Procedures

This reference is designed for both human developers and AI coding agents. Every entry includes complete CALL syntax and return columns that can be used directly in queries.

100+ CALL procedures: Database Introspection (20), Graph Algorithms (27), Embedding (5), Knowledge Graph (6), Temporal (9), Live Queries (5), System (14), Auth (7), Health (3), Extensions (5), and Behavior Graph (3). All return tabular results.

CALL db.procedures()

Returns the full list of available procedures (column: name).

Database Introspection (20)#

Core procedures for inspecting database state, schema, and metadata.

Procedure	Return Columns	Description	Since
`CALL db.nodeCount()`	`count`	Total node count	0.19.0
`CALL db.relCount()`	`count`	Total relationship count	0.19.0
`CALL db.labels()`	`label`	All node labels in use	0.19.0
`CALL db.types()`	`type`	All relationship types in use	0.19.0
`CALL db.keys()`	`key`	All property keys in use	0.19.0
`CALL db.version()`	`name`, `version`, `crates`, `waves`	Engine version and build info	0.19.0
`CALL db.stats()`	`nodes`, `relationships`, `skills`	Database statistics summary	0.20.0
`CALL db.stats.json()`	`json`	All metadata as single JSON object	5.0.0
`CALL db.schema()`	`label`, `properties`, `count`	Schema overview: labels, property keys per label, counts, and relationship patterns	4.0.0
`CALL db.indexes()`	`label`, `property`	All indexes with target label and property	0.19.0
`CALL db.constraints()`	`label`, `property`, `type`	All constraints with target and type	0.19.0
`CALL db.procedures()`	`name`	List all available procedure names	0.20.0
`CALL db.help()`	`procedure`, `description`, `example`	Quick-reference of key procedures with examples	5.0.0
`CALL db.tutorial()`	`step`, `title`, `query`, `description`	Interactive 6-step walkthrough for new users	5.0.0
`CALL db.doctor()`	`check`, `status`, `detail`	Diagnostic health check: 5 checks + HEALTHY/ISSUES_FOUND summary	4.0.0
`CALL db.export()`	`snapshot`, `nodes`, `relationships`, `generation`	Export full graph as JSON snapshot	3.0.0
`CALL db.import('<json>')`	`status`, `nodes_before`, `nodes_after`	Import graph from JSON snapshot (mutating)	5.0.0
`CALL db.import.csv('<csv>', '<Label>')`	`imported`	Import CSV rows as nodes with given label (mutating)	5.0.0
`CALL db.clear()`	`status`, `nodes_removed`, `rels_removed`	Delete all nodes, relationships, and indexes (mutating)	5.0.0
`CALL db.demo()`	(demo graph)	Load sample social network graph with example queries (mutating)	5.0.0

-- Get a schema overview
CALL db.schema()

Returns one row per label with property keys and node count, plus relationship patterns.

-- Run diagnostics
CALL db.doctor()

Returns rows for each check (node_count, relationship_integrity, index_consistency, constraints, generation) plus a summary row with HEALTHY or ISSUES_FOUND status.

Graph Algorithms (27)#

Centrality (5)#

Procedure	Return Columns	Description	Since
`CALL algo.pageRank()`	`nodeId`, `name`, `rank`	PageRank (20 iterations, damping 0.85). GPU-accelerated when available.	0.26.0
`CALL algo.confidencePageRank()`	`nodeId`, `name`, `confidence`, `rank`	PageRank weighted by node confidence scores	5.0.0
`CALL algo.betweenness()`	`nodeId`, `name`, `betweenness`	Betweenness centrality scores	3.0.0
`CALL algo.closeness()`	`nodeId`, `name`, `closeness`	Closeness centrality scores	3.0.0
`CALL algo.degreeCentrality()`	`nodeId`, `name`, `centrality`	Degree centrality scores	3.0.0

CALL algo.pageRank()

Returns one row per node, sorted by rank. Uses 20 iterations with damping factor 0.85.

Community Detection (5)#

Procedure	Return Columns	Description	Since
`CALL algo.connectedComponents()`	`nodeId`, `name`, `component`	Connected component IDs	0.26.0
`CALL algo.communityDetection()`	`nodeId`, `name`, `community`	Community IDs via label propagation. GPU-accelerated when available.	0.26.0
`CALL algo.louvain()`	`nodeId`, `name`, `community`	Community IDs via Louvain modularity optimization. GPU-accelerated when available.	3.0.0
`CALL algo.leiden()`	`nodeId`, `community`	Community IDs via Leiden algorithm (20 iterations)	5.0.0
`CALL algo.kCore()`	`nodeId`, `name`, `coreness`	K-core decomposition values	3.0.0

CALL algo.louvain()

Returns one row per node with hierarchical community assignment.

