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Use when the workflow works but needs polish, or as the final step in a diagnose → fix → refine cycle before shipping.

Quick summary of the last session — commands run, files changed, and what to do next.

Use when starting a new project, adding a new agent to an existing system, or setting up workflow infrastructure from scratch.

Use when the workflow needs to self-correct, improve over time, or establish feedback loops and evaluation cycles.

Use when the workflow lacks error handling, has been failing in production, or needs retry logic, fallback strategies, and circuit breakers.

Use when the user wants to create templates, extract reusable patterns, document solutions, or build a pattern library from working workflows.

Use when the user wants a quality review, interaction audit, or to test the workflow against realistic scenarios.

Use when the user wants to find problems, audit workflow quality, or get a comprehensive health check on their AI workflow.

Use when a single agent demonstrably cannot handle the task and multi-agent coordination is justified.

Use when the workflow needs multi-step processing with sequential, parallel, or conditional tool compositions and proper data flow.

Use when workflow components are inconsistent, naming conventions vary, or a new team member's work needs alignment to project standards.

Use when the workflow works but needs to handle more complex cases or produce higher-quality output through better tools, context, prompts, or models.

Use when any Maestro command is invoked — provides foundational workflow design principles across prompt engineering, context management, tool orchestration, agent architecture, feedback loops, knowledge systems, and guardrails.

Use when porting a workflow to a different AI provider, deployment environment, model tier, or organizational context.

Use when the workflow is too slow, too expensive, or both and needs latency, cost, or token usage optimization.

Implement LDA topic modeling to discover latent topics in document collections. Use this skill when the user needs to extract topics from a text corpus, categorize documents by theme, or explore thematic structure — even if they say 'what are the main topics', 'topic extraction', or 'document clustering by theme'.

Solve the influence maximization problem to select optimal seed nodes for maximum information spread. Use this skill when the user needs to choose seed users for viral campaigns, maximize network reach under a budget constraint, or compare seeding strategies — even if they say 'who should we seed first', 'maximize viral reach', or 'optimal influencer selection'.

Implement Louvain community detection to discover densely connected groups in networks. Use this skill when the user needs to find communities or clusters in social/organizational networks, segment customers by interaction patterns, or analyze network modular structure — even if they say 'find groups in this network', 'community detection', or 'network clustering'.

Calculate network centrality metrics to identify important nodes in graphs. Use this skill when the user needs to find key influencers, critical infrastructure nodes, or central actors in a network — even if they say 'who is most important in this network', 'key nodes', or 'network influence measurement'.

Implement Statistical Process Control charts to monitor production process stability. Use this skill when the user needs to detect process shifts, set control limits, or distinguish common cause from special cause variation — even if they say 'process monitoring', 'control chart', or 'is our process in control'.

Conduct FMEA to systematically identify, prioritize, and mitigate potential failure modes. Use this skill when the user needs to assess product or process risks, prioritize corrective actions, or build a risk register — even if they say 'failure mode analysis', 'risk assessment', 'what could go wrong', or 'RPN calculation'.

Design and analyze factorial experiments to identify significant process factors and optimize settings. Use this skill when the user needs to systematically test factor effects, optimize a manufacturing process, or determine which variables matter most — even if they say 'which factors affect quality', 'optimize process settings', or 'design an experiment'.

Calculate Cpk process capability index to assess whether a process meets specification requirements. Use this skill when the user needs to evaluate process capability, compare processes, or determine if quality targets are achievable — even if they say 'can our process meet spec', 'process capability', or 'Cpk calculation'.

Build employee turnover prediction models to identify flight risk and retention drivers. Use this skill when the user needs to predict which employees are likely to leave, identify retention risk factors, or prioritize HR interventions — even if they say 'attrition prediction', 'who is going to quit', or 'employee retention model'.

Implement Gale-Shapley stable matching algorithm for two-sided matching problems. Use this skill when the user needs to match candidates to positions, assign students to schools, or solve any two-sided preference matching — even if they say 'optimal job matching', 'stable assignment', or 'candidate-position pairing'.

Conduct compensation benchmarking analysis to position salaries against market data. Use this skill when the user needs to assess pay competitiveness, build salary bands, or analyze pay equity — even if they say 'are we paying market rate', 'salary benchmarking', or 'compensation analysis'.

Build forecasting models with Meta's Prophet for business time series with holidays and changepoints. Use this skill when the user needs user-friendly time series forecasting, handling of missing data and holidays, or automatic changepoint detection — even if they say 'forecast with Prophet', 'business forecast', or 'easy time series model'.

Apply exponential smoothing methods for time series forecasting with weighted moving averages. Use this skill when the user needs simple, robust forecasts, implement Holt-Winters for seasonal data, or build lightweight forecasting without complex models — even if they say 'simple forecast', 'moving average prediction', or 'smoothing method'.

Combine multiple forecasting models into ensemble predictions for improved accuracy. Use this skill when the user needs to improve forecast reliability, combine ARIMA/Prophet/ETS outputs, or build a robust forecasting pipeline — even if they say 'combine forecasts', 'model averaging', or 'which forecast should I trust'.

Build ARIMA models for time series forecasting with trend and seasonality decomposition. Use this skill when the user needs to forecast future values from historical sequential data, test for stationarity, or select ARIMA parameters — even if they say 'time series forecast', 'predict next month sales', or 'ARIMA model'.

