Borrowing it
Nothing to install: this file belongs to PatrickSUDO/fadacai-portfolio. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/PatrickSUDO/fadacai-portfolio/main/.agents/skills/trade-journal/SKILL.mdgit clone --depth 1 https://github.com/PatrickSUDO/fadacai-portfolioWrote 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.
[](https://agentmods.dev/skills/patricksudo/fadacai-portfolio/trade-journal)<a href="https://agentmods.dev/skills/patricksudo/fadacai-portfolio/trade-journal"><img src="https://agentmods.dev/badge/skills/patricksudo/fadacai-portfolio/trade-journal/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.
<a href="https://agentmods.dev/skills/patricksudo/fadacai-portfolio/trade-journal"><img src="https://agentmods.dev/badge/skills/patricksudo/fadacai-portfolio/trade-journal.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium Excessive Agency · line 5 Skill selects an external model or provider that may use a different account or billing plan than the operator expects. Undisclosed model switches can cause unexpected cost or quota consumption.Fix: Remove the model/provider override or disclose it prominently and require explicit operator approval before invoking an external coding CLI or billed model.
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 | $0.00036 | $0.01871 |
| Opus 5 | $0.00018 | $0.00936 |
| Sonnet 5 | $0.00007 | $0.00374 |
| Haiku 4.5 | $0.00004 | $0.00187 |
Grade A, and why
trade-journal 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 11d ago.
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.
How it starts
The opening of the file, as written. The whole thing — 175 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Trade Journal
Track trades and compare execution against the investment plan.
Arguments
/trade-journal log— Record a new trade (manual or auto-detect from position changes)/trade-journal review— Show recent trades and compare to plan/trade-journal summary— Monthly P&L summary/trade-journal auto— 只做倉位變動偵測(不需手動輸入)
Step 0: 配置同步 & 倉位偵測
0a. 每次必做
- 讀取
plan.md— 掌握計畫中的待辦操作,用於判斷交易是否「按計畫執行」 - 讀取
feedback/*.md— 套用交易風格偏好
0b. 倉位取得與 journal 判斷(auto 例外)
- 若 action 是
auto→ 無論今天是否已偵測,都重新執行完整偵測(這是 auto 的主要功能) - 若 action 是
log/review/summary:- 呼叫
mcp__firstrade-server__get_account_position取得即時持倉 - 檢查
journal/YYYY-MM-DD.md(今天日期)是否已存在 - 若已存在 → 跳過偵測,使用即時持倉進入主流程
- 若不存在 → 執行完整偵測(見下方 Auto-Detect)
- 呼叫
Workflow
Auto-Detect(完整偵測流程)
倉位變動自動偵測(後減前):
-
呼叫
mcp__firstrade-server__get_account_position取得即時持倉(後 = 最新倉位) -
找到
journal/目錄下最新的.md檔案(前 = 上次快照) -
解析「前」檔案的倉位表格:
- 現股:從「現股持倉」或 Stocks 表格提取 {ticker: quantity}
- 選擇權:從「選擇權持倉」或 Options 表格提取 {contract: quantity}
-
解析「後」(即時持倉)的倉位表格:同上
-
比較差異:
股票:
for each ticker in 後: if ticker not in 前 → 「🆕 新建倉:{ticker} {qty} 股」 if ticker in 前 and qty changed → 「📈 加碼 / 📉 減碼:{ticker} {前qty} → {後qty}」 for each ticker in 前: if ticker not in 後 → 「🔴 已清倉:{ticker} {前qty} 股」選擇權:
比較合約名稱(Symbol + Strike + Expiry + Type) 新合約 → 「🆕 新開倉」 消失的合約 → 「🔴 已平倉/到期」 數量變化 → 「加減倉」 -
輸出偵測結果給用戶確認:
## ⚡ 自動偵測到的倉位變動(vs 上次快照 YYYY-MM-DD) | 類型 | 操作 | 標的 | 變化 | 計畫對應 | |------|------|------|------|----------| | 股票 | 🆕 新建倉 | DDOG | 57 股 | ✅ SaaS建倉計畫 #1 | | 股票 | 🔴 清倉 | DY | 18 股 | ❓ 非計畫操作 | -
計畫對應:比對
plan.md的待辦清單- 如果交易匹配計畫中的操作 → 標記 ✅ 並引用計畫編號
- 如果是計畫外操作 → 標記 ❓ 提醒用戶記錄原因
Log a Trade
- 如果 auto-detect 已偵測到變動 → 以偵測結果為基礎,詢問用戶補充:
- 交易價格(auto-detect 無法得知)
- 交易原因
- 是否按計畫執行
- 如果用戶手動提供交易資訊 → 直接記錄
- 建立/更新檔案:
journal/YYYY-MM-DD.md
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.
- 11d ago First seen · 175 lines · 36 tokens per session scan A ab3ea1be7283
trade-journal is a skill published in the GitHub repository PatrickSUDO/fadacai-portfolio (139 stars, last pushed 2d ago), licensed MIT. It adds 36 tokens to every session and 1,871 once invoked, about $0.0002 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 2026-08-30.
Other skills, from other repositories
sector-rotation
An analysis framework for comparing industries in the Chinese A-share stock market, using business conditions, price momentum, valuation, and money flows. It produces rankings and higher- or lower-allocation suggestions.
strategy-pivot-designer
Detect backtest iteration stagnation and generate structurally different strategy pivot proposals when parameter tuning reaches a local optimum.
twitter-reader
Read Twitter/X for financial research using opencli (read-only). Use this skill whenever the user wants to read their Twitter feed, search for financial tweets, view bookmarks, look up user profiles, or gather market sentiment from Twitter/X. Triggers include: "check my feed", "search Twitter for", "show my…
chenhao-limit-up
A framework for judging Chinese A-share stocks that have reached the daily price-rise limit, using market mood, sector leadership, and trading momentum.
trading-risk-gate
Unified pre-trade safety gate: Ruin check (Law #1), ergodicity audit, and win-rate dominance validation. Absorbs: ergodicity-check, law-of-ruin, win-rate-dominance.
furusato
A Japanese hometown-tax donation manager for furusato nozei, a system where donations to municipalities can qualify for an income-tax or local-tax deduction. It reads donation receipts, stores donation records, and calculates deduction limits.