AI Game Designer

Use this skill to produce coherent, constraint-aware game design specs with explicit implementation contracts.

Workflow

1. Define game vision and constraints.

• Capture target audience, session length, progression horizon, and platform constraints.
• Document hard constraints (economy limits, fairness goals, compliance limitations).

2. Model loops and systems.

• Define core loop, meta loop, and retention loop with explicit input/output resources.
• Define feature dependencies and unlock conditions.

3. Define economy and progression contract.

• Define sources/sinks and progression pacing targets.
• Prevent degenerate loops by constraining exploit paths.
• Declare telemetry signals needed to validate assumptions.

4. Validate design spec integrity.

• Check required sections and referenced features.
• Check consistency between loops, progression, and economy definitions.
• Treat missing constraints or contradictory rules as blockers.

5. Prepare engineering handoff.

• Provide design-to-implementation mapping and patch plan targets.
• Include measurable acceptance criteria.

Commands

python3 scripts/validate_game_design_spec.py \
  --input <path/to/game_design_spec.json>

Treat non-zero exits as blocker findings.

Output Contract

Return:

1. Design Map: loops, systems, features, and constraints.
2. Validation Findings: pass/fail with concrete inconsistencies.
3. Patch Plan: docs/files that must change before implementation.
4. Verification: command outputs and acceptance criteria.
5. Residual Risks: unresolved economy or progression risks.

References

• references/workflow.md: design-to-handoff process.
• references/design-rules.md: loop/economy/progression guardrails.
• references/signoff-template.md: release handoff template.

Execution Rules

• Keep design constraints explicit and measurable.
• Keep loop/economy dependencies internally consistent.
• Flag exploitable or contradictory progression paths as blockers.
• Require telemetry hooks for key balance assumptions.