Optimize e-commerce search relevance across the full pipeline from query understanding to result presentation. Use this skill when the user needs to improve search quality, implement query processing features, or diagnose search relevance issues — even if they say 'search results are bad', 'improve product search', or 'search relevance optimization'.

Design multi-objective e-commerce product ranking combining relevance, conversion, and business metrics. Use this skill when the user needs to build a product ranking system beyond text relevance, balance relevance with commercial objectives, or implement learning-to-rank — even if they say 'product sorting', 'search result ranking', or 'how to rank products'.

Implement BM25 ranking function for e-commerce product search relevance scoring. Use this skill when the user needs to build a text-based product search engine, improve search result relevance, or replace basic TF-IDF with a more robust ranking function — even if they say 'product search ranking', 'search relevance', or 'BM25 implementation'.

Design and implement smart contracts as self-executing programmatic agreements on blockchain. Use this skill when the user needs to build automated on-chain logic, evaluate smart contract security, or design tokenized business rules — even if they say 'smart contract development', 'automated agreement', or 'on-chain logic'.

Explain blockchain fundamentals including distributed ledger architecture, consensus mechanisms, and block structure. Use this skill when the user needs to understand blockchain concepts, evaluate whether blockchain fits a use case, or design a blockchain-based solution — even if they say 'how does blockchain work', 'do I need blockchain', or 'distributed ledger'.

Implement VCG mechanism for incentive-compatible ad slot allocation with truthful bidding. Use this skill when the user needs to design a truthful auction mechanism, compute externality-based payments, or understand why platforms may prefer GSP over VCG — even if they say 'truthful auction design', 'VCG payments', or 'incentive-compatible mechanism'.

Implement Generalized Second Price auction for ad slot allocation and pricing. Use this skill when the user needs to understand search ad auctions, compute ad positions and costs-per-click, or analyze bidding dynamics — even if they say 'how does Google Ads auction work', 'ad rank calculation', or 'second price auction for ads'.

Build CTR prediction models for estimating ad click-through rates from features. Use this skill when the user needs to predict click probability, build an ad ranking model, or evaluate ad creative performance — even if they say 'predict click rate', 'ad relevance scoring', or 'which ad will get more clicks'.

Optimize advertising budget allocation across campaigns using marginal returns analysis. Use this skill when the user needs to distribute budget across multiple campaigns, optimize spend pacing, or maximize overall ROAS under budget constraints — even if they say 'how to split my ad budget', 'campaign budget optimization', or 'diminishing returns on ad spend'.

Implement and select ad bidding strategies from manual CPC to automated target-CPA and target-ROAS. Use this skill when the user needs to choose a bidding strategy, set up automated bidding, or optimize bid parameters — even if they say 'what bidding strategy should I use', 'target CPA setup', or 'smart bidding configuration'.

Diagnose frame-rate bottlenecks (CPU vs GPU bound FIRST), control Unreal Insights traces, sample live frame times, and annotate performance captures. Use when FPS is low/bad, the game is slow, or you need to find what is limiting the frame rate.

Start, stop, and query Play-In-Editor (PIE) sessions for runtime testing of Blueprints, gameplay logic, widgets, AI, and any in-game behavior. Use when the user asks you to "play", "test", "run", "PIE", "start/stop the game", or otherwise needs a live game world to validate changes.

Create, inspect, and edit PCG Graph assets — add nodes, configure settings, connect pins, and wire procedural generation graphs (native PCG Python API). Use when the user asks to build a PCG graph, add PCG nodes (Surface Sampler, Static Mesh Spawner, filters), wire PCG pins, place a PCGVolume and generate, or set up procedural scattering.

Rapid-iteration parameter tuning, diagnostics, and Custom-HLSL scratch-pad authoring for Niagara systems (VibeUE NiagaraService + NiagaraScratchPadService). System/emitter/parameter CRUD is owned by the engine NiagaraToolsets. Use when the user asks to tune emitter rapid-iteration params, compare/diagnose systems, or build scratch-pad/Custom HLSL modules. For emitter color/module work, load niagara-emitters.

Niagara emitter color/curve authoring (tint, hue-shift, ColorFromCurve keys), rapid-iteration parameter tuning, and Custom-HLSL scratch-pad authoring (NiagaraEmitterService + NiagaraScratchPadService). Module/renderer CRUD is owned by the engine NiagaraToolsets. Use when the user asks to recolor or hue-shift particles, edit color curves, tune emitter params, or build a scratch-pad/Custom HLSL module. For system-level lifecycle, load niagara-systems.

Create and modify MetaSound Source assets — add/connect nodes, wire pins, set input defaults, and play procedurally (MetaSoundService). Use when the user asks to create a MetaSound, build or edit a MetaSound graph, add operator/input/output nodes, or generate procedural audio.

Create and edit materials and material instances — graph nodes, parameters, functions, custom HLSL, and instance overrides (MaterialService + MaterialNodeService). Use when the user asks to create or edit a material/material instance, wire material nodes, add material parameters, set blend/shading modes, or recreate a material graph. For landscape materials load landscape-materials.

Procedurally design an AAA-style open-world FPS map blockout (roads, POIs, fields, forests/treelines, railway/bridges) from a landscape, validate it through gated checks, and materialize it into engine geometry. Use when the user asks to block out or lay out an open-world/FPS map, place roads/POIs/forests/railways procedurally, or turn a blockout plan into splines, paint layers, foliage, and actors.