.txt`	序數等級,不轉百分比;「低」≠安全；轉述發言者/時間/原句/理由
老師連續猜對 N 次好神	`survivorship --traders 1000 --streak N`	是對「現象」的數學解釋,非對特定人的指控
這是他的月報酬,是不是假的	`forensics 0.02,0.03,... [--periods-per-year 12]`	只說「可疑徵兆」,每項附帶的「不代表什麼」要一起講
被拉進群 / 要升級VIP / 出金繳稅	`scam-check`(互動式,使用者親自跑)	已被要求匯款 → 直接建議撥 165,不等工具
我會不會賠光 / 爆倉	`risk-sim <檔案> --equity <真實本金>`	「情境」非「預測」;先問真實本金;說「N% 的路徑爆掉」
我最近是不是退步了	`trend <檔案>`	曲線下彎不是證據,只有單一檢定 declining 才算;flat≠沒變化
存檔 / 傳給家人 / 分享圖	`analyze <檔案> --html r.html --card c.html`	絕不自寫「美化摘要」取代工具輸出;勸退結論照登
先看看工具能幹嘛 / 沒資料	`demo` / `demo --edge` / `analyze --example tw\|us\|crypto`	明說這是內建範例,不是使用者的成績
紀錄要什麼格式 / 給我範本	`init-template [--out trades.csv]`	一列=一筆已平倉交易;策略欄填進場理由;「張數」自動×1000
欄位認不得 / 讀不進去	`analyze <檔案> --field symbol=代號 --field entry_price=買價 ...`	先讓自動辨識試一次;.xlsx 需 openpyxl
存成 JSON / 程式化處理	`analyze <檔案> --json out.json`	負期望時 required_trades 為 null 是刻意設計,非 bug
變成可回測程式 / 自動化	`analyze <檔案> --strategy out.py [--framework ...]`	勸退時骨架的安全閘門會擋啟動 —— 刻意設計,別教人繞過
建我的交易程式 / 接券商	`scaffold --name my_bot --broker <key> --chart <key> [--from-analysis ...]`	產出是待填框架,預設紙上模擬;建議帶 --from-analysis
有哪些券商/圖表可選	`brokers` / `charts` / `chart-preview`	清單以指令即時輸出為準,不憑記憶列舉
幫我用真錢下單 / 填 API key / 關閘門	(無指令 — 婉拒)	紅線:可協助寫程式與解釋機制,絕不代執行、代填金鑰、代解閘門
我有券商/圖表截圖，幫我抓點位與技術	`scan-screenshot <圖片>`；已有 OCR 文字用 `--text`	低信心不自動填；技術詞只算文字線索；單張截圖不能驗證績效
老師給我看績效截圖	先 `scan-screenshot`;依素材:報酬序列→`forensics`;宣稱數字→`guru-check`;連勝→`survivorship`	截圖是倖存者偏差的載體;沒有完整連續紀錄,任何工具都無法驗證

通用誠實紀律(跨指令紅線)

機率語氣,不定罪:所有反詐工具只回答「在無能力假設下多容易靠運氣發生」。
序數不轉百分比:風險等級是極高/高/中/低,絕不說「87% 是詐騙」。
情境非預測:risk-sim 的數字是「如果未來像過去」,不是未來。
描述統計不認證:per-tag 與 trend 的分期(月/季)數字不可講成「有優勢/顯著」。
勸退不軟化:gambling / luck_suspected 的結論照實轉述。
🛡 反詐提醒必轉達:使用者可能正被收割而不自知。
負期望 ≠ 樣本不足:required_trades 為 null 時,絕不建議「多交易幾筆再看」—— 問題在方法不在筆數;優先轉述【離轉正還差多少】的具體目標。
不自行美化:不另寫摘要或圖卡取代工具輸出(會繞過內建的誠實措辭)。
範例要標明:demo / --example 的結果必須說是內建範例。
真錢紅線:不代下單、不代填金鑰、不代解安全閘門。
截圖一定覆核:OCR 信心只是文字抽取規則分數，不是正確率；正負號、小數點、方向、張/股/口都要對原圖。
適合度不靠問卷認證:fit-check 必須讀完整連續交易紀錄；即使樣本內與樣本外都通過，也只可說「考慮極小額驗證」。