Graph Metrics (4)#

Procedure	Return Columns	Description	Since
`CALL algo.density()`	`density`	Graph density ratio (0.0 to 1.0)	3.0.0
`CALL algo.diameter()`	`diameter`	Graph diameter (longest shortest path)	3.0.0
`CALL algo.triangleCount()`	`triangles`	Total triangle count in the graph. GPU-accelerated when available.	3.0.0
`CALL algo.clusteringCoefficient()`	`nodeId`, `name`, `coefficient`	Per-node clustering coefficients. GPU-accelerated when available.	3.0.0

CALL algo.triangleCount()

Returns a single row with the total number of triangles.

Path Analysis (4)#

Procedure	Return Columns	Description	Since
`CALL algo.allPairsShortestPath()`	`source`, `target`, `distance`	Shortest path distances between all node pairs (capped at 100 rows). GPU-accelerated when available.	3.0.0
`CALL algo.confidencePath(startId, endId)`	`path`, `cost`, `length`	Shortest path between two nodes weighted by confidence	5.0.0
`CALL algo.dijkstra(startId, endId, 'weight')`	`path`, `distance`	Weighted shortest path	10.0.0
`CALL algo.astar(startId, endId, 'weight', 'heuristic')`	`path`, `distance`	Heuristic-guided shortest path (A*)	10.0.0

-- Find confidence-weighted shortest path between node 1 and node 5
CALL algo.confidencePath(1, 5)

Returns the path as "id1 -> id2 -> id3", total cost, and hop count.

Similarity and Spatial (6)#

Procedure	Return Columns	Description	Since
`CALL algo.nodeSimilarity()`	`node1`, `node2`, `similarity`	Pairs of nodes with Jaccard similarity scores (top 20)	4.0.0
`CALL algo.similarNodes()`	`nodeId`, `score`	Nodes similar to the first vector-bearing node (cosine similarity)	5.0.0
`CALL algo.nearestNodes(point, label, k)`	`node`, `distance`	K nearest nodes by exact spatial distance (ArcFlow Spatial Index, ≥ 2000/s at 11K entities)	5.0.0
`CALL algo.objectsInFrustum($frustum)`	`node`, `distance`	Entities within a camera frustum (6-plane containment, < 2ms for 50 entities)	10.0.0
`CALL algo.nearestVisible($pos, label, k)`	`node`, `distance`	Nearest entities with direct line-of-sight from a point	10.0.0
`CALL spatial.raycast(origin, direction, maxDist)`	`hit`, `distance`	First node along a ray within max distance	10.0.0

Vector Search and RAG (5)#

Procedure	Return Columns	Description	Since
`CALL algo.vectorSearch()`	`nodeId`, `score`, `labels`	Vector similarity search over vector index. Accepts optional query vector argument. GPU-accelerated when available.	5.0.0
`CALL algo.hybridSearch()`	`nodeId`, `score`, `hops`	Combined vector + graph traversal search	5.0.0
`CALL algo.graphRAG()`	`nodeId`, `score`, `hops`, `labels`	Graph-augmented retrieval for RAG pipelines. Accepts optional query vector argument.	5.0.0
`CALL algo.graphRAGContext()`	`context`, `node_count`, `tokens_approx`	Formatted LLM context from graph retrieval. Accepts optional query vector and max_tokens arguments.	5.0.0
`CALL algo.graphRAGTrusted()`	`nodeId`, `trusted_score`, `hops`, `observation`	Trusted RAG with confidence-filtered context, ranked by observation class	5.0.0

-- Vector similarity search with a query vector
CALL algo.vectorSearch([0.1, 0.9, 0.3])

Returns nodes ranked by cosine similarity to the query vector.

-- Trusted RAG pipeline
CALL algo.graphRAGTrusted()

Returns nodes with trusted_score, observation class (observed > inferred > predicted), filtering low-trust paths.

Embedding Algorithms (5)#

Generate node embeddings for downstream vector search, classification, and similarity tasks.

Procedure	Return Columns	Description	Since
`CALL algo.node2vec(dims, walkLen, walks)`	(sets node.embedding)	Structural random walk embeddings	10.0.0
`CALL algo.struc2vec(dims)`	(sets node.embedding)	Structural equivalence embeddings	10.0.0
`CALL algo.graphSAGE(dims)`	(sets node.embedding)	Inductive neighborhood aggregation embeddings	10.0.0
`CALL algo.staleEmbeddings()`	`nodeId`, `name`	Nodes whose embeddings are outdated (property changed after last embed)	10.0.0
`CALL algo.classify($vec, 'indexName', {k: 10})`	`nodeId`, `label`, `confidence`	Classify by similarity to labeled examples in a vector index	10.0.0

-- Embed all nodes with 128-dimensional Node2Vec vectors
CALL algo.node2vec(128, 80, 10)
 
-- Find stale embeddings after property updates
CALL algo.staleEmbeddings()

Knowledge Graph Algorithms (6)#

Algorithms for reasoning over facts, confidence, and semantic relationships.

