Browse the metahub catalog

Calculate Economic Order Quantity to minimize total inventory cost (ordering + holding). Use this skill when the user needs to determine optimal order size, balance ordering frequency against storage costs, or set reorder points — even if they say 'how much to order', 'optimal batch size', or 'inventory cost minimization'.

Analyze and mitigate the bullwhip effect where demand variability amplifies upstream in supply chains. Use this skill when the user needs to diagnose order variability amplification, quantify the bullwhip ratio, or implement dampening strategies — even if they say 'why are our orders so volatile', 'supply chain variability', or 'demand amplification problem'.

Pre-Production validation — build a production-quality end-to-end build to confirm the full game loop is achievable before committing to Production. Run after GDDs, architecture, and UX specs are complete. Produces a PROCEED/PIVOT/KILL verdict that gates the Pre-Production → Production transition.

Calculate Value at Risk to estimate maximum portfolio loss at a given confidence level. Use this skill when the user needs to quantify downside risk, set risk limits, or report regulatory risk measures — even if they say 'worst case loss', 'portfolio risk', or 'how much could we lose'.

Build credit scoring models to predict default probability from borrower characteristics. Use this skill when the user needs to assess creditworthiness, build a credit scorecard, or evaluate lending risk — even if they say 'predict default risk', 'credit scoring', or 'loan approval model'.

Validates a UX spec, HUD design, or interaction pattern library for completeness, accessibility compliance, GDD alignment, and implementation readiness. Produces APPROVED / NEEDS REVISION / MAJOR REVISION NEEDED verdict with specific gaps.

Apply Benford's Law to detect anomalies in numerical datasets by analyzing first-digit frequency distributions. Use this skill when the user needs to audit financial data for fraud indicators, validate data integrity, or detect fabricated numbers — even if they say 'data manipulation detection', 'first digit test', or 'accounting fraud screening'.

Calculate Altman Z-Score to predict corporate bankruptcy probability from financial ratios. Use this skill when the user needs to assess a company's financial distress risk, screen for bankruptcy-prone firms, or evaluate credit worthiness — even if they say 'bankruptcy prediction', 'financial distress score', or 'Z-score analysis'.

Guided, section-by-section UX spec authoring for a screen, flow, or HUD. Reads game concept, player journey, and relevant GDDs to provide context-aware design guidance. Produces ux-spec.md (per screen/flow) or hud-design.md using the studio templates.

Implement session-based recommendation from short-term user behavior sequences without long-term profiles. Use this skill when the user needs to recommend in anonymous sessions, predict next click from browsing sequence, or build recommendations for non-logged-in users — even if they say 'what should they click next', 'anonymous user recommendations', or 'browsing sequence prediction'.

Implement matrix factorization to decompose user-item interaction matrices into latent factor representations. Use this skill when the user needs scalable collaborative filtering, latent feature discovery, or dimensionality reduction for recommendation — even if they say 'SVD recommendations', 'latent factors', or 'factorize the rating matrix'.

Scaffold the test framework and CI/CD pipeline for the project's engine. Creates the tests/ directory structure, engine-specific test runner configuration, and GitHub Actions workflow. Run once during Technical Setup phase before the first sprint begins.

Design hybrid recommendation systems combining multiple strategies for improved accuracy. Use this skill when the user needs to overcome single-method limitations, combine collaborative and content-based filtering, or build a production recommendation pipeline — even if they say 'combine recommendation approaches', 'best recommendation architecture', or 'cold start plus personalization'.

Implement content-based recommendation by matching item features to user preference profiles. Use this skill when the user needs to recommend items based on attributes, solve the cold start problem for new items, or build recommendations without collaborative data — even if they say 'recommend similar products', 'items like this', or 'feature-based matching'.

Generate engine-specific test helper libraries for the project's test suite. Reads existing test patterns and produces tests/helpers/ with assertion utilities, factory functions, and mock objects tailored to the project's systems. Reduces boilerplate in new test files.

Implement collaborative filtering for recommendations based on user behavior patterns. Use this skill when the user needs to build a recommendation engine from user-item interaction data, find similar users or items, or predict ratings — even if they say 'users who bought this also bought', 'similar users', or 'recommend based on behavior'.

Calculate Wilson Score confidence intervals for ranking items by positive proportion with sample size correction. Use this skill when the user needs to rank products by ratings, sort content by approval rate, or build a 'best rated' list that accounts for sample size — even if they say 'rank by star rating', 'best rated with few reviews', or 'confidence-adjusted rating'.

Detect non-deterministic (flaky) tests by reading CI run logs or test result history. Aggregates pass rates per test, identifies intermittent failures, recommends quarantine or fix, and maintains a flaky test registry. Best run during Polish phase or after multiple CI runs.

Implement TrueSkill rating system for multiplayer and team-based competitive ranking. Use this skill when the user needs to rate players in team games, handle multiplayer (non-1v1) matchups, or build a matchmaking system with uncertainty tracking — even if they say 'team rating system', 'multiplayer ranking', or 'matchmaking rating'.

Implement Elo rating system to rank items or players from pairwise comparison outcomes. Use this skill when the user needs to rank items from head-to-head matchups, build a competitive rating system, or evaluate relative quality from comparison data — even if they say 'player rating', 'ranking from comparisons', or 'competitive scoring system'.

Quality review of test files and manual evidence documents. Goes beyond existence checks — evaluates assertion coverage, edge case handling, naming conventions, and evidence completeness. Produces ADEQUATE/INCOMPLETE/MISSING verdict per story. Run before QA sign-off or on demand.