analyze 主流程

bash

python -m core.cli analyze <檔案> \
    [--market tw_stock|tw_etf|tw_futures|tw_options|us_stock|crypto|forex] \
    [--field 標準名=欄名 ...] [--full --equity 本金] \
    [--json out.json] [--strategy out.py --framework backtrader|vectorbt|generic] \
    [--html 報告.html] [--card 圖卡.html] [--example tw|us|crypto] [--bootstrap N]

--market 通常可省略 —— 工具會從標的代號自動推斷市場(混合市場的紀錄就該省略);只在「整份紀錄同屬一個市場且自動推斷有誤」時才指定。

五種裁決等級:

等級	意義	勸退
`gambling`	樣本期望值為負 —— 若方法不變,長期繼續的統計預期是虧損	✅ 強烈勸退
`insufficient`	樣本太少(<30),無法區分本事與運氣	✅ 勸阻重押
`luck_suspected`	帳面賺錢,但統計上無法排除是運氣	✅ 高度存疑
`fragile_edge`	有統計訊號但結構脆弱	✅ 謹慎
`statistical_edge`	樣本內通過顯著性檢定(樣本外另行報告,未綁入此等級)	❌(仍非保證)

報告結尾的樣本外措辭有三種,必須區分轉述:

✅「樣本外驗證顯示優勢延續」→ 相對強的證據(仍非保證)。
🟡「樣本外驗證尚未確認」→ 絕不可說「通過所有驗證」;要講「樣本內的優勢不等於未來,先確認延續再加碼」。
連樣本內都沒過 → 依裁決等級轉述。

Exit code 通則:分析/反詐/風險類指令高風險一律回 2 (analyze=勸退、scan-text/scam-check=高風險、guru-check=宣稱不可信、 forensics=可疑、risk-sim=爆倉路徑>10%),錯誤回 1,其餘 0。可用它快速判斷嚴重度,但轉述仍以報告文字為準。

風險與趨勢(risk-sim / trend)

risk-sim:risk-sim <檔案> --equity <真實本金> [--future-trades 200 --paths 5000]

執行前先問使用者真實本金:未給 --equity 時工具用「單筆最大虧損×20」粗估, 爆倉比例對本金假設極度敏感,報告會醒目標示「工具粗估」。
必轉達「尾端低估」:樣本裡沒出現過的大虧抽不到,真實風險可能更高 (選擇權賣方尤其如此)。<10 筆會拒算。

trend:trend <檔案>

分月彙總 / 權益曲線 / 滾動期望值都是描述統計;唯一可下結論的是「早期 vs 近期」的單一檢定(用報酬率非金額,避免部位變大被誤讀)。
declining=顯著退步(值得警覺)、improving=顯著進步(非未來保證)、 flat=「看不出變化」不等於「沒有變化」。<30 筆時誠實說無法判斷。

