trade-journal

trade-journal is a skill for Claude Code, Codex from ZICXR/A-Stock-Skills. It costs 98 tokens per session (716 once invoked), scanned A, original, MIT.

A trading journal that records AI trading signals, real trades, and the results after 30 days.

In plain words
What is it for?
Use it to log AI suggestions, record purchases, review trades after 30 days, and calculate results such as win rate, average return, and performance against the CSI 300 index.
Why use it?
It replaces memory and guesswork with a record of what the AI recommended and what actually happened. After enough entries, you can measure how often its recommendations were right.

Skill for Claude CodeCodex

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

Good fit Use it to log AI suggestions, record purchases, review trades after 30 days, and calculate results such as win rate, average return, and performance against the CSI 300 index.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/zicxr/a-stock-skills/trade-journal
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 ZICXR/A-Stock-Skills --skill trade-journal
Clone the repo
git clone --depth 1 https://github.com/ZICXR/A-Stock-Skills

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/zicxr/a-stock-skills/trade-journal/github.svg)](https://agentmods.dev/skills/zicxr/a-stock-skills/trade-journal)
Your own site
<a href="https://agentmods.dev/skills/zicxr/a-stock-skills/trade-journal"><img src="https://agentmods.dev/badge/skills/zicxr/a-stock-skills/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/zicxr/a-stock-skills/trade-journal"><img src="https://agentmods.dev/badge/skills/zicxr/a-stock-skills/trade-journal.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 98 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 716 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.
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 $0.00098 $0.00716
Opus 5 $0.00049 $0.00358
Sonnet 5 $0.00020 $0.00143
Haiku 4.5 $0.00010 $0.00072

Measured 12d ago against content hash d00ad91ebd98, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, 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 12d ago.

The scan reads SKILL.md. This mod also ships 1 executable file (main.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.

skills/02-data-collection/trade-journal/SKILL.md · 94 lines

What it actually says

trade-journal: AI vs 实盘 复盘

何时使用

  • 用户做了交易,想记录"AI 当时怎么说"
  • 周/月复盘,看 AI 推荐准不准
  • 想积累历史数据,看"AI 推荐的 4 只,30 天后涨跌幅 vs 沪深 300"

核心理念

AI 信号 → 记录 → 30 天后比对 → 算胜率
                                    ↓
                          3 个月后知道 AI 准不准

快速使用

1. 记录 AI 建议

python main.py record --code 601991 --signal "MACD金叉+站上MA20" --action buy --target_price 3.50

输出 journal/2026-06-22.md:

## 2026-06-22 14:30
- 代码: 601991 大唐发电
- AI 信号: MACD金叉+站上MA20
- 建议操作: buy
- 目标价: 3.50 (+9%)
- 当前价: 3.20

2. 记录实盘

python main.py fill --code 601991 --price 3.21 --shares 6200

3. 30 天后比对

python main.py review

输出:

📊 30 天复盘
| 代码 | AI 建议 | 实盘买入 | 30 天后 | 盈亏 | AI 准? |
|------|---------|---------|--------|------|--------|
| 601991 | 3.20 | 3.21 | 3.85 | +19.9% | ✅ 准 |

4. AI 胜率统计

python main.py stats

输出:

🎯 AI 信号胜率 (近 90 天)
- 总推荐: 24 次
- 命中 (涨幅>5%): 14 次
- 胜率: 58.3%
- 平均收益: +4.2%
- vs 沪深 300: +1.8%

数据格式

journal/ 目录:

journal/
├── 2026-06-22.md      # 每日记录
├── 2026-06-23.md
└── _stats.json         # 自动统计

哲学

AI 不可信, 除非它愿意被复盘

这个 Skill 是 A-Stock-Skills 的"问责机制"。 不积跬步无以至千里, 跑 3 个月您就知道 AI 准不准。

Files

What ships with it

2 files 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. 12d ago First seen · 94 lines · 98 tokens per session scan A d00ad91ebd98

Subscribe to this mod's changes

trade-journal is a skill published in the GitHub repository ZICXR/A-Stock-Skills (25 stars, last pushed 2mo ago), licensed MIT. It adds 98 tokens to every session and 716 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 2026-08-30.