chan-crypto-trader
Provides Chan-theory market structure analysis with decision-only outputs for cryptocurrency trading.
Install
mkdir -p .claude/skills/chan-crypto-trader && curl -L -o skill.zip "https://agentskills.codes/api/skills/download/13657" && unzip -o skill.zip -d .claude/skills/chan-crypto-trader && rm skill.zipInstalls to .claude/skills/chan-crypto-trader
Activation
This is the description your AI agent reads to decide when to run this skill — the better it matches your request, the more reliably it fires.
Use when Codex needs Chan-theory-based cryptocurrency structure analysis for requests involving 缠论, 分型, 笔, 线段, 中枢, 背驰, 区间套, or 三类买卖点; require decision-only outputs in strict JSON plus concise Chinese conclusion, prioritize conservative confirmation logic, and never auto-place orders.Key capabilities
- →Validate input fields and K-line completeness.
- →Process K-line inclusions for main and sub levels.
- →Identify pivots and generate segments.
- →Determine trend types and central structures.
- →Generate buy/sell point candidates based on Chan theory rules.
How it works
The skill performs Chan-theory-based cryptocurrency market structure analysis by validating data, processing K-line inclusions, identifying pivots and segments, determining trend types, and generating buy/sell point candidates.
Inputs & outputs
When to use chan-crypto-trader
- →Identify trend types and market phases
- →Locate buy/sell points via interval nesting
- →Validate market structure with multi-level K-line data
About this skill
Chan Crypto Trader
Overview
执行基于缠论的加密市场结构分析,输出可执行但不自动下单的决策建议。 优先给出保守确认型结论,默认高一级别优先,低级别仅做确认或减仓辅助。
Workflow
- 数据校验:校验输入字段和 K 线完整性。缺字段或样本不足(
bars_main < 50或bars_sub < 100)时直接输出data_quality.status="insufficient"。 - K 线包含处理:对主级别和次级别分别执行 K 线包含关系处理(按时间顺序逐根合并,方向由前一根决定)。
- 分型识别与笔生成: a. 识别所有顶分型和底分型,标注分型强度(弱/强/最强)。 b. 按同性质分型筛选规则(连续顶取最高、连续底取最低)过滤。 c. 按笔规则(5 根最低要求、顶底配对)生成笔。
- 线段生成:基于笔提取特征序列,对特征序列做包含处理得到标准特征序列,按两种终结情况(无缺口/有缺口)判定线段终结或延续。
- 走势中枢与走势类型:在主级别识别最近走势中枢,计算
[ZD, ZG]及GG/DD/G/D,判断走势类型(盘整/趋势)和中枢演化状态(延伸/新生/扩展)。 - 中阴阶段判断:判断当前是否处于中阴阶段——若前一走势类型刚完成(背驰或盘整背驰确认终结)且新走势类型未确立,标记
market_state.phase="transitional",借助前中枢进行分析。 - 背驰与区间套:在次级别判断背驰(a+A+b+B+c 模型)或盘整背驰,并通过区间套逐级缩小转折范围。MACD 作为辅助判断。
- 买卖点生成:按三类买卖点规则生成候选信号
B1/B2/B3/S1/S2/S3,每个信号标注结构前提、触发条件和失效条件。 - 级别冲突与风控:应用级别优先规则和保守确认规则,处理主次级别冲突,生成最终
action.decision。 - 输出:输出固定 JSON,并附一段简洁
cn_summary。
Input Contract
必填字段
exchange:交易所,例如binancesymbol:交易对,例如BTC/USDTtimeframe_main:主级别,默认1htimeframe_sub:次级别,默认15mbars_main[]:主级别 K 线数组,每项包含time/open/high/low/closebars_sub[]:次级别 K 线数组,每项包含time/open/high/low/close
可选字段
macd_main[]:主级别 MACD 数据(DIF/DEA/柱值),用于背驰辅助判断macd_sub[]:次级别 MACD 数据
最低数据要求
bars_main[]:至少 50 根 K 线(满足笔→线段→中枢的最低识别需求)。bars_sub[]:至少 100 根 K 线(次级别需要更细粒度结构用于区间套确认)。- 不满足以上要求时,必须输出
data_quality.status="insufficient",不得强行判断买卖点。
执行要求
- 不得在缺少主级别或次级别 K 线时强行判断买卖点。
- 不得在字段不完整时输出高置信度结论。
- MACD 缺失时仍可做纯形态学分析,但置信度上限降低 0.1。
Output Contract
始终输出 JSON,固定字段如下:
{
"exchange": "binance",
"symbol": "BTC/USDT",
"timeframe_main": "1h",
"timeframe_sub": "15m",
"data_quality": {
"status": "ok",
"notes": ""
},
"market_state": {
"trend_type": "up",
"walk_type": "trend",
"phase": "trending",
