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agentdb-traverse

K-hop traversal from a starting node in AgentDB's graph. Use to explore neighborhoods, find reachable nodes, or visualize a memory's "context".

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SKILL.md (original)

Review the instructions the agent will receive before you install.

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

GoalPattern
Forward influencedirection: 'out', k: 3
Backward dependenciesdirection: 'in', k: 3
Local neighborhooddirection: 'both', k: 1
Causal chain onlyedgeFilter: ['caused', 'supersedes']
Skill composition graphedgeFilter: ['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.

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