Purpose
SkillDev toolsCompute symbolic numerology from a person's name and birthdate using deterministic mappings only. Use for numerology / 数字命理 / 生命路径数 / 姓名映射 requests and structured numerology JSON. Do not use for predictive fortune-telling or non-symbolic advice.
Available today. Use it from your connected AI after setup.
No other account needed.
Connect ahel once, and every AI you use reads what you have installed.
Then ask your AI: use the Purpose skill
What this skill tells your AI
The instructions your AI receives, as published by shizhilya/yuan in references/numerology/SKILL.md and read by ahel’s review.
Return a numerology analysis using only the symbolic rules in this skill. The result must be deterministic, reproducible, and limited to symbolic mappings.
Accepted input
Accept either:
-
A JSON object:
{ "input": { "name": "", "birthdate": "" } } -
A natural-language request that clearly includes both a name and a birthdate.
If one field is missing, ask only for the missing field.
If the birthdate is ambiguous (for example 03/04/2001), ask for ISO YYYY-MM-DD before computing.
Flow
- Calculate
- Map
- Output
Rules
1) Normalize birthdate
- Accept
YYYY-MM-DD,YYYY/MM/DD, orYYYYMMDD. - Remove all non-digit characters to produce
normalized_birthdate. normalized_birthdatemust contain exactly 8 digits.- If the date cannot be normalized to 8 digits, request correction.
2) Reduce function
Use this deterministic reducer everywhere a reduction step is required:
reduce_number(n):
while n is not 11, 22, or 33 and n > 9:
n = sum_of_digits(n)
return n
This preserves the master numbers 11, 22, and 33.
3) Life path number
Compute:
life_path_number = reduce_number(sum(digits(normalized_birthdate)))
4) Normalize name
- Trim leading and trailing whitespace.
- Ignore spaces, hyphens, underscores, apostrophes, and common punctuation.
- Convert Latin letters to uppercase before mapping.
- Do not transliterate non-Latin scripts into Latin. Use the fallback mapping directly.
5) Name mapping
Latin mapping
Use the following fixed mapping:
A J S = 1B K T = 2C L U = 3D M V = 4E N W = 5F O X = 6G P Y = 7H Q Z = 8I R = 9
Fallback mapping for non-Latin or unmapped characters
For every character that is not mapped by the Latin table:
- Take the character's Unicode decimal code point.
- Sum the digits of that decimal code point.
- Reduce that sum to a single digit from
1to9. - Use that value as the character mapping.
Example:
- Unicode code point
24352->2 + 4 + 3 + 5 + 2 = 16->1 + 6 = 7
6) Name number
- Map every valid character after name normalization.
- Compute:
name_number = reduce_number(sum(mapped_character_values))
7) Personality map
Use only this symbolic map:
1-> 标签["独立", "主动", "开创"], 符号"起点型"2-> 标签["协调", "敏感", "合作"], 符号"联结型"3-> 标签["表达", "创意", "社交"], 符号"表达型"4-> 标签["稳定", "秩序", "执行"], 符号"结构型"5-> 标签["变化", "自由", "探索"], 符号"变化型"6-> 标签["责任", "关怀", "和谐"], 符号"照护型"7-> 标签["内省", "分析", "洞察"], 符号"思辨型"8-> 标签["目标", "掌控", "成就"], 符号"成就型"9-> 标签["理想", "包容", "完成"], 符号"完成型"11-> 标签["直觉", "启发", "感召"], 符号"启发型"22-> 标签["建构", "整合", "落地"], 符号"建构型"33-> 标签["奉献", "滋养", "引导"], 符号"滋养型"
Output contract
Return JSON with exactly this top-level structure:
{
"核心数字": {
"生命路径数": 0,
"姓名数": 0,
"主导数": 0,
"辅助数": 0
},
"性格": {
"生命路径": {
"标签": [],
"符号": ""
},
"姓名映射": {
"标签": [],
"符号": ""
},
"综合": {
"标签": [],
"说明": ""
}
}
}
Output rules
主导数 = 生命路径数辅助数 = 姓名数生命路径uses the symbolic map forlife_path_number姓名映射uses the symbolic map forname_number综合.标签is the de-duplicated concatenation of生命路径.标签followed by姓名映射.标签综合.说明must be exactly:以内在核心采用生命路径数的符号映射,以外在表达采用姓名数的符号映射
Constraints
- Pure symbolic mapping only.
- No event prediction.
- No luck, fate, or timing claims.
- No medical, legal, financial, or safety claims.
- Do not add astrology, tarot, zodiac, feng shui, MBTI, clinical psychology, or any external system.
- Do not infer real-world outcomes from the numbers.
- Do not add unsupported narrative beyond the provided labels and symbols unless the user explicitly asks for a short explanation.
Formatting behavior
- Default to JSON only.
- If the user explicitly asks for an explanation, provide the JSON first and then a short explanation that stays fully consistent with the same mapping and constraints.
Canonical machine-readable spec
The canonical internal spec id is numerology_analysis.
The runtime skill name is numerology-analysis for broad compatibility across agent tools.
Use assets/spec.json as the machine-readable reference when needed.
Signals
- GitHub stars
- 191
- Forks
- 30
- Last commit
- Apr 2026
Advanced
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numerology-analysis- Source
- github.com/shizhilya/yuan