Understanding Db Schema
by C0ntr0lledCha0s
>
Skill Details
Repository Files
4 files in this skill directory
name: understanding-db-schema version: 1.0.0 description: > Deep expertise in Logseq's Datascript database schema. Auto-invokes when users ask about Logseq DB schema, Datascript attributes, built-in classes, property types, entity relationships, schema validation, or the node/block/page data model. Provides authoritative knowledge of the DB graph architecture. allowed-tools: Read, Grep, Glob, WebFetch, WebSearch
Understanding Logseq DB Schema
When to Use This Skill
This skill auto-invokes when:
- User asks about Logseq's database schema or Datascript
- Questions about built-in classes (Tag, Page, Task, Property, etc.)
- Property type system questions (:default, :number, :date, :checkbox, etc.)
- Entity relationship questions (block/tags, block/refs, block/parent)
- Schema validation or Malli schemas
- Node model or unified page/block concept
- User mentions
:db/ident,:logseq.class/*, or:logseq.property/*
Reference Material: See {baseDir}/references/built-in-classes.md for complete class hierarchy.
You have expert knowledge of Logseq's database schema architecture.
Datascript Foundation
Logseq DB graphs are built on Datascript, a Clojure/ClojureScript in-memory database that supports:
- Entity-Attribute-Value (EAV) data model
- Datalog queries
- Schema-driven attribute definitions
Attribute Types
;; Value types
:db.type/ref ; References to other entities
:db.type/string ; Text values
:db.type/long ; Integer numbers
:db.type/double ; Floating point numbers
:db.type/boolean ; True/false
:db.type/instant ; Timestamps
:db.type/keyword ; Clojure keywords
:db.type/uuid ; UUIDs
;; Cardinality
:db.cardinality/one ; Single value
:db.cardinality/many ; Multiple values (set)
Core Reference Attributes
:block/tags ; Classes/tags assigned to the entity
:block/refs ; Outgoing references to other entities
:block/alias ; Alternative names for a page
:block/parent ; Parent block in hierarchy
:block/page ; Page containing this block
Built-in Classes Hierarchy
:logseq.class/Root
├── :logseq.class/Page
├── :logseq.class/Tag (classes themselves)
├── :logseq.class/Property
├── :logseq.class/Task
│ └── Status, Priority, Deadline, Scheduled
├── :logseq.class/Query
├── :logseq.class/Asset
├── :logseq.class/Code-block
└── :logseq.class/Template
All non-Root classes extend :logseq.class/Root via :logseq.property.class/extends.
Property Type System
| Type | Validator | Closed Values | Use Case |
|---|---|---|---|
:default |
text-entity? |
✅ | Text blocks with titles |
:number |
number-entity? |
✅ | Numeric values |
:date |
date? |
❌ | Journal page entities |
:datetime |
datetime? |
❌ | Time-based scheduling |
:checkbox |
boolean? |
❌ | Toggle properties |
:url |
url-entity? |
✅ | URL strings or macros |
:node |
node-entity? |
❌ | Block/page references |
:class |
class-entity? |
❌ | Class entities |
Property Configuration Keys
{:db/ident :user.property/my-property
:logseq.property/type :default ; Property type
:logseq.property/cardinality :one ; :one or :many
:logseq.property/hide? false ; Hide by default
:logseq.property.ui/position :properties ; UI placement
:logseq.property/closed-values [...] ; Restricted choices
:logseq.property/schema-classes [...] ; Associated classes
:block/title "My Property"} ; Display name
Property Namespaces
| Namespace | Purpose | Example |
|---|---|---|
logseq.property |
Core system properties | :logseq.property/type |
logseq.property.class |
Class-related | :logseq.property.class/extends |
logseq.property.table |
Table views | :logseq.property.table/columns |
user.property |
User-defined | :user.property/author |
plugin.property |
Plugin-defined | :plugin.property/custom |
Schema Versioning
;; Version format
{:major 65 :minor 12}
;; Stored in
:logseq.kv/schema-version ; Graph's current version
db-schema/version ; Expected version
Migrations handle schema upgrades between versions (65.0 → 65.12+).
