---

name: surrealdb description: "Expert SurrealDB 3 architect and developer skill. SurrealQL mastery, multi-model data modeling (document, graph, vector, time-series, geospatial), schema design, security, deployment, performance tuning, SDK integration (JS, Python, Go, Rust), Surrealism WASM extensions, and full ecosystem (Surrealist, Surreal-Sync, SurrealFS). Universal skill for 30+ AI agents." license: MIT metadata: version: "1.2.0" author: "24601" snapshot_date: "2026-03-03" repository: "https://github.com/24601/surreal-skills" requires: binaries: - name: surreal install: "brew install surrealdb/tap/surreal" purpose: "SurrealDB CLI for server management, SQL REPL, import/export" optional: false - name: python3 version: ">=3.10" purpose: "Required for skill scripts (doctor.py, schema.py, onboard.py)" optional: false - name: uv install: "brew install uv" purpose: "PEP 723 script runner -- installs script deps automatically" optional: false - name: docker purpose: "Containerized SurrealDB instances" optional: true - name: gh install: "brew install gh" purpose: "GitHub CLI -- used only by check_upstream.py for comparing upstream repo SHAs" optional: true env_vars: - name: SURREAL_ENDPOINT purpose: "SurrealDB server URL" default: "http://localhost:8000" sensitive: false - name: SURREAL_USER purpose: "Authentication username" default: "root" sensitive: true - name: SURREAL_PASS purpose: "Authentication password" default: "root" sensitive: true - name: SURREAL_NS purpose: "Default namespace" default: "test" sensitive: false - name: SURREAL_DB purpose: "Default database" default: "test" sensitive: false security: no_network: false no_network_note: "doctor.py and schema.py connect to a user-specified SurrealDB endpoint (WebSocket) for health checks and schema introspection. check_upstream.py calls GitHub API via gh CLI to compare upstream repo SHAs. No other third-party network calls." no_credentials: false no_credentials_note: "Scripts accept SURREAL_USER/SURREAL_PASS for DB authentication. No credentials are stored in the skill itself." no_env_write: true no_file_write: true no_shell_exec: false no_shell_exec_note: "Scripts invoke surreal CLI and gh for health checks." scripts_auditable: true scripts_use_pep723: true no_obfuscated_code: true no_binary_blobs: true no_minified_scripts: true no_curl_pipe_sh: false no_curl_pipe_sh_note: "Documentation mentions curl|sh as ONE install option alongside safer alternatives (brew, Docker, package managers). The skill itself never executes curl|sh."

SurrealDB 3 Skill

Expert-level SurrealDB 3 architecture, development, and operations. Covers SurrealQL, multi-model data modeling, graph traversal, vector search, security, deployment, performance tuning, SDK integration, and the full SurrealDB ecosystem.

For AI Agents

Get a full capabilities manifest, decision trees, and output contracts:

uv run {baseDir}/scripts/onboard.py --agent

See AGENTS.md for the complete structured briefing.

Prerequisites

• surreal CLI -- brew install surrealdb/tap/surreal (macOS) or see install docs
• Python 3.10+ -- Required for skill scripts
• uv -- brew install uv (macOS) or pip install uv or see uv docs

Optional:

• Docker -- For containerized SurrealDB instances (docker run surrealdb/surrealdb:v3)
• SDK of choice -- JavaScript, Python, Go, Rust, Java, .NET, C, PHP, or Dart

Security note: This skill's documentation references package manager installs (brew, pip, cargo, npm, Docker) as the recommended install method. If you encounter curl | sh examples in the rules files, prefer your OS package manager or download-and-review workflow instead.

Quick Start

Credential warning: Examples below use root/root for local development only. Never use default credentials against production or shared instances. Create scoped, least-privilege users for non-local environments.