Procedure	Return Columns	Description	Since
`CALL algo.entityResolution()`	`nodeId1`, `nodeId2`, `similarity`	Find nodes referring to the same real-world entity	10.0.0
`CALL algo.factContradiction()`	`nodeId1`, `nodeId2`, `contradiction_type`, `confidence`	Detect contradictory facts in the graph	10.0.0
`CALL algo.relationshipStrength()`	`fromId`, `toId`, `strength`	Score relationship strength by frequency, recency, mutual links	10.0.0
`CALL algo.compoundingScore()`	`nodeId`, `score`	Composite confidence propagated through fact chains	10.0.0
`CALL algo.entityFreshness()`	`nodeId`, `name`, `freshness`, `last_observed_at`	Freshness of each entity based on last observation	10.0.0
`CALL algo.semanticDedup()`	`nodeId1`, `nodeId2`, `similarity`	Near-duplicate nodes via embedding similarity	10.0.0

-- Find entities that may refer to the same person
CALL algo.entityResolution()

Auth & Governance (7)#

API key management and audit log procedures.

Procedure	Return Columns	Description	Since
`CALL db.auth.whoami()`	`identity`, `role`, `scopes`	Current authenticated identity	9.0.0
`CALL db.auth.policies()`	`resource`, `action`, `allowed`	ACL policy definitions	9.0.0
`CALL db.auth.check('resource', 'action')`	`allowed`, `reason`	Check if current identity has permission	9.0.0
`CALL db.auth.createApiKey('name')`	`key`, `created_at`	Create a new API key (write)	9.0.0
`CALL db.auth.revokeApiKey('key')`	`revoked`	Revoke an API key (write)	9.0.0
`CALL db.auth.listApiKeys()`	`name`, `created_at`, `last_used`	List all API keys	9.0.0
`CALL db.auth.auditLog()`	`timestamp`, `identity`, `action`, `resource`	Recent auth audit events	9.0.0

Temporal (9)#

Procedures for temporal queries, clock management, and change tracking.

Procedure	Return Columns	Description	Since
`CALL db.clock()`	`name`, `tick`	Current engine clock name and tick value	4.0.0
`CALL db.clockDomains()`	`domain`, `count`	All registered clock domains with node counts	4.0.0
`CALL db.temporalCompare()`	`changeCount`, `fromSequence`, `toSequence`, `operation`	Compare mutations from sequence 0 to current	4.0.0
`CALL db.temporalGate()`	`valid`, `violationCount`, `violation`	Check temporal gate consistency; lists violations if any	4.0.0
`CALL db.temporalReplay()`	`sequence`, `operation`, `timestamp`	Replay all WAL mutations from sequence 0	4.0.0
`CALL db.nodesAsOf()`	`nodeId`, `labels`, `createdAt`	Return all nodes that existed at or before current time	4.0.0
`CALL db.changesSince()`	`sequence`, `operation`	Recent mutations (last 100 entries)	5.0.0
`CALL db.mutations()`	`sequence`, `operation`, `timestamp`	Recent mutation log (last 50 entries) with timestamps	5.0.0
`CALL db.fingerprint()`	`fingerprint`	Deterministic FNV hash of current graph state (hex string)	5.0.0

-- See recent mutations with timestamps
CALL db.mutations()

Returns rows with sequence number, operation description, and timestamp.

-- Point-in-time query (query modifier, not a CALL procedure)
MATCH (n:Person) AS OF seq N
RETURN n.name

Note: AS OF is a query modifier, not a CALL procedure.

Live Queries (5)#

Procedures for live queries: topics, subscriptions, live views, and causal chains.

Procedure	Return Columns	Description	Since
`CALL db.topics()`	`id`, `name`, `events`	All registered event topics with event counts	3.0.0
`CALL db.subscriptions()`	`name`, `topic`, `query`, `active`	Active subscriptions with topic bindings	3.0.0
`CALL db.liveQueries()`	`name`, `query`	Active live query registrations	3.0.0
`CALL db.causalChain()`	`origin`, `depth`, `target`, `target_labels`, `confidence`	Traces CAUSES chains from all Action nodes (depth 10)	3.0.0
`CALL db.views()`	`name`, `query`	Materialized view definitions	4.0.0

CALL db.causalChain()

Finds all :Action nodes and traces outgoing CAUSES relationships up to depth 10, returning each hop with confidence scores.

System (14)#

Procedures for backend management, validation, and observability.