Show full SKILL.md (192 more words)Show less

反詐四件套速查

scan-text:支援簡體話術(「保证获利」也抓得到)、Big5 檔自動回退。可解析 LINE 匯出標頭，並只組合同一發言者、同日、10 分鐘內的拆句；跨平台首選 scan-text --file LINE對話.txt;管線輸入 POSIX 用 cat 對話.txt | ... scan-text,PowerShell 用 Get-Content 對話.txt | ... scan-text。
scan-screenshot:圖片 OCR 為可選功能(Pillow + pytesseract，系統另需 Tesseract 與繁中字庫)；沒有 OCR 時可用手機複製圖片文字後傳 --text。只有高信心且無衝突的欄位可預填，仍需人工覆核；lot/share/contract 單位不可混寫，百分比損益不可當金額 pnl；數量沒有股/張/口/幣單位時不得預填。任何 OCR 結果都必須人工逐欄覆核。突破/均線/RSI/MACD 等只標成文字線索，不認證策略。
record / direct pnl:必須明示帳戶結算幣別，且為已扣手續費/稅/滑價的淨損益；不同幣別不得相加，direct pnl 不再自動估費、推測幣別或重複扣費。方向未知可留白；只有用價差推算時才必須明示做多/做空。模糊的 realized_pnl/已實現損益 欄需改成明示淨額的欄名，或用 --field pnl=... 親自確認。
guru-check:對長期上漲標的(如美股大盤)把 --null-win-prob 調高至 0.55~0.62,避免對多頭市場過度嚴苛 —— 連工具的保守都要誠實。
forensics:先問資料是月報酬(--periods-per-year 12)還是日報酬(252), 給錯會算出錯誤的年化夏普。不用班佛定律(報酬有負數、不跨數量級, 前提不成立 —— 見 docs/methodology.md「我們刻意不做的事」)。
survivorship:精確解析解(模型計算,非實證資料)。兩個「不同事件」別混講: 1000 人各猜 10 次,「至少一人 10 全對」= 62.4%(--trials 10); 1000 人各猜 20 次,「至少一人出現 10 連對」= 99.7%(CLI 預設 --trials 20)。引用數字必須連參數與事件定義一起講,且說「有 X% 機率出現」,不說「必然存在」。

scaffold(建立個人交易程式)

流程:chart-preview 挑圖表樣式 → brokers / charts 看選項 → scaffold --name my_bot --broker <key> --chart <key> --symbols "..." [--from-analysis trades.csv] → cd my_bot && pip install -r requirements.txt && python main.py(紙上模擬)。

產出自包含(內含 broker_lib.py),不依賴本體即可執行。
券商 14 種選項(含 PaperBroker；台股:永豐/元大/富邦/凱基/群益等; 美股:IBKR/Alpaca/Tradier;加密:Binance/Pionex/OKX/Bybit/ccxt),真實券商為待填框架;Pionex 官方現貨規格未列 sandbox,必須先用 PaperBroker;台灣券商 API 多需臨櫃簽署與數個工作天審核。
四層安全:預設 PaperBroker、真實下單需雙重明確確認；設定檔只有在樣本外延續、幣別與風險基準皆可靠，且 stage=tiny_live_validation 時才可能開啟 live 旗標，其餘情況一律禁用；生成的歷史/示範 replay 偵測到 live broker 會硬退出。

資料與環境備註

支援市場:台股(張數自動×1000)、台股ETF、台指期/選擇權(契約乘數自動, 乘數未知會拒估成本)、美股、加密貨幣、外匯。
欄位中英文自動辨識;# 開頭列視為註解。
Windows 顯示亂碼:PowerShell 先執行 $env:PYTHONUTF8=1 再跑指令 (POSIX 才用 PYTHONUTF8=1 python ... 前綴)。stdin/stdout 編碼已自動處理, 遇亂碼先試環境變數,不要懷疑資料壞掉。
程式化使用:from core.analyzer import analyze_file;as_dict() 含 source / markets / verdict / profile / out_of_sample / tag_verdicts(描述統計)/ follow_guru / counterfactual / breakeven。CLI 同時帶 --full --json 時, JSON 另含 full_extras(trend / risk_scenario / 略過原因)。
核心零依賴;.xlsx 需 openpyxl;跑回測骨架需 backtrader 或 vectorbt。

資料隱私與統計解讀邊界

直接使用 CLI 分析時，資料留在本機；若改用雲端 AI 協助，檔案內容或工具輸出可能會送至該提供者。
送出前請遮蔽姓名、帳號、訂單編號與其他可識別資訊。
有被拒列或尚未釐清的精確重複列時，不得宣稱存在正向優勢，也不得據此判定適合實盤。
p 值不等於「不是運氣」的證明；統計顯著也不能單獨證明未來可重複。

免責

本技能為統計分析與教育工具,輸出不構成投資建議。投資有風險,盈虧自負。過去績效不代表未來表現。

Files

Just SKILL.md in .agents/skills/anti-gambling-trader of mars-tw/anti-gambling-trader-tw.