# Start SurrealDB in-memory for LOCAL DEVELOPMENT ONLY
surreal start memory --user root --pass root --bind 127.0.0.1:8000

# Start with persistent RocksDB storage (local dev)
surreal start rocksdb://data/mydb.db --user root --pass root

# Start with SurrealKV (time-travel queries supported, local dev)
surreal start surrealkv://data/mydb --user root --pass root

# Connect via CLI REPL (local dev)
surreal sql --endpoint http://localhost:8000 --user root --pass root --ns test --db test

# Import a SurrealQL file
surreal import --endpoint http://localhost:8000 --user root --pass root --ns test --db test schema.surql

# Export the database
surreal export --endpoint http://localhost:8000 --user root --pass root --ns test --db test backup.surql

# Check version
surreal version

# Run the skill health check
uv run {baseDir}/scripts/doctor.py

Environment Variables

These map directly to the surreal sql CLI flags (--endpoint, --user, --pass, --ns, --db) and are recognized by official SurrealDB SDKs.

Core Capabilities

SurrealQL Mastery

Full coverage of the SurrealQL query language: CREATE, SELECT, UPDATE, UPSERT, DELETE, RELATE, INSERT, LIVE SELECT, DEFINE, REMOVE, INFO, subqueries, transactions, futures, and all built-in functions (array, crypto, duration, geo, math, meta, object, parse, rand, string, time, type, vector).

See: rules/surrealql.md

Multi-Model Data Modeling

Design schemas that leverage SurrealDB's multi-model capabilities -- document collections, graph edges, relational references, vector embeddings, time-series data, and geospatial coordinates -- all in a single database with a single query language.

See: rules/data-modeling.md

Graph Queries

First-class graph traversal without JOINs. RELATE creates typed edges between records. Traverse with -> (outgoing), <- (incoming), and <-> (bidirectional) operators. Filter, aggregate, and recurse at any depth.

See: rules/graph-queries.md

Vector Search

Built-in vector similarity search using HNSW and brute-force indexes. Define vector fields, create indexes with configurable distance metrics (cosine, euclidean, manhattan, minkowski), and query with vector::similarity::* functions. Build RAG pipelines and semantic search directly in SurrealQL.

See: rules/vector-search.md

Security and Permissions

Row-level security via DEFINE TABLE ... PERMISSIONS, namespace/database/record-level access control, DEFINE ACCESS for JWT/token-based auth, DEFINE USER for system users, and $auth/$session runtime variables for permission predicates.

See: rules/security.md

Deployment and Operations

Single-binary deployment, Docker, Kubernetes (Helm charts), storage engine selection (memory, RocksDB, SurrealKV, TiKV for distributed), backup/restore, monitoring, and production hardening.

See: rules/deployment.md

Performance Tuning

Index strategies (unique, search, vector HNSW, MTree), query optimization with EXPLAIN, connection pooling, storage engine trade-offs, batch operations, and resource limits.

See: rules/performance.md

SDK Integration

Official SDKs for JavaScript/TypeScript (Node.js, Deno, Bun, browser), Python, Go, Rust, Java, .NET, C, PHP, and Dart. Connection protocols (HTTP, WebSocket), authentication flows, live query subscriptions, and typed record handling.

See: rules/sdks.md

Surrealism WASM Extensions

New in SurrealDB 3: extend the database with custom functions, analyzers, and logic written in Rust and compiled to WASM. Define, deploy, and manage Surrealism modules.

See: rules/surrealism.md

Ecosystem Tools

• Surrealist -- Official IDE and GUI for SurrealDB (schema designer, query editor, graph visualizer)
• Surreal-Sync -- Change Data Capture (CDC) for migrations from other databases
• SurrealFS -- AI agent filesystem built on SurrealDB
• SurrealML -- Machine learning model management and inference within SurrealDB

See: rules/surrealist.md, rules/surreal-sync.md, rules/surrealfs.md

Doctor / Health Check

# Full diagnostic (Rich output on stderr, JSON on stdout)
uv run {baseDir}/scripts/doctor.py

# Quick check (exit code 0 = healthy, 1 = issues found)
uv run {baseDir}/scripts/doctor.py --check

# Check a specific endpoint
uv run {baseDir}/scripts/doctor.py --endpoint http://my-server:8000

The doctor script verifies: surreal CLI installed and on PATH, server reachable, authentication succeeds, namespace and database exist, version compatibility, and storage engine status.

