egorfedorov AI Game Developer
Use this skill to ship AI gameplay features with deterministic runtime behavior and explicit failure handling.
Workflow
- Define runtime contract first.
- Specify AI feature goals, update cadence, latency budget, and deterministic fallback behavior.
- Declare model/provider dependencies and allowed failure modes.
- Implement AI systems behind adapters.
- Keep inference providers behind replaceable adapter interfaces.
- Separate game loop logic from model/provider wiring.
- Ensure each AI system has clear input/output contracts.
- Enforce runtime safeguards.
- Add timeout and fallback strategy for inference failures.
- Bound update rates and queue growth.
- Protect core gameplay from AI dependency outages.
- Validate integration spec consistency.
- Validate systems/models/runtime/safety/telemetry fields.
- Validate fallback model references and guard coverage.
- Treat missing fallback and missing telemetry as blockers.
- Prepare production handoff.
- Deliver module map, runtime budgets, fallback behavior, and test expectations.
- Include patch plan with concrete file targets.
Commands
python3 scripts/validate_ai_game_runtime.py \
--input <path/to/ai_game_runtime_spec.json>
Treat non-zero exits as blocker findings.
Output Contract
Return:
Runtime Map: systems, models, providers, and budgets.Validation Findings: pass/fail with concrete integration gaps.Patch Plan: runtime/modules/config files requiring changes.Verification: command outputs and acceptance criteria.Residual Risks: unresolved latency, fallback, or safety concerns.
References
references/workflow.md: implementation-to-release process.references/runtime-rules.md: runtime guardrails and constraints.references/signoff-template.md: release handoff template.
Execution Rules
- Keep AI features optional from core gameplay continuity perspective.
- Keep fallback behavior deterministic and tested.
- Keep latency budgets explicit and enforced.
- Flag unsafe failure modes and missing telemetry as blockers.