Mini Six Ren (小六壬占卜)

Chinese traditional divination system based on the Nine-Palace hand technique. Generate three-pass (三传) predictions and provide AI-powered analysis.

Workflow

Determine input mode (numbers / datetime / Chinese chars / current time)
Run scripts/xiaoliu.py --format json to compute the prediction
Check if config.yaml exists and has a model field:
- No config (default): Display ℹ️ 当前使用 Claude Code 内置模型解读。如需使用第三方模型，请创建 config.yaml。Then use the built-in LLM to analyze the result following the "LLM Analysis" section below.
- Has config + API key: Display ℹ️ 当前使用 <model> 解读。Run scripts/interpret.py with the prediction JSON piped in:
```
uv run scripts/xiaoliu.py --now --question "问题" --format json | \
  uv run scripts/interpret.py --question "问题"
```
- Has config, missing API key: Display ⚠️ 请在 .env 中设置 <ENV_KEY>。Fall back to built-in LLM analysis.
Format the report using assets/template.md

Quick Start

Run the divination script (uv single-file script, no project install needed):

# By three numbers
uv run scripts/xiaoliu.py --numbers 1,2,3 --question "今日运势" --format json

# By date/time (converts to lunar calendar internally)
uv run scripts/xiaoliu.py --datetime "2025-07-15 10:30" --question "面试能成功吗" --format json

# By Chinese characters (uses stroke count)
uv run scripts/xiaoliu.py --chars "天地人" --question "感情运势" --format json

# By current time
uv run scripts/xiaoliu.py --now --question "今天适合出行吗" --format json

Use --format json to get structured output for LLM analysis. Use --format text for human-readable display.

Input Mode Selection

User says	Mode	Example
gives 3 numbers	`--numbers`	`--numbers 3,5,7`
mentions a date/time	`--datetime`	`--datetime "2025-01-31 14:30"`
gives Chinese characters	`--chars`	`--chars "天地人"`
"用现在的时间" / "now"	`--now`	`--now`
no specific input	`--now`	default to current time

LLM Analysis

After getting the JSON prediction result, provide an analysis following this structure. Role-play as a 小六壬占卜大师 with deep traditional culture knowledge.

Analysis structure

卦象总览: Summarize the three passes and their elements
时间发展脉络:
- 初传（前期/当前）: What the first symbol means for this question
- 中传（中期/发展）: How the middle symbol drives change
- 末传（后期/结果）: What the final symbol predicts
五行生克解读: Explain how the element relationships affect the outcome
具体建议: Practical, actionable advice tied to the question
关键提示: Notable directions, timing, or deity influences

Analysis guidelines

Always tie the interpretation to the specific question asked
Prioritize the final pass (末传) as the most important indicator
Explain five-element relationships in terms the user understands
Keep analysis under 800 characters (Chinese) for conciseness
Use elegant, philosophical Chinese language but remain accessible

Report Output

After generating the prediction and LLM analysis, format using assets/template.md. Replace all {{placeholder}} variables with actual values from the script output and LLM analysis.

Third-Party Model Configuration (Optional)

By default, the skill uses Claude Code's built-in LLM for interpretation. To use a third-party model instead:

Step 1: Create `config.yaml`

Create config.yaml in the skill root directory (mini-six-ren/config.yaml):

# 格式: provider:model_name
model: deepseek:deepseek-chat

Format: provider:model_name

Step 2: Set API Key in `.env`

Add your API key to mini-six-ren/.env:

DEEPSEEK_API_KEY=sk-...

Supported Providers

Provider prefix	API Key env var	Notes
`openai`	`OPENAI_API_KEY`	GPT series
`anthropic`	`ANTHROPIC_API_KEY`	Claude series
`google-gla`	`GEMINI_API_KEY`	Gemini series
`deepseek`	`DEEPSEEK_API_KEY`	DeepSeek
`kimi`	`MOONSHOT_API_KEY`	Moonshot Kimi
`qwen`	`DASHSCOPE_API_KEY`	Alibaba Qwen
`glm`	`ZHIPU_API_KEY`	Zhipu ChatGLM

Examples

# DeepSeek
model: deepseek:deepseek-chat

# GPT-4o
# model: openai:gpt-4o

# Qwen
# model: qwen:qwen-plus

To switch back to built-in LLM, simply delete config.yaml.

Reference

For detailed symbol meanings and five-element relationships: see references/symbols_reference.md

For usage examples: see the examples/ directory

mini-six-ren