"zhongshu_count": 2,
"last_zhongshu": {
"zd": 101000.0,
"zg": 103200.0,
"gg": 104500.0,
"dd": 100200.0
},
"current_stroke_dir": "up",
"current_segment_dir": "up"
},
"signals": [
{
"type": "B2",
"level": "sub",
"trigger": "一买后次级别回抽不破关键低点并重新转强",
"invalid_if": "回抽低点跌破一买低点",
"confidence": 0.72
}
],
"action": {
"decision": "hold",
"reason": "主级别未确认转折,次级别仅出现候选二买"
},
"risk": {
"conflict_level": "low",
"notes": "主级别与次级别方向轻微冲突,避免激进加仓"
},
"cn_summary": "当前以观察或轻仓持有为主,等待主级别确认后再执行加仓。"
}
字段规则
market_state.trend_type:up|down|rangemarket_state.walk_type:consolidation|trend(盘整/趋势)market_state.phase:trending|consolidating|transitional(趋势进行中/盘整中/中阴阶段过渡)market_state.zhongshu_count:当前走势中的中枢数量,>= 0整数market_state.last_zhongshu:包含zd/zg/gg/dd四个数值字段market_state.current_stroke_dir:up|down(当前笔方向)market_state.current_segment_dir:up|down(当前线段方向)signals[].type:B1|B2|B3|S1|S2|S3signals[].level:main|subaction.decision:buy|sell|reduce|hold|waitrisk.conflict_level:none|low|highconfidence:0.0-1.0
Decision Policy
执行以下固定优先级:
- 高级别优先于低级别。主级别趋势延续时,低级别反向信号仅用于
reduce或短差,不用于重仓反转。 - 保守确认型:默认优先
B2/B3或S2/S3。B1/S1仅作为候选,不直接给重仓结论,需次级别确认后方可升级动作。 - 同时出现多信号时,以结构完整度和失效条件清晰度更高者优先。
- 中阴阶段处理:
- 中阴阶段内默认
action.decision = "wait",除非中枢震荡给出明确的第三类买卖点。 - 中阴阶段内所有信号的置信度上限为
0.6。 - 中阴阶段结束的标志:新走势类型的第三类买卖点出现。
- 中阴阶段内默认
- 走势类型延伸处理:
- 盘整延伸中:中枢形成后走势不断回到中枢,不产生新中枢 → 按中枢震荡处理,关注 Zn 变化。
- 趋势延伸中:同向走势不断产生新中枢 → 注意每个新中枢形成后的背驰判断(a+A+b+B+c 逐段比较)。
- 走势类型延伸随时可能结束,关键在于是否产生新的走势中枢。
- 同级别分解说明:
- 可选的机械化操作方法:按固定级别分解走势为 A0+A1+A2+...,比较 Ai 与 Ai+2 的力度。
- 适合不区分牛熊、按固定节奏操作的场景。
- 详见
references/chan-core-rules.md第 2.11 节。
Safety Rules
- 仅做分析,不调用交易接口,不自动下单。
- 禁止输出"必涨""必跌""稳赚"等情绪化或确定性承诺。
- 每个信号必须包含
trigger与invalid_if。 - 冲突高时优先
wait或reduce。 - 中阴阶段默认
wait,除非有明确的中枢震荡短差机会。 - 极端波动后(闪崩/暴拉),优先标注
risk.conflict_level = "high"并建议wait。
References
- 核心规则与判定细节:
references/chan-core-rules.md - 输出格式与错误码:
references/signal-output-spec.md
按需加载参考文档,不在主文档重复长篇定义。
When not to use it
- →When the user wants automated order placement.
- →When K-line data is insufficient (bars_main < 50 or bars_sub < 100).
- →When the user expects emotional or certainty-promising outputs like '必涨' or '稳赚'.
Limitations
- →The skill does not call trading interfaces or place orders automatically.
- →The skill requires a minimum of 50 main K-lines and 100 sub K-lines for analysis.
- →The skill's confidence for purely morphological analysis is reduced by 0.1 if MACD data is missing.
How it compares
This skill automates complex Chan-theory analysis for cryptocurrency markets, providing structured decision-only outputs and prioritizing conservative confirmation logic, which is more systematic and less prone to human bias than manual int
Compared to similar skills
chan-crypto-trader side by side with the closest alternatives in the catalog.
| Skill | Installs | Updated | Safety | Difficulty |
|---|---|---|---|---|
| chan-crypto-trader (this skill) | 0 | 5mo | No flags | Advanced |
| trade | 0 | 4mo | No flags | Intermediate |
| quant-analyst | 103 | 2mo | No flags | Advanced |
| stock-analyzer | 71 | 2mo | Review | Beginner |
Try saying
Example prompts that trigger this skill in your AI assistant.
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