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Found 42 Skills
Animate objects, cameras, lights, and properties in Blender — keyframes, F-curves, easing (Bezier, Linear, Sine, Bounce, Elastic), shape keys (morph targets / blendshapes / visemes), drivers (Python expressions on properties), NLA actions for reuse and layering. Use whenever the user asks to "animate this", "make it move / rotate / scale over time", "add keyframes", "loop / oscillate", "shape key / morph / blendshape", "visemes for lip sync", or any time-based property change. Make sure to use this skill even if the user does not say "animate" — also covers "spin it slowly", "make it wave", "fade in / out", "pulse", "facial expression".
Unified Azure cost management: query historical costs, forecast future spending, and optimize to reduce waste. WHEN: "Azure costs", "Azure spending", "Azure bill", "cost breakdown", "cost by service", "cost by resource", "how much am I spending", "show my bill", "monthly cost summary", "cost trends", "top cost drivers", "actual cost", "amortized cost", "forecast spending", "projected costs", "estimate bill", "future costs", "budget forecast", "end of month costs", "how much will I spend", "optimize costs", "reduce spending", "find cost savings", "orphaned resources", "rightsize VMs", "cost analysis", "reduce waste", "unused resources", "optimize Redis costs", "cost by tag", "cost by resource group", "AKS cost analysis add-on", "namespace cost", "cost spike", "anomaly", "budget alert", "AKS cost visibility". DO NOT USE FOR: deploying resources, provisioning infrastructure, diagnostics, security audits, or estimating costs for new resources not yet deployed.
Required reference for Prisma v7 driver adapter work. Use when implementing or modifying adapters, adding database drivers, or touching SqlDriverAdapter/Transaction interfaces. Contains critical contract details not inferable from code examples — including the transaction lifecycle protocol, error mapping requirements, and verification checklist. Existing implementations do not replace this skill.
Auto-activate for sqlspec, SQLSpec, SQLFileLoader, drivers, query builders, named SQL, filters, pagination, Arrow, framework extensions, ADK stores, data dictionary, or observers. Not for ORM repositories.
Check and compare software component versions on SageMaker HyperPod cluster nodes - NVIDIA drivers, CUDA toolkit, cuDNN, NCCL, EFA, AWS OFI NCCL, GDRCopy, MPI, Neuron SDK (Trainium/Inferentia), Python, and PyTorch. Use when checking component versions, verifying CUDA/driver compatibility, detecting version mismatches across nodes, planning upgrades, documenting cluster configuration, or troubleshooting version-related issues on HyperPod. Triggers on requests about versions, compatibility, component checks, or upgrade planning for HyperPod clusters.
Generate a Wren MDL project by exploring a database with available tools (SQLAlchemy, database drivers, MCP connectors, or raw SQL). Guides agents through schema discovery, type normalization, and MDL YAML generation using the wren CLI. Use when: user wants to create or set up a new MDL, onboard a new data source, or scaffold a project from an existing database.
Analyzes events through futures lens using scenario planning, trend analysis, weak signals, drivers of change, and forecasting methods (exploratory, normative, backcasting). Provides insights on possible futures, emerging trends, disruptive forces, strategic foresight, and alternative scenarios. Use when: Strategic planning, emerging trends, technology assessment, long-term planning, uncertainty navigation. Evaluates: Trends, weak signals, drivers of change, plausible futures, strategic options, uncertainty ranges.
AI-powered Uniswap developer tools: trading, hooks, drivers, and on-chain analysis across V2/V3/V4
Guides embedded real-time firmware—MCU tradeoffs, bare-metal vs RTOS (FreeRTOS/Zephyr patterns), task priorities/deadlines/jitter, ISR deferred work, stack/heap policy, WCET/timing analysis, concurrency and priority inversion, drivers/HAL, JTAG/SWD/trace, power modes, MISRA C awareness, safety-aware automotive/medical/industrial patterns without certification claims. Use for embedded firmware, RTOS scheduling, drivers/HAL, IRQ design, memory policy, WCET, bring-up, low-power—not HIL security (hardware-in-the-loop-security-tester), backend apps (senior-software-engineer), SCADA/OT (scada-ics-cyber-security-specialist), server perf (performance-engineer), RTL-only without firmware, CI gates (build-validator), tiering only (mission-critical).
Instructions for using the DeepBase multi-driver persistence library. Use when a task requires data persistence, storage abstraction, multi-backend setups, data migration between drivers, or integrating DeepBase into a Node.js project.
Answer natural language questions and perform analysis on GKE cluster and workload costs using BigQuery billing exports, cost allocation data, and live cluster monitoring metrics. Use when querying GKE costs across projects, namespaces, or workloads, analyzing billing reports in BigQuery (`bq`), checking cluster cost budgets (`gcloud billing`), or diagnosing cost drivers like pod requests vs. actual utilization (`kubectl top`). Don't use for applying cost optimization changes, creating rightsizing manifests (VPA/MPA), or selecting ComputeClasses (use gke-cost-optimization instead).
Decompose financial variances into drivers with narrative explanations and waterfall analysis. Use when analyzing budget vs. actual, period-over-period changes, revenue or expense variances, or preparing variance commentary for leadership.