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.
npx skills add skloxo/TideTrading --skill trade-journalgit clone --depth 1 https://github.com/skloxo/TideTradingWrote 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/skloxo/tidetrading/trade-journal)<a href="https://agentmods.dev/skills/skloxo/tidetrading/trade-journal"><img src="https://agentmods.dev/badge/skills/skloxo/tidetrading/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/skloxo/tidetrading/trade-journal"><img src="https://agentmods.dev/badge/skills/skloxo/tidetrading/trade-journal.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00064 | $0.02277 |
| Opus 5 | $0.00032 | $0.01138 |
| Sonnet 5 | $0.00013 | $0.00455 |
| Haiku 4.5 | $0.00006 | $0.00228 |
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 7d 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.
This is a copy
100% identical to trade-journal — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 214 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Trade Journal Analysis
Purpose
Users upload broker exports (交割单) and get an honest, data-grounded portrait of their own trading. Two layers are live:
- Profile — holding days, frequency, win rate, PnL ratio, cumulative PnL, max drawdown, top symbols, market/hourly distribution.
- Behavior diagnostics — 4 biases, each with severity (low/medium/high) and numeric evidence: disposition effect, overtrading, chasing momentum, anchoring.
Strategy extraction → backtest bridge lands in Phase 4c.
Supported formats (auto-detected):
- 同花顺 (Tonghuashun) — A-share CSV, typically GBK-encoded
- 东方财富 (Eastmoney) — A-share CSV, typically GBK-encoded
- 富途 (Futu) — HK/US CSV, UTF-8
- Generic — any CSV with columns like
datetime/symbol/side/qty/price
Usage
Call the analyze_trade_journal tool directly. Never run Python from bash.
analyze_trade_journal(file_path="uploads/xxx.csv")
analyze_trade_journal(file_path="uploads/xxx.csv", analysis_type="profile")
analyze_trade_journal(file_path="uploads/xxx.csv", filter_expr="2026-01 to 2026-03")
analyze_trade_journal(file_path="uploads/xxx.csv", filter_expr="symbol=600519.SH")
analyze_trade_journal(file_path="uploads/xxx.csv", filter_expr="market=china_a")
analysis_type:
full(default) — profile + behavior (strategy still placeholder)profile— profile metrics only (fastest)behavior— 4 behavior diagnostics onlystrategy— Phase 4c placeholder
filter_expr (optional):
- Date range:
"YYYY-MM to YYYY-MM"or"YYYY-MM-DD to YYYY-MM-DD" - Symbol:
"symbol=600519.SH"(exact match on qualified symbol) - Market:
"market=china_a|us|hk|crypto"
Return shape (profile subset)
{
"status": "ok",
"file": "xxx.csv",
"format_detected": "tonghuashun",
"total_records": 326,
"date_range": "2026-01-06 ~ 2026-03-28",
"symbols_count": 42,
"market": "china_a",
"profile": {
"total_trades": 326,
"total_roundtrips": 118,
"avg_holding_days": 3.2,
"trade_frequency_per_week": 4.1,
"win_rate": 0.48,
"profit_loss_ratio": 1.35,
"total_pnl": 18240.55,
"max_drawdown": -9820.10,
"top_symbols": [{"symbol": "600519.SH", "trades": 14, "total_amount": 1.02e6}, ...],
"market_distribution": {"china_a": 326},
"hourly_distribution": {9: 52, 10: 84, ...},
"roundtrips_sample": [{"symbol": "600519.SH", "buy_dt": "...", "sell_dt": "...", "pnl": 3400.1, "pnl_pct": 0.021, "hold_days": 2.5}, ...]
}
}
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.
- 7d ago First seen · 214 lines · 64 tokens per session scan A 183774bbcaa5
trade-journal is a skill published in the GitHub repository skloxo/TideTrading (10 stars, last pushed 4d ago), licensed MIT. It adds 64 tokens to every session and 2,277 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to trade-journal, differing in 0 lines, and is treated as a copy.
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