agentdb-traverse

K-Hop Traverse

Walk outward from a node up to K hops, returning the visited subgraph.

When to use

• "Show me what's connected to X"
• Building a context window from a starting fact + everything causally linked to it
• Visualizing a memory's neighborhood for the user
• Pre-fetch for an investigator agent before running causal_explain

API

agentdb_kHopNeighbors(
  startId:        <node id>
  k:              1..5                 // hops
  edgeFilter?:    [<relation>, ...]    // limit to specific relations
  direction?:     'in' | 'out' | 'both'
  maxNodes?:      100                  // safety cap
)

Returns: { nodes, edges, stats: { reachable, capped } }

Patterns

Goal	Pattern
Forward influence	direction: 'out', k: 3
Backward dependencies	direction: 'in', k: 3
Local neighborhood	direction: 'both', k: 1
Causal chain only	edgeFilter: ['caused', 'supersedes']
Skill composition graph	edgeFilter: ['composes', 'requires'], start: skill id

Output sizing

K-hop fans out exponentially. With average degree d, k hops returns up to d^k nodes. AgentDB defaults maxNodes: 100 — when you hit the cap, stats.capped: true and you should rerun with smaller k or tighter edgeFilter.

Don't

• Don't traverse with k > 4 without edgeFilter — explosive fan-out destroys the answer's signal.
• Don't render the whole subgraph to the user. Pick the top-15 by uplift and summarize the rest.