game design core loop extractor

    1

    Extract and audit the repeatable action-feedback-motivation cycle at the heart of your game design.

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    game design core loop extractor

    Example session with this skill installed

    Analyze the core loop for a top-down extraction shooter where players scavenge a haunted city for 'echoes', fight ghosts using light-based gadgets, and trade echoes for gear upgrades.

    • Read your context and instructions
    • Compiled the game design core
    • Generated the UI component

    I have analyzed the mechanics for the haunted city extraction shooter. The design centers on a high-tension resource conversion loop where light serves as both a weapon and a depletable survival resource.

    Game Design Core Loop Extraction

    Extraction Target

    • Top-down extraction shooter (Haunted City / Light-based gadgets)

    Extracted Core Loop

    Scavenge (Risk) -> Confront (Conflict) -> Harvest (Reward) -> Extract (Resolution) -> Upgrade (Growth) -> Re-enter

    Loop Step Breakdown

    StagePlayer ActionGame ResponseRenewed Intent
    InitiateEnter city zoneSpawns ghosts/echoesPressure to find resources before light fades
    ActionUse light gadgets to fightEnemy defeat / Battery drainNeed to finish fight to secure loot
    FeedbackCollect 'Echoes'Visual/Audio soul harvestGreed vs. survival (inventory vs. light)
    ResolutionReach extraction pointGear safety / Meta-progressionSatisfaction of survival

    Loop Drivers

    • Tension: The constant drain of light batteries creates a ticking clock.
    • Fantasy: The "Ghost Hunter" power fantasy vs. the vulnerability of darkness.
    • Reward: Echoes are the only currency for permanent power spikes.

    Loop Breaks and Dead Steps

    The "Trading" Chore: If the trade-in process at the base requires multiple menu layers or walking between distant NPCs, it becomes a dead step that delays the high-tension re-entry.

    Feedback Gap: If light battery drain isn't highly visible, the "reason to continue" feels like a surprise death rather than a strategic choice.

    Design Implications

    1. Strengthen Feedback: Add a flickering light effect as batteries low to increase immediate tension.
    2. Simplify Base: Automate echo-to-gear conversion to get the player back into the city faster.

    Escalate Scarcity: Make light sources rarer as the player carries more echoes to force a choice between greed and safety.

    Minimal Loop Fix

    Tie light battery life directly to Echo count. The more you carry, the faster your light fades. This forces the "Extract" decision to be a mechanical necessity rather than a player whim.

    Next steps

    • Define the specific battery drain rate per Echo stack.
    • Map the "Upgrade" tree to ensure it directly improves light efficiency.
    • Prototype the light-flicker UI feedback.

    game-design-core-loop-extractor.tsx

    TSX · React component

    Generated

    Example file from a real run - the skill writes it into your workspace.

    Connects securely to your tools. The creator never sees your data.

    What you get

    Identify structural breaks in a game's motivational circuit.Distinguish between core engagement and meta-progression systems.Expose "dead steps" and chores that cause player churn.Audit a pitch to ensure the primary loop is coherent and rewarding.

    About this skill

    The problem

    Game design documents often read like a laundry list of disconnected features. Teams struggle to articulate the actual repeatable circuit that keeps a player engaged minute-to-minute.

    What it does

    • Identifies the actual action-feedback-reward cycle buried in your design docs.
    • Separates the core engine from progression wrappers, meta-systems, and decorative fluff.
    • Exposes "dead steps" and chores that break player motivation or stall the loop.
    • Diagnoses why a loop feels emotionally flat or structurally incomplete.
    • Provides concrete design implications to strengthen the recurring player experience.

    Why this beats prompting it yourself

    General LLMs often confuse content progression with core loops. This skill uses a specialized extraction framework that forces a distinction between state changes and mere chores, ensuring you get a functional engine analysis rather than a summary of your features.

    Use cases

    • Analyzing a pitch deck to see if the central hook is actually repeatable.
    • Auditing a prototype that "isn't fun yet" to find where the feedback loop is broken.
    • Refining a GDD to cut feature sprawl and double down on the primary engagement driver.
    • Evaluating sub-loops like crafting or base-building to ensure they support the main game.

    How to install

    Works the same in every agent - Claude, Cursor, Codex, Copilot and 20+ more.

    ~30 seconds
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