Malli Validation Flow
- Entity transformation: Properties →
[property-map value]tuples - Schema dispatch: Validation dispatches on
:logseq.property/type - Value validation: Individual values checked against type schemas
- Cardinality handling: Automatic
:manyvs:onehandling - Transaction validation:
validate-tx-reportensures integrity
Node Model
Unified Node Concept
In DB version, nodes represent both pages and blocks:
Node
├── Page (unique by tag combination)
│ ├── Journal pages (#Journal)
│ ├── Regular pages (#Page)
│ └── Class pages (#Tag)
└── Block (within pages)
├── Content blocks
├── Property blocks
└── Convertible to page via #Page tag
Page Uniqueness
Pages are unique by their tag combination:
- "Apple #Company" ≠ "Apple #Fruit"
- Both can coexist as separate entities
Common Patterns
Creating a Custom Class
;; Define a class with properties
{:db/ident :user.class/Book
:block/tags [:logseq.class/Tag]
:block/title "Book"
:logseq.property.class/extends :logseq.class/Root
:logseq.property/schema-classes
[:user.property/author
:user.property/isbn
:user.property/rating]}
Creating a Typed Property
;; Number property with choices
{:db/ident :user.property/rating
:block/title "Rating"
:logseq.property/type :number
:logseq.property/cardinality :one
:logseq.property/closed-values [1 2 3 4 5]}
Resources
When users need more information, reference:
Related Skills
Attack Tree Construction
Build comprehensive attack trees to visualize threat paths. Use when mapping attack scenarios, identifying defense gaps, or communicating security risks to stakeholders.
Grafana Dashboards
Create and manage production Grafana dashboards for real-time visualization of system and application metrics. Use when building monitoring dashboards, visualizing metrics, or creating operational observability interfaces.
Matplotlib
Foundational plotting library. Create line plots, scatter, bar, histograms, heatmaps, 3D, subplots, export PNG/PDF/SVG, for scientific visualization and publication figures.
Scientific Visualization
Create publication figures with matplotlib/seaborn/plotly. Multi-panel layouts, error bars, significance markers, colorblind-safe, export PDF/EPS/TIFF, for journal-ready scientific plots.
Seaborn
Statistical visualization. Scatter, box, violin, heatmaps, pair plots, regression, correlation matrices, KDE, faceted plots, for exploratory analysis and publication figures.
Shap
Model interpretability and explainability using SHAP (SHapley Additive exPlanations). Use this skill when explaining machine learning model predictions, computing feature importance, generating SHAP plots (waterfall, beeswarm, bar, scatter, force, heatmap), debugging models, analyzing model bias or fairness, comparing models, or implementing explainable AI. Works with tree-based models (XGBoost, LightGBM, Random Forest), deep learning (TensorFlow, PyTorch), linear models, and any black-box model
Pydeseq2
Differential gene expression analysis (Python DESeq2). Identify DE genes from bulk RNA-seq counts, Wald tests, FDR correction, volcano/MA plots, for RNA-seq analysis.
Query Writing
For writing and executing SQL queries - from simple single-table queries to complex multi-table JOINs and aggregations
Pydeseq2
Differential gene expression analysis (Python DESeq2). Identify DE genes from bulk RNA-seq counts, Wald tests, FDR correction, volcano/MA plots, for RNA-seq analysis.
Scientific Visualization
Meta-skill for publication-ready figures. Use when creating journal submission figures requiring multi-panel layouts, significance annotations, error bars, colorblind-safe palettes, and specific journal formatting (Nature, Science, Cell). Orchestrates matplotlib/seaborn/plotly with publication styles. For quick exploration use seaborn or plotly directly.
