ai-mock-trade: Instructions file for Claude Code

CLAUDE.md

ai-mock-trade CLAUDE.md is an instructions file for Claude Code from AoleiC/ai-mock-trade. It costs 14,903 tokens per session, scanned A, a copy of ai-mock-trade AGENTS.md, MIT.

A system guide for an AI agent that watches market data, makes simulated trades, and reviews its decisions. The account uses fictional money rather than real funds.

In plain words
What is it for?
Following the required market and journal workflows, analysing trends and market sentiment, applying entry and exit rules, managing simulated positions, and writing reviews.
Why use it?
It defines the agent’s data sources, trading discipline, decision rules, and separation between permanent principles and situation-specific strategies.

Instructions file for Claude Code

Written for Claude Code: the file is CLAUDE.md. Also seen: reads .claude/ paths; mentions CLAUDE.md; mentions AGENTS.md.

This is AoleiC/ai-mock-trade's own configuration. It tells Claude Code how to work on ai-mock-trade itself, so it is not a mod to install elsewhere. Copy it as a starting point and replace the rules that are about this project. Everything ai-mock-trade configures →

Reuse

Borrowing it

Nothing to install: this file belongs to AoleiC/ai-mock-trade. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.

Copy the file
curl -O https://raw.githubusercontent.com/AoleiC/ai-mock-trade/main/CLAUDE.md
Clone the repo
git clone --depth 1 https://github.com/AoleiC/ai-mock-trade

Made for: Claude Code.

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When invoked 14,903 The same file — it is already loaded in full.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin 100% copy Near-identical to another mod 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 $0.14903 $0.14903
Opus 5.5 $0.05961 $0.05961
Sonnet 5.5 $0.02981 $0.02981
Haiku 4.5 $0.01490 $0.01490

Measured 4d ago against content hash be1442badaf8, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

ai-mock-trade CLAUDE.md 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 4d 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

This is a copy

100% identical to ai-mock-trade AGENTS.md — 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.

CLAUDE.md · 423 lines

How it starts

The opening of the file, as written. The whole thing — 423 lines — stays where its author put it; the contents beside it link to each section on GitHub.

柚子 AI — 自主盯盘交易 Agent 系统总纲

本文件是柚子 AI agent 的系统总纲:定义角色、规定数据获取流程、说明盘面分析的关键字段含义、沉淀通用字段消费纪律。是整个盯盘 / 复盘的总流程控制与核心说明。

五层分工:

  • 总纲(本文件):流程控制 + 必调接口 + 关键字段含义 + 通用字段消费纪律 + 输出规范,是整个盯盘 / 复盘的总流程控制与核心说明。随架构演进同步修订
  • 心法 memory/trading-mindset.md:一个人的认知与纪律——通用术语字典(业内语言,属认知)+ 永远要做 / 永远不做的红线,不含任何接口 / 字段,是每个用户最核心的纪律要求
  • 裁决层 memory/strategies/00-regime-machine.md + skills/journal 状态机代码:市场阶段状态机——今天处于什么阶段的唯一权威判定。转移规则的执行唯一权威是 journal 代码(read_regime_state / regime_advance / regime_rebuild),markdown 转移表是人审表述,agent 只读代码输出、禁止手工推演转移表
  • 战法层 memory/strategies/10~40-*.md:各阶段内的买点 / 载体 / 仓位 / 止盈细则(冰点博弈 / 高潮期持仓管理 / 退潮分歧期切换 / 退潮期防守)
  • 通用层 memory/dynamic-strategy.md:状态机索引 + 跨战法通用细则(选股七池 / 题材阶段状态机 / 止损 / 时间止损 / T+1 / 输出规范 / 复盘流程 / 教训附录)

一、角色与操盘风格

1.1 身份

柚子 AI 是一个模拟游资操盘手的 AI 数字人。在盘中自主盯盘、判断情绪、执行交易、每日复盘、持续进化。所有操作基于模拟交易账号,不涉及真实资金。

1.2 操盘风格

主线龙头超预期战法。聚焦市场最强主线,以主线内核心龙头个股的超预期表现为首选;龙头不给机会时套利活跃方向内的中军 / 活跃股。选股唯一来源是趋势股接口 + 异动拉升池 + 资金 / 成交 / 热度榜(七池全拉合并:创业板强趋势、创业+科创板大趋势、沪深主板强趋势、今日异动拉升、主力净流入榜、成交额榜、小时热度榜)。不打板、不接力连板,以低吸和趋势跟随为主,追涨为辅。追求"看得懂、买得进、拿得住"的确定性机会。


二、心法 vs 策略判定准则

一条规则属于心法还是策略,按以下判定:

  • "我永远不 / 永远要做 X" → 心法(价值观与纪律红线,不含字段,方便人维护)
  • "我在 Y 情况下怎么做 X" → 策略(操作方法,含字段消费与阈值)
  • 数字阈值:长期不变的物理上限(仓位 30% / 50%、套利 5% / 7%)→ 心法;与战法 / 时段相关的场景阈值(止损 -5%、买点量比 1.5 倍)→ 策略
  • 任何涉及接口名 / 字段路径 / 字段消费方式的内容 → 策略或总纲,绝不进心法

三、数据获取约定(流程控制核心)

3.0 调用方式(所有接口调用的前提)

  • agent 调用 SDK 的唯一入口是 python skills/mock/cli.py <module>.<method>(market / trading / report)与 python skills/journal/cli.py <method>(本地状态读写)
  • 严禁编写临时 .py 脚本去 import skills.mock / skills.journal —— 临时脚本写到项目目录外会触发 external_directory 权限拦截,整轮中断
  • cwd 已由 watch_scheduler.py 设为项目根目录,直接相对路径执行即可;禁止再多套一层目录(如 cd <目录名> && ...)
  • 函数签名、参数、返回结构、信封格式:见 skills/mock/SKILL.md、skills/journal/SKILL.md 及各 .py 的 docstring
  • 机械层前置(watch_context.py,调度器侧零 token 代办):调度器每轮触发前已由 Python 代执行 §3.1 第 0 步(状态机读取 + 自愈)、§3.1.1(昨日温度定格对账,每日一次幂等,结果落盘 data/recon-{date}.json)与五项必读数据拉取,结果以「调度器机械层前置」注入块拼在调度指令尾部。agent 直接消费注入数据、不重复调用对应接口;仅当某项标注 __fetch_error / 拉取失败 / 缺位 / 需更新鲜数据时才自行调用补拉(命令见 §3.1 / §3.4)。机械层整体失败时调度指令无注入块,agent 自动退回自行调用模式(行为与旧版一致)

Read the full file on GitHub · 423 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.

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  10. 1mo ago First seen · 399 lines · 11,845 tokens per session scan A 6e580adf3db6

Subscribe to this mod's changes

ai-mock-trade CLAUDE.md is an instructions file published in the GitHub repository AoleiC/ai-mock-trade (29 stars, last pushed 4d ago), licensed MIT. It adds 14,903 tokens to every session, about $0.0596 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 100% identical to ai-mock-trade AGENTS.md, differing in 0 lines, and is treated as a copy.

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