Apply Bayesian averaging to rank items by combining observed ratings with prior expectations. Use this skill when the user needs to rank items with varying review counts, build a 'top rated' list that handles low-sample items fairly, or implement IMDB-style weighted rating — even if they say 'weighted average rating', 'IMDB formula', or 'ranking with prior'.

Conduct Van Westendorp Price Sensitivity Meter analysis to identify acceptable price ranges. Use this skill when the user needs to determine price boundaries for a new product, find the optimal and indifference price points, or survey-based pricing research — even if they say 'what should we charge', 'price sensitivity survey', or 'acceptable price range'.

Track, categorize, and prioritize technical debt across the codebase. Scans for debt indicators, maintains a debt register, and recommends repayment scheduling.

Calculate price elasticity of demand to quantify how price changes affect sales volume. Use this skill when the user needs to estimate demand sensitivity, set optimal prices, or evaluate the revenue impact of price changes — even if they say 'how sensitive are customers to price', 'will a price increase hurt sales', or 'elasticity calculation'.

Implement dynamic pricing strategies that adjust prices in real-time based on demand, time, and competition. Use this skill when the user needs to build a dynamic pricing system, implement surge pricing, or optimize prices for perishable inventory — even if they say 'real-time pricing', 'surge pricing', or 'demand-based price adjustment'.

Orchestrate the UI team through the full UX pipeline: from UX spec authoring through visual design, implementation, review, and polish. Integrates with /ux-design, /ux-review, and studio UX templates.

Run conjoint analysis to measure how product attributes drive consumer preferences and willingness to pay. Use this skill when the user needs to quantify feature value trade-offs, estimate willingness to pay for specific features, or optimize product configuration — even if they say 'which features do customers value most', 'willingness to pay for feature X', or 'product attribute trade-offs'.

Design bundle pricing strategies using pure bundling, mixed bundling, and consumer surplus analysis. Use this skill when the user needs to set prices for product bundles, determine whether bundling increases profit, or analyze unbundling opportunities — even if they say 'should we bundle these products', 'bundle pricing', or 'package deal pricing'.

Orchestrate the release team: coordinates release-manager, qa-lead, devops-engineer, and producer to execute a release from candidate to deployment.

Implement text summarization using extractive and abstractive approaches. Use this skill when the user needs to condense long documents, build an automatic summarization pipeline, or compare summarization strategies — even if they say 'summarize this document', 'TLDR', or 'key points extraction'.

Calculate text similarity using lexical and semantic methods for matching and deduplication. Use this skill when the user needs to find similar documents, detect near-duplicates, or measure semantic closeness between texts — even if they say 'how similar are these texts', 'find duplicates', or 'semantic matching'.

Orchestrate the QA team through a full testing cycle. Coordinates qa-lead (strategy + test plan) and qa-tester (test case writing + bug reporting) to produce a complete QA package for a sprint or feature. Covers: test plan generation, test case writing, smoke check gate, manual QA execution, and sign-off report.

Implement Named Entity Recognition to identify and classify entities in text. Use this skill when the user needs to extract people, organizations, locations, dates, or custom entities from documents — even if they say 'extract names from text', 'find companies mentioned', or 'entity extraction'.

Orchestrate the polish team: coordinates performance-analyst, technical-artist, sound-designer, and qa-tester to optimize, polish, and harden a feature or area for release quality.

Orchestrate the narrative team: coordinates narrative-director, writer, world-builder, and level-designer to create cohesive story content, world lore, and narrative-driven level design.

Orchestrate the live-ops team for post-launch content planning: coordinates live-ops-designer, economy-designer, analytics-engineer, community-manager, writer, and narrative-director to design and plan a season, event, or live content update.

Orchestrate level design team: level-designer + narrative-director + world-builder + art-director + systems-designer + qa-tester for complete area/level creation.

Orchestrate the combat team: coordinates game-designer, gameplay-programmer, ai-programmer, technical-artist, sound-designer, and qa-tester to design, implement, and validate a combat feature end-to-end.

Orchestrate audio team: audio-director + sound-designer + technical-artist + gameplay-programmer for full audio pipeline from direction to implementation.

Validate that a story file is implementation-ready. Checks for embedded GDD requirements, ADR references, engine notes, clear acceptance criteria, and no open design questions. Produces READY / NEEDS WORK / BLOCKED verdict with specific gaps. Use when user says 'is this story ready', 'can I start on this story', 'is story X ready to implement'.

End-of-story completion review. Reads the story file, verifies each acceptance criterion against the implementation, checks for GDD/ADR deviations, prompts code review, updates story status to Complete, and surfaces the next ready story from the sprint.

First-time onboarding — asks where you are, then guides you to the right workflow. No assumptions.

Fast sprint status check. Reads the current sprint plan, scans story files for status, and produces a concise progress snapshot with burndown assessment and emerging risks. Run at any time during a sprint for quick situational awareness. Use when user asks 'how is the sprint going', 'sprint update', 'show sprint progress'.

Generates a new sprint plan or updates an existing one based on the current milestone, completed work, and available capacity. Pulls context from production documents and design backlogs.

Generate a soak test protocol for extended play sessions. Defines what to observe, measure, and log during long play sessions to surface slow leaks, fatigue effects, and edge cases that only appear after sustained play. Primarily used in Polish and Release phases.

Run the critical path smoke test gate before QA hand-off. Executes the automated test suite, verifies core functionality, and produces a PASS/FAIL report. Run after a sprint's stories are implemented and before manual QA begins. A failed smoke check means the build is not ready for QA.

Validate skill files for structural compliance and behavioral correctness. Three modes: static (linter), spec (behavioral), audit (coverage report).