Open the folder on GitHubat commit 8609cef

Compare with similar skills

Anti Gambling Trader next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Anti Gambling Trader compared with similar skills
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Works with

Questions about Anti Gambling Trader

What does Anti Gambling Trader do?

When should I use Anti Gambling Trader?

Anti Gambling Trader fits situations like: tasks that involve Trading and backtesting; tasks that involve Excel spreadsheets; tasks that involve Stock and market analysis.

How do I install Anti Gambling Trader in Claude Code?

Run `npx skills add mars-tw/anti-gambling-trader-tw --skill anti-gambling-trader -a claude-code`. Or copy the skill folder (.agents/skills/anti-gambling-trader in mars-tw/anti-gambling-trader-tw) into .claude/skills/anti-gambling-trader in your project. Claude Code loads it when a task matches its description.

How do I install Anti Gambling Trader in Codex?

Run `npx skills add mars-tw/anti-gambling-trader-tw --skill anti-gambling-trader -a codex`. Or copy the skill folder (.agents/skills/anti-gambling-trader in mars-tw/anti-gambling-trader-tw) into .agents/skills/anti-gambling-trader in your project. Codex loads it when a task matches its description.

Can I use Anti Gambling Trader in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add mars-tw/anti-gambling-trader-tw --skill anti-gambling-trader -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/anti-gambling-trader, .gemini/skills/anti-gambling-trader, .github/skills/anti-gambling-trader and .opencode/skills/anti-gambling-trader in your project.

What does Anti Gambling Trader need to run?

Going by SKILL.md and its folder, Anti Gambling Trader needs the command-line tools its instructions call (python). Our summary lists: Python 3.

Does Anti Gambling Trader access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Anti Gambling Trader safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Anti Gambling Trader use?

Anti Gambling Trader is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Anti Gambling Trader use?

About 1.9k tokens (SKILL.md is roughly 7.5k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Anti Gambling Trader?

Skills that share tags, products or a category with Anti Gambling Trader: Data Update (Sixian-Li/plain-backtest, 204 stars), Stock Market Analysis (qusong0627/QuantMind, 1.7k stars), Instrument Data To Allotrope (aws-samples/amazon-bedrock-agents-healthcare-lifesciences, 274 stars) and XLSX Spreadsheet Toolkit (XiaomiMiMo/MiMo-Code, 14k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Anti Gambling Trader?

mars-tw (a GitHub user) maintains it in mars-tw/anti-gambling-trader-tw, which has 907 GitHub stars. The repository was last updated on October 9, 2026.

Source: mars-tw/anti-gambling-trader-tw on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.

Install Anti Gambling Trader

Facts

At a glance

What it does

When your agent uses it

Example prompts

Requirements

Workflow steps

What it can do on your machine

Tool permissions

Runs code

Network

Credentials

Context cost

Safety

SKILL.md

反詐投資王 — Anti-Gambling Trader

意圖路由表(第一查找點)

通用誠實紀律(跨指令紅線)

analyze 主流程

風險與趨勢(risk-sim / trend)

反詐四件套速查

scaffold(建立個人交易程式)

資料與環境備註

資料隱私與統計解讀邊界

免責

Files

Compare with similar skills

Similar skills

Data Update

Stock Market Analysis

Instrument Data To Allotrope

XLSX Spreadsheet Toolkit

Excel Spreadsheet Builder

CSV and Excel Merger

Related

Questions about Anti Gambling Trader