Agent Test Spec: economy-designer

Agent Summary

Domain: Resource economy design, loot table design, progression curves (XP, level, unlock), in-game market and shop design, economic balance analysis, sink and faucet mechanics, inflation/deflation risk assessment
Does NOT own: Live ops event scheduling and structure (live-ops-designer), code implementation, analytics tracking design (analytics-engineer), narrative justification for economy systems (writer)
Model tier: Sonnet
Gate IDs: None; escalates economy-breaking design conflicts to creative-director or producer

Static Assertions (Structural)

description: field is present and domain-specific (references economy, loot tables, progression curves, balance)
allowed-tools: list matches the agent's role (Read/Write for design/balance/ documents; no code or analytics tools)
Model tier is Sonnet (default for design specialists)
Agent definition does not claim authority over live ops scheduling, code, or narrative

Test Cases

Case 1: In-domain request — loot table design for a chest

Input: "Design the loot table for a standard treasure chest in our dungeon game." Expected behavior:

Produces a probability table with distinct rarity tiers: Common, Uncommon, Rare, Epic, Legendary (or project-equivalent tiers)
Each tier has: probability percentage, example item categories, and expected gold equivalent value range
Probabilities sum to 100%
Includes a brief rationale for each tier's probability: why Common is set at its value, why Legendary is set at its value
Does NOT produce a single flat list of items — uses tiered probability structure to reflect meaningful rarity

Case 2: Out-of-domain request — seasonal event schedule

Input: "Design the schedule for our summer event and fall event. When should they run and how long should each last?" Expected behavior:

Does not produce an event schedule or content cadence plan
States clearly: "Live ops event scheduling is owned by live-ops-designer; I design the economic structure of rewards within events once the event schedule is defined"
Offers to produce the reward value design for events once live-ops-designer defines the structure

Case 3: Domain boundary — inflation risk from new currency

Input: "We're adding a new 'Prestige Coins' currency earned by completing all seasonal content. Players can spend them in a Prestige Shop." Expected behavior:

Identifies the inflation risk: if Prestige Coins accumulate faster than the shop provides sinks, the shop loses perceived value and players hoard coins without spending
Flags the specific risk: seasonal content completion is a finite faucet, but if the shop catalog is exhausted before the season ends, late-season coins have no value
Proposes a sink mechanic: rotating limited-time shop items, consumable items in the Prestige Shop, or a currency conversion option to keep coins draining
Does NOT approve the design as economically sound without addressing the sink question
Produces a structured risk assessment: faucet rate (estimated coins/week), sink capacity (estimated coins required to exhaust catalog), surplus projection

Case 4: Mid-game progression curve issue

Input: "Players are reporting the mid-game XP grind (levels 20-35) feels like a wall. They need 3x more XP per level but rewards don't increase proportionally." Expected behavior:

Identifies this as a progression curve problem: the XP cost growth rate outpaces the reward growth rate
Produces a revised XP formula or curve adjustment: either reduce the XP cost multiplier for levels 20-35, increase reward XP in that range, or introduce a catch-up mechanic (bonus XP for completing content significantly below the player's level)
Shows the math: current curve vs. proposed curve, with specific numbers for levels 20, 25, 30, 35
Flags that any curve change affects time-to-level-cap projections — notes the downstream impact on end-game content pacing

Case 5: Context pass — balance analysis using current economy data

Input context: Current economy data: average player earns 450 Gold/hour, average shop item costs 2,000 Gold, average session length is 40 minutes. Premium items cost 5,000 Gold. Input: "Is our current Gold economy healthy? Should we adjust prices or earn rates?" Expected behavior:

Uses the specific numbers provided: 450 Gold/hour = 300 Gold/40-min session; 2,000 Gold item requires ~4.4 sessions to afford; 5,000 Gold premium item requires ~11 sessions
Evaluates whether these ratios feel rewarding or frustrating based on economy design principles
Produces a concrete recommendation using the actual numbers: e.g., "At current earn rates, premium items take ~7.3 hours of play to afford — this is at the high end of acceptable; consider either increasing earn rate to 550 Gold/hour or reducing premium item cost to 4,000 Gold"
Does NOT produce generic advice ("prices may be too high") without anchoring to the provided data

Protocol Compliance

Stays within declared domain (loot tables, progression curves, resource economy, inflation/deflation analysis)
Redirects live ops scheduling requests to live-ops-designer without producing schedules
Flags inflation/deflation risks proactively with quantified sink/faucet analysis
Produces explicit math for progression curves — no vague curve adjustments without numbers
Uses actual economy data from context; does not produce generic benchmarks when specifics are provided

Coverage Notes

Case 3 (inflation risk) is an economic health test — missed inflation risks cause long-term economy damage in live games
Case 4 requires the agent to produce actual numbers, not curve shapes — verify math is present, not just a narrative
Case 5 is the most important context-awareness test; agent must use provided data, not placeholder values
No automated runner; review manually or via /skill-test

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