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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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ruvnet/agentdb
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6 de mayo de 2026 a las 15:22
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SKILL.md
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name
agentdb-traverse
description
K-hop traversal from a starting node in AgentDB's graph. Use to explore neighborhoods, find reachable nodes, or visualize a memory's "context".
# 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.
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