| name | tag-initialize |
| description | Generate an initial hierarchical tag taxonomy for a knowledge base domain by calling LLM once. Uses domain-specific references (general, university-policy, etc.) that customize the generation prompt. The output maps to the tags table (ltree paths). The generated 2-level tree is the starting point — deeper nesting emerges naturally during ingest as the extraction LLM splits overcrowded leaf tags into sub-leaves. |
| license | MIT |
| compatibility | Requires schema.sql tags table with ltree extension. |
| metadata | {"author":"Hello-Wiki","version":"0.1.0","stage":"mvp"} |
Tag Initialize Skill
Generate a domain-specific hierarchical tag taxonomy. Invoked once when setting up a new knowledge base. Selects the appropriate domain reference, calls an LLM with the domain-specific prompt, and produces a JSON tag tree ready for insertion into the tags table.
Domain Reference Selection
The skill resolves the reference by matching the user's domain against references/index.yaml:
| Reference | When |
|---|
general | Mixed-content or unspecified domain (default fallback) |
university_policy | Higher education administration documents |
Selection logic: match domain → reference id. No match → fallback to the reference with default: true.
Input
{
"domain": "string — domain identifier (e.g. 'university_policy')",
"description": "string — what content the knowledge base will contain",
"language": "string — primary language ('zh', 'en', 'mixed')",
"existing_tags": ["string — tag names already in the system (avoid duplicates)"]
}
Output
{
"domain": "university_policy",
"generated_at": "2026-05-08T10:00:00Z",
"categories": [
{
"name": "document_type",
"label": "文档类型",
"description": "The type or genre of the document, independent of its topic.",
"leaves": [
{ "name": "policy", "label": "政策文件", "description": "Formal policy documents establishing rules or principles." },
{ "name": "regulation", "label": "管理规定", "description": "Detailed regulations implementing policies." }
]
}
]
}
Mapping to tags Table
The output maps to tags as a 2-level hierarchy (this is the starting point — deeper levels emerge during ingest splitting):
Category (level=0, is_leaf=false):
INSERT INTO tags (name, label, description, parent_id, level, path, is_leaf)
VALUES ('document_type', '文档类型', '...', NULL, 0, 'document_type', false)
Leaf (level=1, is_leaf=true):
INSERT INTO tags (name, label, description, parent_id, level, path, is_leaf)
VALUES ('policy', '政策文件', '...', <category.id>, 1, 'document_type.policy', true)
The persistence layer:
- Inserts category rows (level=0, is_leaf=false, path=name)
- For each leaf: inserts leaf row (level=1, is_leaf=true, path=
{category_name}.{leaf_name}, parent_id=category.id)
- Uses
ON CONFLICT (path) DO NOTHING for idempotency
How the Tree Grows During Ingest (Not This Skill's Job)
The initial 2-level tree provides the classification backbone. During ingest, the extraction LLM can split a leaf that becomes too broad. For example, if functional_area.examinations accumulates 200+ documents, the extraction LLM proposes sub-leaves (makeup, midterm, final) and the parent becomes a non-leaf node. This is handled by the ingest persistence layer, not this initialization skill.
Guardrails
- Domain-driven: The LLM designs the taxonomy from the domain description + reference prompt, not from a fixed template
- Initial structure is 2-level: categories (level 0) → leaves (level 1). Deeper nesting emerges from ingest splitting
- Idempotent: Running twice with the same input produces compatible output;
ON CONFLICT (path) prevents duplicates
- Naming: All tag names match
^[a-z][a-z0-9_]*$