Procedure	Return Columns	Description	Since
`CALL db.backends()`	`id`, `available`, `message`	Available compute backends (CPU, CUDA, Metal) with status	5.0.0
`CALL db.storageInfo()`	`format`, `nodes`	Storage backend details (format, generation, node/rel counts, mutation sequence)	5.0.0
`CALL db.validateQuery()`	`valid`, `warnings`	Parse and validate a query without executing	5.0.0
`CALL db.vectorIndexes()`	`name`, `label`, `property`, `dimensions`, `similarity`	All vector indexes with configuration	5.0.0
`CALL db.observationClasses()`	`class`, `count`	Observation class counts (observed, inferred, predicted)	4.0.0
`CALL db.nodesByObservation.observed()`	`_id`, `_labels`, `_observation_class`, `_confidence`	All nodes with observation class "observed"	5.0.0
`CALL db.nodesByObservation.inferred()`	`_id`, `_labels`, `_observation_class`, `_confidence`	All nodes with observation class "inferred"	5.0.0
`CALL db.nodesByObservation.predicted()`	`_id`, `_labels`, `_observation_class`, `_confidence`	All nodes with observation class "predicted"	5.0.0
`CALL db.nodesByPlane.semantic()`	`_id`, `_labels`, `_authority_plane`	Nodes in the semantic authority plane	5.0.0
`CALL db.nodesByPlane.scene()`	`_id`, `_labels`, `_authority_plane`	Nodes in the scene authority plane	5.0.0
`CALL db.proofGates()`	`gate`, `status`, `evidence`	Proof gate definitions and their validation status	5.0.0
`CALL db.proofArtifacts()`	`artifact`, `type`, `detail`	Generated proof artifacts	5.0.0
`CALL db.executionContext()`	`context`, `fallback_disabled`, `backends_available`	Current execution context (backend, GPU availability)	5.0.0
`CALL db.affordances()`	`from`, `to`, `confidence`	All AFFORDS relationships in the graph	5.0.0

-- Check available GPU backends
CALL db.backends()

Returns one row per backend (cpu, metal, cuda) with availability and status message.

-- Query by observation class
CALL db.nodesByObservation.observed()

Returns all nodes classified as "observed" with their confidence scores.

Spatial System (3)#

Coordinate frame management and spatial query observability.

Procedure	Return Columns	Description	Since
`CALL db.spatialMetadata()`	`crs`, `meters_per_unit`, `up_axis`, `handedness`, `calibration_version`	Current coordinate frame settings. Hard error raised on mismatch at ingest.	10.0.0
`CALL arcflow.spatial.dispatch_stats()`	`lane_chosen`, `estimated_candidates`, `actual_candidates`, `prefilter_us`, `rtree_us`, `gpu_transfer_us`, `kernel_us`, `total_us`	Last spatial query execution metrics. `lane_chosen`: CpuLive, CpuBatch, GpuLocal, GpuMulti.	10.0.0
`CALL arcflow.spatial.trigger_stats()`	`query_name`, `node_id`, `predicate_type`, `evaluation_us`, `fired`	Live geofence trigger metrics — one row per predicate evaluation since last reset.	10.0.0

-- Inspect current coordinate frame
CALL db.spatialMetadata()
 
-- Check dispatch lane after a spatial query
CALL arcflow.spatial.dispatch_stats()

Health (3)#

Procedure	Return Columns	Description	Since
`CALL db.replicationStatus()`	`mode`, `replica_count`, `writes_enabled`	Replication mode, replica count, and write status	5.0.0
`CALL db.checkpointMeta()`	`generation`, `nodes`	Last checkpoint generation, node/rel counts, mutation sequence	5.0.0
`CALL db.schemaRegistry()`	`label`, `property`, `type`	Registered schema versions with property types	5.0.0

CALL db.replicationStatus()

Returns the current replication mode (standalone/primary/replica), replica count, and whether writes are enabled.

Extension Procedures (5)#

Additional domain-specific procedures.

Procedure	Return Columns	Description	Since
`CALL vector.search()`	`nodeId`, `score`, `labels`	Alias for algo.vectorSearch — searches first available vector index	5.0.0
`CALL swarm.agents()`	`id`, `type`, `status`, `position`	All registered agent definitions	8.0.0
`CALL swarm.register('agent_id', 'agent_type')`	`id`, `type`, `status`	Register a new agent (requires agent_id argument)	8.0.0
`CALL swarm.agentCount()`	`active`, `total`	Number of active and total registered agents	8.0.0
`CALL geo.cells()`	`cell_id`, `name`, `status`, `entities`, `agents`	Spatial grid cells with entity/agent counts	9.0.0

-- Register a drone agent
CALL swarm.register('drone_01', 'drone')

Behavior Graph (3)#

Behavior tree procedures backed by the world model. Nodes labeled :BehaviorNode form the tree; CHILD relationships define structure.

Procedure	Return Columns	Description	Since
`CALL behavior.tick('treeName')`	`tree`, `status`, `running`, `success`, `failure`	Tick a behavior tree: evaluate from root, propagate SUCCESS/FAILURE/RUNNING	9.0.0
`CALL behavior.status('treeName')`	`nodeId`, `name`, `type`, `status`, `lastTick`	Current status of all nodes in a behavior tree	9.0.0
`CALL behavior.nodes()`	`nodeId`, `name`, `type`, `children`	List all behavior tree nodes with child counts	9.0.0

-- Tick a behavior tree named "patrol"
CALL behavior.tick('patrol')

-- List all behavior nodes
CALL behavior.nodes()

Procedures

This reference is designed for both human developers and AI coding agents. Every entry includes complete CALL syntax and return columns that can be used directly in queries.

CALL db.procedures()

Returns the full list of available procedures (column: name).

Database Introspection (20)#

Core procedures for inspecting database state, schema, and metadata.

