Requirements
- Target platform
- OpenClaw
- Install method
- Manual import
- Extraction
- Extract archive
- Prerequisites
- OpenClaw
- Primary doc
- SKILL.md
Tencent SkillHub Β· AI
Data Model Designer
Design data models for construction projects. Create entity-relationship diagrams, define schemas, and generate database structures.
skill openclawclawhub Free
Design data models for construction projects. Create entity-relationship diagrams, define schemas, and generate database structures.
β¬ 0 downloads β
0 stars Unverified but indexed
Install for OpenClaw
Quick setup
- Download the package from Yavira.
- Extract the archive and review SKILL.md first.
- Import or place the package into your OpenClaw setup.
Package facts
- Download mode
- Yavira redirect
- Package format
- ZIP package
- Source platform
- Tencent SkillHub
- What's included
- claw.json, instructions.md, SKILL.md
Validation
- Use the Yavira download entry.
- Review SKILL.md after the package is downloaded.
- Confirm the extracted package contains the expected setup assets.
Install with your agent
Agent handoff
Hand the extracted package to your coding agent with a concrete install brief instead of figuring it out manually.
- Download the package from Yavira.
- Extract it into a folder your agent can access.
- Paste one of the prompts below and point your agent at the extracted folder.
New install
I downloaded a skill package from Yavira. Read SKILL.md from the extracted folder and install it by following the included instructions. Tell me what you changed and call out any manual steps you could not complete.
Upgrade existing
I downloaded an updated skill package from Yavira. Read SKILL.md from the extracted folder, compare it with my current installation, and upgrade it while preserving any custom configuration unless the package docs explicitly say otherwise. Summarize what changed and any follow-up checks I should run.
Trust & source
Release facts
- Source
- Tencent SkillHub
- Verification
- Indexed source record
- Version
- 2.1.0
Provenance
- Publisher
- datadrivenconstruction
- Source page
- View original listing
- Canonical URL
- Open canonical page
Documentation
Problem Statement
Construction data management challenges: Fragmented data across systems Inconsistent data structures Missing relationships between entities Difficult data integration
Solution
Systematic data model design for construction projects, defining entities, relationships, and schemas for effective data management.
Technical Implementation
from typing import Dict, Any, List, Optional from dataclasses import dataclass, field from enum import Enum import json class DataType(Enum): STRING = "string" INTEGER = "integer" FLOAT = "float" BOOLEAN = "boolean" DATE = "date" DATETIME = "datetime" TEXT = "text" JSON = "json" class RelationType(Enum): ONE_TO_ONE = "1:1" ONE_TO_MANY = "1:N" MANY_TO_MANY = "N:M" class ConstraintType(Enum): PRIMARY_KEY = "primary_key" FOREIGN_KEY = "foreign_key" UNIQUE = "unique" NOT_NULL = "not_null" @dataclass class Field: name: str data_type: DataType nullable: bool = True default: Any = None description: str = "" constraints: List[ConstraintType] = field(default_factory=list) @dataclass class Entity: name: str description: str fields: List[Field] = field(default_factory=list) primary_key: str = "id" @dataclass class Relationship: name: str from_entity: str to_entity: str relation_type: RelationType from_field: str to_field: str class ConstructionDataModel: """Design data models for construction projects.""" def __init__(self, project_name: str): self.project_name = project_name self.entities: Dict[str, Entity] = {} self.relationships: List[Relationship] = [] def add_entity(self, entity: Entity): """Add entity to model.""" self.entities[entity.name] = entity def add_relationship(self, relationship: Relationship): """Add relationship between entities.""" self.relationships.append(relationship) def create_entity(self, name: str, description: str, fields: List[Dict[str, Any]]) -> Entity: """Create entity from field definitions.""" entity_fields = [ Field( name=f['name'], data_type=DataType(f.get('type', 'string')), nullable=f.get('nullable', True), default=f.get('default'), description=f.get('description', ''), constraints=[ConstraintType(c) for c in f.get('constraints', [])] ) for f in fields ] entity = Entity(name=name, description=description, fields=entity_fields) self.add_entity(entity) return entity def create_relationship(self, from_entity: str, to_entity: str, relation_type: str = "1:N", from_field: str = None) -> Relationship: """Create relationship between entities.""" rel = Relationship( name=f"{from_entity}_{to_entity}", from_entity=from_entity, to_entity=to_entity, relation_type=RelationType(relation_type), from_field=from_field or f"{to_entity.lower()}_id", to_field="id" ) self.add_relationship(rel) return rel def generate_sql_schema(self, dialect: str = "postgresql") -> str: """Generate SQL DDL statements.""" sql = [] type_map = { DataType.STRING: "VARCHAR(255)", DataType.INTEGER: "INTEGER", DataType.FLOAT: "DECIMAL(15,2)", DataType.BOOLEAN: "BOOLEAN", DataType.DATE: "DATE", DataType.DATETIME: "TIMESTAMP", DataType.TEXT: "TEXT", DataType.JSON: "JSONB" if dialect == "postgresql" else "JSON" } for name, entity in self.entities.items(): columns = [] for fld in entity.fields: col = f" {fld.name} {type_map.get(fld.data_type, 'VARCHAR(255)')}" if not fld.nullable: col += " NOT NULL" if ConstraintType.PRIMARY_KEY in fld.constraints: col += " PRIMARY KEY" columns.append(col) sql.append(f"CREATE TABLE {name} (\n" + ",\n".join(columns) + "\n);") for rel in self.relationships: sql.append(f"""ALTER TABLE {rel.from_entity} ADD CONSTRAINT fk_{rel.name} FOREIGN KEY ({rel.from_field}) REFERENCES {rel.to_entity}({rel.to_field});""") return "\n\n".join(sql) def generate_json_schema(self) -> Dict[str, Any]: """Generate JSON Schema representation.""" schemas = {} for name, entity in self.entities.items(): properties = {} required = [] for fld in entity.fields: prop = {"description": fld.description} if fld.data_type == DataType.STRING: prop["type"] = "string" elif fld.data_type == DataType.INTEGER: prop["type"] = "integer" elif fld.data_type == DataType.FLOAT: prop["type"] = "number" elif fld.data_type == DataType.BOOLEAN: prop["type"] = "boolean" else: prop["type"] = "string" properties[fld.name] = prop if not fld.nullable: required.append(fld.name) schemas[name] = { "type": "object", "title": entity.description, "properties": properties, "required": required } return schemas def generate_er_diagram(self) -> str: """Generate Mermaid ER diagram.""" lines = ["erDiagram"] for name, entity in self.entities.items(): for fld in entity.fields[:5]: lines.append(f" {name} {{") lines.append(f" {fld.data_type.value} {fld.name}") lines.append(" }") for rel in self.relationships: rel_symbol = { RelationType.ONE_TO_ONE: "||--||", RelationType.ONE_TO_MANY: "||--o{", RelationType.MANY_TO_MANY: "}o--o{" }.get(rel.relation_type, "||--o{") lines.append(f" {rel.from_entity} {rel_symbol} {rel.to_entity} : \"{rel.name}\"") return "\n".join(lines) def validate_model(self) -> List[str]: """Validate data model for issues.""" issues = [] for rel in self.relationships: if rel.from_entity not in self.entities: issues.append(f"Missing entity: {rel.from_entity}") if rel.to_entity not in self.entities: issues.append(f"Missing entity: {rel.to_entity}") for name, entity in self.entities.items(): has_pk = any(ConstraintType.PRIMARY_KEY in f.constraints for f in entity.fields) if not has_pk: issues.append(f"Entity '{name}' has no primary key") return issues class ConstructionEntities: """Standard construction data entities.""" @staticmethod def project_entity() -> Entity: return Entity( name="projects", description="Construction projects", fields=[ Field("id", DataType.INTEGER, False, constraints=[ConstraintType.PRIMARY_KEY]), Field("code", DataType.STRING, False, constraints=[ConstraintType.UNIQUE]), Field("name", DataType.STRING, False), Field("status", DataType.STRING), Field("start_date", DataType.DATE), Field("end_date", DataType.DATE), Field("budget", DataType.FLOAT) ] ) @staticmethod def activity_entity() -> Entity: return Entity( name="activities", description="Schedule activities", fields=[ Field("id", DataType.INTEGER, False, constraints=[ConstraintType.PRIMARY_KEY]), Field("project_id", DataType.INTEGER, False), Field("wbs_code", DataType.STRING), Field("name", DataType.STRING, False), Field("start_date", DataType.DATE), Field("end_date", DataType.DATE), Field("percent_complete", DataType.FLOAT) ] ) @staticmethod def cost_item_entity() -> Entity: return Entity( name="cost_items", description="Project cost items", fields=[ Field("id", DataType.INTEGER, False, constraints=[ConstraintType.PRIMARY_KEY]), Field("project_id", DataType.INTEGER, False), Field("wbs_code", DataType.STRING), Field("description", DataType.STRING), Field("budgeted_cost", DataType.FLOAT), Field("actual_cost", DataType.FLOAT) ] )
Quick Start
# Create model model = ConstructionDataModel("Office Building A") # Add standard entities model.add_entity(ConstructionEntities.project_entity()) model.add_entity(ConstructionEntities.activity_entity()) model.add_entity(ConstructionEntities.cost_item_entity()) # Add relationships model.create_relationship("activities", "projects") model.create_relationship("cost_items", "projects") # Generate SQL sql = model.generate_sql_schema("postgresql") print(sql)
1. Custom Entity
model.create_entity( name="change_orders", description="Project change orders", fields=[ {"name": "id", "type": "integer", "nullable": False, "constraints": ["primary_key"]}, {"name": "project_id", "type": "integer", "nullable": False}, {"name": "amount", "type": "float"}, {"name": "status", "type": "string"} ] )
2. Generate ER Diagram
er_diagram = model.generate_er_diagram() print(er_diagram)
3. Validate Model
issues = model.validate_model() for issue in issues: print(f"Issue: {issue}")
Resources
DDC Book: Chapter 2.5 - Data Models and Standards Website: https://datadrivenconstruction.io
Category context
Agent frameworks, memory systems, reasoning layers, and model-native orchestration.
Source: Tencent SkillHub
Largest current source with strong distribution and engagement signals.
Package contents
Included in package
2 Docs1 Config
- SKILL.md
- instructions.md
- claw.json