unreal-build-ai
Build Unreal decisions, perception and navigation using selected Behavior Trees, StateTree, EQS and Smart Objects with cancellable ownership.
SKILL.mdskills/unreal-build-ai/SKILL.md
GitHubUnreal Build AI
When to use
Implement Unreal agent decisions, perception, navigation queries and contextual interactions. Mass entity storage/processing remains separate from decision authoring.
Activation and prerequisites
Run commands/resolve-engine.sh and commands/resolve-skill.sh unreal-build-ai before edits or tool launches. Require effective engine UNREAL and compatible: true; revalidate task overrides/output scope. Requesting this skill never selects an engine.
Read release, selected AI plugins, controller/pawn topology, decision framework, navigation data, authority and agent budgets. Behavior Tree versus StateTree is a project decision. Record context/evidence in resolved .hephaera/.cache/tasks/<task>/; preserve ENGINE.md.
Workflow
- Map decision, observation, blackboard/state, movement and action authority. Distinguish server decisions from replicated presentation and define missing-controller/target/path outcomes.
- Implement selected Behavior Tree tasks/services/decorators or StateTree tasks/transitions with explicit enter/tick/success/failure/abort. Shared node templates cannot accidentally retain per-agent mutable state.
- Retire observations on perception expiry, target destruction, team change and world streaming. Revalidate eligibility at authoritative action time rather than trusting cached perception.
- Configure navigation agents, filters/costs, dimensions and generation against movement constraints. Route requests through existing movement ownership; cancel only the request owned by the decision.
- Use EQS only when selected and justified. Bound query frequency/candidates, track decision generation and discard stale asynchronous results.
- For selected Smart Objects own reservation/claim handles. Release on abort, death, target loss and travel; failed or expired claims return bounded outcomes instead of endless retries.
- Budget perception, decision ticks, path requests and backoff. Use debugger/visual-log evidence to find state errors before adding polling or raising update rates.
Read decision and cancellation boundaries when authoring tasks or navigation integration.
Verification
Test success, unreachable/missing target, latent abort, expired observations, claim contention and world teardown. Use real native AI/navigation assets. Record representative agent counts and cost; a Behavior Tree abort fixture cannot certify unexercised StateTree, EQS or Smart Objects.
Output
Decision graph/data ownership, native-authored tasks/assets, resource/cancellation policy and scoped runtime/profile evidence. Record environment, expected/observed outcomes and blocked/not-run checks.
Boundaries
No automatic plugin enablement, engine changes or binary-asset synthesis. Match host APIs and target platform, preserve gameplay authority, budgets and approval/publication gates.