Procedure	Return Columns	Description	Since
`CALL db.nodeCount()`	`count`	Total node count	0.19.0
`CALL db.relCount()`	`count`	Total relationship count	0.19.0
`CALL db.labels()`	`label`	All node labels in use	0.19.0
`CALL db.types()`	`type`	All relationship types in use	0.19.0
`CALL db.keys()`	`key`	All property keys in use	0.19.0
`CALL db.version()`	`name`, `version`, `crates`, `waves`	Engine version and build info	0.19.0
`CALL db.stats()`	`nodes`, `relationships`, `skills`	Database statistics summary	0.20.0
`CALL db.stats.json()`	`json`	All metadata as single JSON object	5.0.0
`CALL db.schema()`	`label`, `properties`, `count`	Schema overview: labels, property keys per label, counts, and relationship patterns	4.0.0
`CALL db.indexes()`	`label`, `property`	All indexes with target label and property	0.19.0
`CALL db.constraints()`	`label`, `property`, `type`	All constraints with target and type	0.19.0
`CALL db.procedures()`	`name`	List all available procedure names	0.20.0
`CALL db.help()`	`procedure`, `description`, `example`	Quick-reference of key procedures with examples	5.0.0
`CALL db.tutorial()`	`step`, `title`, `query`, `description`	Interactive 6-step walkthrough for new users	5.0.0
`CALL db.doctor()`	`check`, `status`, `detail`	Diagnostic health check: 5 checks + HEALTHY/ISSUES_FOUND summary	4.0.0
`CALL db.export()`	`snapshot`, `nodes`, `relationships`, `generation`	Export full graph as JSON snapshot	3.0.0
`CALL db.import('<json>')`	`status`, `nodes_before`, `nodes_after`	Import graph from JSON snapshot (mutating)	5.0.0
`CALL db.import.csv('<csv>', '<Label>')`	`imported`	Import CSV rows as nodes with given label (mutating)	5.0.0
`CALL db.clear()`	`status`, `nodes_removed`, `rels_removed`	Delete all nodes, relationships, and indexes (mutating)	5.0.0
`CALL db.demo()`	(demo graph)	Load sample social network graph with example queries (mutating)	5.0.0

-- Get a schema overview
CALL db.schema()

Returns one row per label with property keys and node count, plus relationship patterns.

-- Run diagnostics
CALL db.doctor()

Returns rows for each check (node_count, relationship_integrity, index_consistency, constraints, generation) plus a summary row with HEALTHY or ISSUES_FOUND status.

Graph Algorithms (27)#

Centrality (5)#

Procedure	Return Columns	Description	Since
`CALL algo.pageRank()`	`nodeId`, `name`, `rank`	PageRank (20 iterations, damping 0.85). GPU-accelerated when available.	0.26.0
`CALL algo.confidencePageRank()`	`nodeId`, `name`, `confidence`, `rank`	PageRank weighted by node confidence scores	5.0.0
`CALL algo.betweenness()`	`nodeId`, `name`, `betweenness`	Betweenness centrality scores	3.0.0
`CALL algo.closeness()`	`nodeId`, `name`, `closeness`	Closeness centrality scores	3.0.0
`CALL algo.degreeCentrality()`	`nodeId`, `name`, `centrality`	Degree centrality scores	3.0.0

CALL algo.pageRank()

Returns one row per node, sorted by rank. Uses 20 iterations with damping factor 0.85.

Community Detection (5)#

Procedure	Return Columns	Description	Since
`CALL algo.connectedComponents()`	`nodeId`, `name`, `component`	Connected component IDs	0.26.0
`CALL algo.communityDetection()`	`nodeId`, `name`, `community`	Community IDs via label propagation. GPU-accelerated when available.	0.26.0
`CALL algo.louvain()`	`nodeId`, `name`, `community`	Community IDs via Louvain modularity optimization. GPU-accelerated when available.	3.0.0
`CALL algo.leiden()`	`nodeId`, `community`	Community IDs via Leiden algorithm (20 iterations)	5.0.0
`CALL algo.kCore()`	`nodeId`, `name`, `coreness`	K-core decomposition values	3.0.0

CALL algo.louvain()

Returns one row per node with hierarchical community assignment.

Graph Metrics (4)#

Procedure	Return Columns	Description	Since
`CALL algo.density()`	`density`	Graph density ratio (0.0 to 1.0)	3.0.0
`CALL algo.diameter()`	`diameter`	Graph diameter (longest shortest path)	3.0.0
`CALL algo.triangleCount()`	`triangles`	Total triangle count in the graph. GPU-accelerated when available.	3.0.0
`CALL algo.clusteringCoefficient()`	`nodeId`, `name`, `coefficient`	Per-node clustering coefficients. GPU-accelerated when available.	3.0.0

CALL algo.triangleCount()

Returns a single row with the total number of triangles.