Schema Introspection

# Full schema dump (all tables, fields, indexes, events, accesses)
uv run {baseDir}/scripts/schema.py introspect

# List tables with summary
uv run {baseDir}/scripts/schema.py tables

# Inspect a specific table
uv run {baseDir}/scripts/schema.py table <table_name>

# Export schema as SurrealQL (reproducible DEFINE statements)
uv run {baseDir}/scripts/schema.py export --format surql

# Export schema as JSON
uv run {baseDir}/scripts/schema.py export --format json

Introspection uses INFO FOR DB, INFO FOR TABLE, and INFO FOR NS to reconstruct the full schema.

Rules Reference

Workflow Examples

All workflow examples use root/root for local development only. For production, use DEFINE USER with scoped, least-privilege credentials.

New Project Setup

# 1. Verify environment
uv run {baseDir}/scripts/doctor.py

# 2. Start SurrealDB
surreal start rocksdb://data/myproject.db --user root --pass root

# 3. Design schema (use rules/data-modeling.md for guidance)
# 4. Import initial schema
surreal import --endpoint http://localhost:8000 --user root --pass root \
  --ns myapp --db production schema.surql

# 5. Introspect to verify
uv run {baseDir}/scripts/schema.py introspect

Migration from SurrealDB v2

# 1. Export v2 data
surreal export --endpoint http://old-server:8000 --user root --pass root \
  --ns myapp --db production v2-backup.surql

# 2. Review breaking changes (see rules/surrealql.md v2->v3 migration section)
# Key changes: range syntax 1..4 is now exclusive of end, new WASM extension system

# 3. Import into v3
surreal import --endpoint http://localhost:8000 --user root --pass root \
  --ns myapp --db production v2-backup.surql

# 4. Verify schema
uv run {baseDir}/scripts/schema.py introspect

Data Modeling for a New Domain

# 1. Read rules/data-modeling.md for schema design patterns
# 2. Read rules/graph-queries.md if your domain has relationships
# 3. Read rules/vector-search.md if you need semantic search
# 4. Draft schema.surql with DEFINE TABLE, DEFINE FIELD, DEFINE INDEX
# 5. Import and test
surreal import --endpoint http://localhost:8000 --user root --pass root \
  --ns dev --db test schema.surql
uv run {baseDir}/scripts/schema.py introspect

Deploying to Production

# 1. Read rules/deployment.md for storage engine selection and hardening
# 2. Read rules/security.md for access control setup
# 3. Read rules/performance.md for index strategy
# 4. Run doctor against production endpoint
uv run {baseDir}/scripts/doctor.py --endpoint https://prod-surreal:8000
# 5. Verify schema matches expectations
uv run {baseDir}/scripts/schema.py introspect --endpoint https://prod-surreal:8000

Upstream Source Check

# Check if upstream SurrealDB repos have changed since this skill was built
uv run {baseDir}/scripts/check_upstream.py

# JSON-only output for agents
uv run {baseDir}/scripts/check_upstream.py --json

# Only show repos that have new commits
uv run {baseDir}/scripts/check_upstream.py --stale

Compares current HEAD SHAs and release tags of all tracked repos against the baselines in SOURCES.json. Use this to plan incremental skill updates.

Source Provenance

This skill was built on 2026-02-19 from these upstream sources:

Documentation: surrealdb.com/docs snapshot 2026-02-22.

Machine-readable provenance: SOURCES.json.

Output Convention

All Python scripts in this skill follow a dual-output pattern:

• stderr: Rich-formatted human-readable output (tables, panels, status indicators)
• stdout: Machine-readable JSON for programmatic consumption by AI agents

This means 2>/dev/null hides the human output, and piping stdout gives clean JSON for downstream processing.