trade-journal

trade-journal is a skill for Claude Code, Codex from HKUDS/Vibe-Trading. It costs 64 tokens per session (2,277 once invoked), scanned A, original, MIT.

A trade-journal analyzer for CSV or Excel broker exports. It summarizes trading results and looks for four common behavior patterns: selling winners too early, trading too often, chasing momentum, and relying too heavily on an earlier price.

In plain words
What is it for?
Use it to calculate holding time, frequency, win rate, profit and loss, drawdown, and symbol distribution, then inspect behavioral diagnostics.
Why use it?
It turns a transaction history into evidence about trading habits instead of relying on memory or impressions. It can handle several broker formats and generic files with common trade columns.

Skill for Claude CodeCodex

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

Good fit Use it to calculate holding time, frequency, win rate, profit and loss, drawdown, and symbol distribution, then inspect behavioral diagnostics.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/hkuds/vibe-trading/trade-journal
About the project

Vibe-Trading is a personal trading agent that gives an AI system tools for market analysis, algorithmic trading, backtesting, and related workflows. It is for users who want an agent to research and evaluate trading strategies or manage simulated and other trading activities. The catalogue contains skills that expose these trading capabilities to compatible agents.

HKUDS/Vibe-Trading · 33,177 stars · on GitHub · vibetrading.wiki

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 HKUDS/Vibe-Trading --skill trade-journal
Clone the repo
git clone --depth 1 https://github.com/HKUDS/Vibe-Trading

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 trade-journal

README.md
[![agentmods](https://agentmods.dev/badge/skills/hkuds/vibe-trading/trade-journal/github.svg)](https://agentmods.dev/skills/hkuds/vibe-trading/trade-journal)
Your own site
<a href="https://agentmods.dev/skills/hkuds/vibe-trading/trade-journal"><img src="https://agentmods.dev/badge/skills/hkuds/vibe-trading/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.

agentmods 80×15 button for trade-journal

Your own site · 80×15
<a href="https://agentmods.dev/skills/hkuds/vibe-trading/trade-journal"><img src="https://agentmods.dev/badge/skills/hkuds/vibe-trading/trade-journal.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 64 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,277 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. ✓ AI security review Fable 5.1 · 6 Sept 2026 📄 Read the review Third-party audits
  • Snyk pass 7 Sept 2026
  • 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 $0.00064 $0.02277
Opus 5 $0.00032 $0.01138
Sonnet 5 $0.00013 $0.00455
Haiku 4.5 $0.00006 $0.00228

Measured 8d ago against content hash 183774bbcaa5, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

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 8d 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.

Origin

Copies of this mod

1 near-identical copy found in the catalogue:

agent/src/skills/trade-journal/SKILL.md · 214 lines

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 only
  • strategy — 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}, ...]
  }
}

Read the full file on GitHub · 214 lines

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. 8d ago First seen · 214 lines · 64 tokens per session scan A 183774bbcaa5

Subscribe to this mod's changes

trade-journal is a skill published in the GitHub repository HKUDS/Vibe-Trading (33,177 stars, last pushed yesterday), 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. 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

hyperliquid

Use when backtesting, deploying, checking funding readiness, or debugging a Hyperliquid strategy through Superior Trade Unified API — writing Freqtrade configs and strategy code, running sweeps, checking managed-wallet balances, trading HIP-3 perps, or diagnosing a deployment that will not start or trade.

Superior-Trade/superior-skills · 64 tokens

polymarket

Use when the user wants to trade, research, or backtest Polymarket prediction markets through Superior Trade — finding markets by slug or event URL, placing a single immediate market order, writing NautilusTrader strategies, running filled-data backtests, funding pUSD, or deploying and monitoring a live Polymarket…

Superior-Trade/superior-skills · 68 tokens

aerodrome

Use when creating, validating, backtesting, deploying, sizing, or troubleshooting Aerodrome/Base spot trading strategies through the Superior Trade API, especially Freqtrade configs using exchange.name "aerodrome", AERO/USDC or CHECK/USDC pairs, AMM market swaps, wallet/gas balance checks, no-orderbook pricing, or…

Superior-Trade/superior-skills · 83 tokens

backtesting

Use when running, interpreting, or designing backtests on Superior Trade — anything about backtest windows, trade-count thresholds, exit-reason mix, parameter sweeps, walk-forward validation, zero-trade diagnosis, compute-cost estimation, or "is this backtest result trustworthy?". Pair with the relevant strategy…

Superior-Trade/superior-skills · 73 tokens

basis-arb

Use when the user asks for spot-perp basis trade, basis arbitrage, cash-and-carry, perp discount, or any setup that reads the spot–perp basis as a positioning signal. Long-perp leg only — pure two-leg basis arb requires a paired spot short (or long) which Freqtrade can't run cleanly. The strategy below captures the…

Superior-Trade/superior-skills · 87 tokens

fees-optimizations

Use when the user asks about fees, fee optimization, slippage, maker vs taker, post-only or ALO orders, fee tiers, builder code fees, effective spread, order pricing, lowering trading costs, or why a live Hyperliquid Freqtrade strategy underperforms its backtest. Also use proactively for high-turnover designs (5m or…

Superior-Trade/superior-skills · 94 tokens