Path Analysis (4)#

Procedure	Return Columns	Description	Since
`CALL algo.allPairsShortestPath()`	`source`, `target`, `distance`	Shortest path distances between all node pairs (capped at 100 rows). GPU-accelerated when available.	3.0.0
`CALL algo.confidencePath(startId, endId)`	`path`, `cost`, `length`	Shortest path between two nodes weighted by confidence	5.0.0
`CALL algo.dijkstra(startId, endId, 'weight')`	`path`, `distance`	Weighted shortest path	10.0.0
`CALL algo.astar(startId, endId, 'weight', 'heuristic')`	`path`, `distance`	Heuristic-guided shortest path (A*)	10.0.0

-- Find confidence-weighted shortest path between node 1 and node 5
CALL algo.confidencePath(1, 5)

Returns the path as "id1 -> id2 -> id3", total cost, and hop count.

Similarity and Spatial (6)#

Procedure	Return Columns	Description	Since
`CALL algo.nodeSimilarity()`	`node1`, `node2`, `similarity`	Pairs of nodes with Jaccard similarity scores (top 20)	4.0.0
`CALL algo.similarNodes()`	`nodeId`, `score`	Nodes similar to the first vector-bearing node (cosine similarity)	5.0.0
`CALL algo.nearestNodes(point, label, k)`	`node`, `distance`	K nearest nodes by exact spatial distance (ArcFlow Spatial Index, ≥ 2000/s at 11K entities)	5.0.0
`CALL algo.objectsInFrustum($frustum)`	`node`, `distance`	Entities within a camera frustum (6-plane containment, < 2ms for 50 entities)	10.0.0
`CALL algo.nearestVisible($pos, label, k)`	`node`, `distance`	Nearest entities with direct line-of-sight from a point	10.0.0
`CALL spatial.raycast(origin, direction, maxDist)`	`hit`, `distance`	First node along a ray within max distance	10.0.0

Vector Search and RAG (5)#

Procedure	Return Columns	Description	Since
`CALL algo.vectorSearch()`	`nodeId`, `score`, `labels`	Vector similarity search over vector index. Accepts optional query vector argument. GPU-accelerated when available.	5.0.0
`CALL algo.hybridSearch()`	`nodeId`, `score`, `hops`	Combined vector + graph traversal search	5.0.0
`CALL algo.graphRAG()`	`nodeId`, `score`, `hops`, `labels`	Graph-augmented retrieval for RAG pipelines. Accepts optional query vector argument.	5.0.0
`CALL algo.graphRAGContext()`	`context`, `node_count`, `tokens_approx`	Formatted LLM context from graph retrieval. Accepts optional query vector and max_tokens arguments.	5.0.0
`CALL algo.graphRAGTrusted()`	`nodeId`, `trusted_score`, `hops`, `observation`	Trusted RAG with confidence-filtered context, ranked by observation class	5.0.0

-- Vector similarity search with a query vector
CALL algo.vectorSearch([0.1, 0.9, 0.3])

Returns nodes ranked by cosine similarity to the query vector.

-- Trusted RAG pipeline
CALL algo.graphRAGTrusted()

Returns nodes with trusted_score, observation class (observed > inferred > predicted), filtering low-trust paths.

Embedding Algorithms (5)#

Generate node embeddings for downstream vector search, classification, and similarity tasks.

Procedure	Return Columns	Description	Since
`CALL algo.node2vec(dims, walkLen, walks)`	(sets node.embedding)	Structural random walk embeddings	10.0.0
`CALL algo.struc2vec(dims)`	(sets node.embedding)	Structural equivalence embeddings	10.0.0
`CALL algo.graphSAGE(dims)`	(sets node.embedding)	Inductive neighborhood aggregation embeddings	10.0.0
`CALL algo.staleEmbeddings()`	`nodeId`, `name`	Nodes whose embeddings are outdated (property changed after last embed)	10.0.0
`CALL algo.classify($vec, 'indexName', {k: 10})`	`nodeId`, `label`, `confidence`	Classify by similarity to labeled examples in a vector index	10.0.0

-- Embed all nodes with 128-dimensional Node2Vec vectors
CALL algo.node2vec(128, 80, 10)
 
-- Find stale embeddings after property updates
CALL algo.staleEmbeddings()

Knowledge Graph Algorithms (6)#

Algorithms for reasoning over facts, confidence, and semantic relationships.

Procedure	Return Columns	Description	Since
`CALL algo.entityResolution()`	`nodeId1`, `nodeId2`, `similarity`	Find nodes referring to the same real-world entity	10.0.0
`CALL algo.factContradiction()`	`nodeId1`, `nodeId2`, `contradiction_type`, `confidence`	Detect contradictory facts in the graph	10.0.0
`CALL algo.relationshipStrength()`	`fromId`, `toId`, `strength`	Score relationship strength by frequency, recency, mutual links	10.0.0
`CALL algo.compoundingScore()`	`nodeId`, `score`	Composite confidence propagated through fact chains	10.0.0
`CALL algo.entityFreshness()`	`nodeId`, `name`, `freshness`, `last_observed_at`	Freshness of each entity based on last observation	10.0.0
`CALL algo.semanticDedup()`	`nodeId1`, `nodeId2`, `similarity`	Near-duplicate nodes via embedding similarity	10.0.0

-- Find entities that may refer to the same person
CALL algo.entityResolution()

Auth & Governance (7)#

API key management and audit log procedures.

