hoatv2211 Balance Data Change Review
Overview
Review balance changes as data contracts with intent, bounds, dependencies, and rollback conditions rather than approving isolated numbers by feel.
When to use
Use for stat tables, abilities, cooldowns, drop rates, XP curves, encounter tuning, rewards, crafting values, and configuration-driven balance patches.
When NOT to use
Do not use to write generated tables directly, deploy live configuration, or replace playtest and telemetry evidence.
Required inputs and context discovery
Collect source-of-truth path, generated outputs, baseline and proposed rows, design intent, allowed bounds, formulas, dependent systems, segment impact, test evidence, rollout scope, and rollback owner.
Safety and risk level
Read-only review. Source data may be changed only by its named owner through the project generation pipeline; generated outputs are never hand-edited.
Workflow
- Verify source ownership, generation path, schema, and baseline snapshot. Completion criterion: the canonical editable source and generated consumers are identified.
- Compute field-level deltas and compare them with declared bounds. Completion criterion: every changed value has old, new, absolute, relative, and bound status.
- Trace formulas, dependencies, breakpoints, and player-segment effects.
Completion criterion: hidden multipliers and downstream consumers are documented or
BLOCKED. - Review design evidence, exploit risk, and rollback conditions. Completion criterion: intent is testable and rollback restores the exact baseline.
- Issue a review verdict and required validation plan. Completion criterion: approval is withheld for unexplained, out-of-bound, or untestable changes.
Evidence and output contract
Produce balance-change-review.json with source identity, deltas, bound violations, dependency impacts, evidence, risks, rollback data, verdict, and required tests.
Handoff contract
Record canonical source, generation command, affected systems, unresolved dependencies, review owner, validation build, rollout scope, and rollback snapshot.
Pitfalls and anti-rationalization
- A small scalar change can cross a systemic breakpoint.
- Percentage deltas need context for zero or tiny baselines.
- Generated data is not the source of truth.
- Design intent without a measurable criterion is not sufficient evidence.
Verification checklist
- Canonical source and baseline are exact.
- Every delta is normalized and bounded.
- Dependencies and formulas are traced.
- Validation and rollback are concrete.
- No generated or live data was modified during review.
References and scripts
Use the bundled scripts/balance_review.py for normalized data-delta and bound checks. Use project-specific generators only after owner approval.