Record a causal relationship between two memories in AgentDB — "X caused Y", "A supersedes B", "patch-foo depends-on patch-bar". Use when the user is documenting cause/effect, dependencies, supersessions, or after-action analysis.
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See how to installReview the instructions the agent will receive before you install.
Add a typed edge between two memories so future queries can traverse cause→effect, supersedes, depends-on, etc.
supersedes / amends / related-to between architecture decisionsagentdb_causal_edge(
fromMemoryId: <id>
fromMemoryType: 'episode' | 'pattern' | 'skill' | 'adr'
toMemoryId: <id>
toMemoryType: <same set>
relation: 'caused' | 'supersedes' | 'depends-on' | 'related-to' | <custom>
similarity?: 0..1
uplift?: -1..1 // signed reward delta
confidence?: 0..1
metadata?: { evidenceCount, sourceTimestamp, ... }
)
uplift is the secret sauce. Positive uplift = the causal link improved outcomes; negative = it hurt. The agentdb-investigator agent (this plugin) walks edges weighted by uplift × confidence to find root causes.
The agentdb 3.0.0-alpha.13 release added cascade: true semantics:
agentdb_causal_edge_delete(edgeId) — single edgeagentdb_causal_node_delete(nodeId, { cascade: true }) — node + all incident edges; returns deletedEdges countagentdb_edges_by_endpoints(from, to, label?) — bulk delete by tupleUse cascade when removing an obsolete ADR or decommissioning an agent — leaving dangling edges in the graph poisons future traversals.
agentdb_causal_explain quality.caused for correlation — reserve it for genuinely causal evidence (controlled change, repeated observation, expert confirmation).No reviews yet. Tell others what you thought.
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