Procedure	Return Columns	Description	Since
`CALL db.auth.whoami()`	`identity`, `role`, `scopes`	Current authenticated identity	9.0.0
`CALL db.auth.policies()`	`resource`, `action`, `allowed`	ACL policy definitions	9.0.0
`CALL db.auth.check('resource', 'action')`	`allowed`, `reason`	Check if current identity has permission	9.0.0
`CALL db.auth.createApiKey('name')`	`key`, `created_at`	Create a new API key (write)	9.0.0
`CALL db.auth.revokeApiKey('key')`	`revoked`	Revoke an API key (write)	9.0.0
`CALL db.auth.listApiKeys()`	`name`, `created_at`, `last_used`	List all API keys	9.0.0
`CALL db.auth.auditLog()`	`timestamp`, `identity`, `action`, `resource`	Recent auth audit events	9.0.0

Temporal (9)#

Procedures for temporal queries, clock management, and change tracking.

Procedure	Return Columns	Description	Since
`CALL db.clock()`	`name`, `tick`	Current engine clock name and tick value	4.0.0
`CALL db.clockDomains()`	`domain`, `count`	All registered clock domains with node counts	4.0.0
`CALL db.temporalCompare()`	`changeCount`, `fromSequence`, `toSequence`, `operation`	Compare mutations from sequence 0 to current	4.0.0
`CALL db.temporalGate()`	`valid`, `violationCount`, `violation`	Check temporal gate consistency; lists violations if any	4.0.0
`CALL db.temporalReplay()`	`sequence`, `operation`, `timestamp`	Replay all WAL mutations from sequence 0	4.0.0
`CALL db.nodesAsOf()`	`nodeId`, `labels`, `createdAt`	Return all nodes that existed at or before current time	4.0.0
`CALL db.changesSince()`	`sequence`, `operation`	Recent mutations (last 100 entries)	5.0.0
`CALL db.mutations()`	`sequence`, `operation`, `timestamp`	Recent mutation log (last 50 entries) with timestamps	5.0.0
`CALL db.fingerprint()`	`fingerprint`	Deterministic FNV hash of current graph state (hex string)	5.0.0

-- See recent mutations with timestamps
CALL db.mutations()

Returns rows with sequence number, operation description, and timestamp.

-- Point-in-time query (query modifier, not a CALL procedure)
MATCH (n:Person) AS OF seq N
RETURN n.name

Note: AS OF is a query modifier, not a CALL procedure.

Live Queries (5)#

Procedures for live queries: topics, subscriptions, live views, and causal chains.

Procedure	Return Columns	Description	Since
`CALL db.topics()`	`id`, `name`, `events`	All registered event topics with event counts	3.0.0
`CALL db.subscriptions()`	`name`, `topic`, `query`, `active`	Active subscriptions with topic bindings	3.0.0
`CALL db.liveQueries()`	`name`, `query`	Active live query registrations	3.0.0
`CALL db.causalChain()`	`origin`, `depth`, `target`, `target_labels`, `confidence`	Traces CAUSES chains from all Action nodes (depth 10)	3.0.0
`CALL db.views()`	`name`, `query`	Materialized view definitions	4.0.0

CALL db.causalChain()

Finds all :Action nodes and traces outgoing CAUSES relationships up to depth 10, returning each hop with confidence scores.

System (14)#

Procedures for backend management, validation, and observability.

Procedure	Return Columns	Description	Since
`CALL db.backends()`	`id`, `available`, `message`	Available compute backends (CPU, CUDA, Metal) with status	5.0.0
`CALL db.storageInfo()`	`format`, `nodes`	Storage backend details (format, generation, node/rel counts, mutation sequence)	5.0.0
`CALL db.validateQuery()`	`valid`, `warnings`	Parse and validate a query without executing	5.0.0
`CALL db.vectorIndexes()`	`name`, `label`, `property`, `dimensions`, `similarity`	All vector indexes with configuration	5.0.0
`CALL db.observationClasses()`	`class`, `count`	Observation class counts (observed, inferred, predicted)	4.0.0
`CALL db.nodesByObservation.observed()`	`_id`, `_labels`, `_observation_class`, `_confidence`	All nodes with observation class "observed"	5.0.0
`CALL db.nodesByObservation.inferred()`	`_id`, `_labels`, `_observation_class`, `_confidence`	All nodes with observation class "inferred"	5.0.0
`CALL db.nodesByObservation.predicted()`	`_id`, `_labels`, `_observation_class`, `_confidence`	All nodes with observation class "predicted"	5.0.0
`CALL db.nodesByPlane.semantic()`	`_id`, `_labels`, `_authority_plane`	Nodes in the semantic authority plane	5.0.0
`CALL db.nodesByPlane.scene()`	`_id`, `_labels`, `_authority_plane`	Nodes in the scene authority plane	5.0.0
`CALL db.proofGates()`	`gate`, `status`, `evidence`	Proof gate definitions and their validation status	5.0.0
`CALL db.proofArtifacts()`	`artifact`, `type`, `detail`	Generated proof artifacts	5.0.0
`CALL db.executionContext()`	`context`, `fallback_disabled`, `backends_available`	Current execution context (backend, GPU availability)	5.0.0
`CALL db.affordances()`	`from`, `to`, `confidence`	All AFFORDS relationships in the graph	5.0.0

-- Check available GPU backends
CALL db.backends()

Returns one row per backend (cpu, metal, cuda) with availability and status message.

