Causal Experience Instantiation: Grounding Procedural Memory with Temporal Graphs for Tool-Use Agents

Tool-use agents need to reuse past procedures without treating task-specific values from those executions as facts about a new task. Retrieving a successful trajectory can import stale identifiers, while abstracting it into a workflow leaves open when and where its arguments should be grounded. We introduce Causal Experience Instantiation, which couples a Static Procedural Bank of abstract workflow graphs with an online Dynamic Fact Ledger. The bank retains action and argument dependencies without episode-specific values. As the agent acts, the ledger adds typed facts from the current task to a temporal graph, recording when each value became available and which observation supplied it. At each decision, a Presence Head estimates whether evidence for a required argument is available; a Source Ranking Head selects among compatible observed sources when it is. Otherwise, the readout leaves the argument unresolved rather than supplying an unsupported value. On AppWorld, the method completes 82/168 tasks versus ReMe’s 73/168, while reducing the invalid-call rate from 1.10% to 0.21%. Relative to ExpeL, gains also appear on ALFWorld, a stratified ScienceWorld panel, and all five evaluated AppWorld language-model backbones. Component ablations show lower AppWorld success when either memory path or the evidence-checking readout is removed.