-- Query by observation class
CALL db.nodesByObservation.observed()

Returns all nodes classified as "observed" with their confidence scores.

Spatial System (3)#

Coordinate frame management and spatial query observability.

Procedure	Return Columns	Description	Since
`CALL db.spatialMetadata()`	`crs`, `meters_per_unit`, `up_axis`, `handedness`, `calibration_version`	Current coordinate frame settings. Hard error raised on mismatch at ingest.	10.0.0
`CALL arcflow.spatial.dispatch_stats()`	`lane_chosen`, `estimated_candidates`, `actual_candidates`, `prefilter_us`, `rtree_us`, `gpu_transfer_us`, `kernel_us`, `total_us`	Last spatial query execution metrics. `lane_chosen`: CpuLive, CpuBatch, GpuLocal, GpuMulti.	10.0.0
`CALL arcflow.spatial.trigger_stats()`	`query_name`, `node_id`, `predicate_type`, `evaluation_us`, `fired`	Live geofence trigger metrics — one row per predicate evaluation since last reset.	10.0.0

-- Inspect current coordinate frame
CALL db.spatialMetadata()
 
-- Check dispatch lane after a spatial query
CALL arcflow.spatial.dispatch_stats()

Health (3)#

Procedure	Return Columns	Description	Since
`CALL db.replicationStatus()`	`mode`, `replica_count`, `writes_enabled`	Replication mode, replica count, and write status	5.0.0
`CALL db.checkpointMeta()`	`generation`, `nodes`	Last checkpoint generation, node/rel counts, mutation sequence	5.0.0
`CALL db.schemaRegistry()`	`label`, `property`, `type`	Registered schema versions with property types	5.0.0

CALL db.replicationStatus()

Returns the current replication mode (standalone/primary/replica), replica count, and whether writes are enabled.

Extension Procedures (5)#

Additional domain-specific procedures.

Procedure	Return Columns	Description	Since
`CALL vector.search()`	`nodeId`, `score`, `labels`	Alias for algo.vectorSearch — searches first available vector index	5.0.0
`CALL swarm.agents()`	`id`, `type`, `status`, `position`	All registered agent definitions	8.0.0
`CALL swarm.register('agent_id', 'agent_type')`	`id`, `type`, `status`	Register a new agent (requires agent_id argument)	8.0.0
`CALL swarm.agentCount()`	`active`, `total`	Number of active and total registered agents	8.0.0
`CALL geo.cells()`	`cell_id`, `name`, `status`, `entities`, `agents`	Spatial grid cells with entity/agent counts	9.0.0

-- Register a drone agent
CALL swarm.register('drone_01', 'drone')

Behavior Graph (3)#

Behavior tree procedures backed by the world model. Nodes labeled :BehaviorNode form the tree; CHILD relationships define structure.

Procedure	Return Columns	Description	Since
`CALL behavior.tick('treeName')`	`tree`, `status`, `running`, `success`, `failure`	Tick a behavior tree: evaluate from root, propagate SUCCESS/FAILURE/RUNNING	9.0.0
`CALL behavior.status('treeName')`	`nodeId`, `name`, `type`, `status`, `lastTick`	Current status of all nodes in a behavior tree	9.0.0
`CALL behavior.nodes()`	`nodeId`, `name`, `type`, `children`	List all behavior tree nodes with child counts	9.0.0

-- Tick a behavior tree named "patrol"
CALL behavior.tick('patrol')

-- List all behavior nodes
CALL behavior.nodes()

Procedures

Database Introspection (20)#

Graph Algorithms (27)#

Centrality (5)#

Community Detection (5)#

Graph Metrics (4)#

Path Analysis (4)#

Similarity and Spatial (6)#

Vector Search and RAG (5)#

Embedding Algorithms (5)#

Knowledge Graph Algorithms (6)#

Auth & Governance (7)#

Temporal (9)#

Live Queries (5)#

System (14)#

Spatial System (3)#

Health (3)#

Extension Procedures (5)#

Behavior Graph (3)#

See Also#

Procedures

Database Introspection (20)#

Graph Algorithms (27)#

Centrality (5)#

Community Detection (5)#

Graph Metrics (4)#

Path Analysis (4)#

Similarity and Spatial (6)#

Vector Search and RAG (5)#

Embedding Algorithms (5)#

Knowledge Graph Algorithms (6)#

Auth & Governance (7)#

Temporal (9)#

Live Queries (5)#

System (14)#

Spatial System (3)#

Health (3)#

Extension Procedures (5)#

Behavior Graph (3)#

See Also#