537 skills · sorted by relevance
Use telnet to interact with IoT device shells for pentesting operations including device enumeration, vulnerability discovery, credential testing, and post-exploitation. Use when the user needs to interact with network-accessible shells, IoT devices, or telnet services.
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Use picocom to interact with IoT device UART consoles for pentesting operations including device enumeration, vulnerability discovery, bootloader manipulation, and gaining root shells. Use when the user needs to interact with embedded devices, IoT hardware, or serial consoles.
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Expert knowledge for Azure Stack Edge development including troubleshooting, best practices, decision making, limits & quotas, security, configuration, integrations & coding patterns, and deployment. Use when deploying IoT Edge modules, GPU/Kubernetes apps, DeepStream workloads, Arc GitOps, or local ARM integrations, and other Azure Stack Edge related development tasks. Not for Azure IoT Edge (use azure-iot-edge), Azure Kubernetes Service (AKS) (use azure-kubernetes-service), Azure Kubernetes Service Edge Essentials (use azure-aks-edge-essentials), Azure Virtual Machines (use azure-virtual-machines).
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Expert knowledge for Azure Kubernetes Service Edge Essentials development including troubleshooting, best practices, decision making, architecture & design patterns, limits & quotas, security, configuration, integrations & coding patterns, and deployment. Use when deploying AKS Edge/Hybrid with Arc, Azure Local, GitOps, IoT/OPC/ONVIF, or Key Vault-integrated workloads, and other Azure Kubernetes Service Edge Essentials related development tasks. Not for Azure Kubernetes Service (AKS) (use azure-kubernetes-service), Azure IoT Edge (use azure-iot-edge), Azure Stack Edge (use azure-stack-edge), Azure Container Apps (use azure-container-apps).
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Guides privacy impact assessment for emerging technologies including IoT, blockchain, AR/VR, quantum computing, and digital twins. Covers risk identification methodology, proportionality assessment, and technology-specific privacy challenges. Activate when evaluating new technology adoption, innovation projects, or emerging tech procurement. Keywords: PIA, emerging technology, IoT, blockchain, AR/VR, quantum computing, digital twins, innovation privacy.
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Manage IoT SIM cards, eSIMs, data plans, and wireless connectivity. Use when building IoT/M2M solutions. This skill provides Go SDK examples.
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Manage IoT SIM cards, eSIMs, data plans, and wireless connectivity. Use when building IoT/M2M solutions. This skill provides Java SDK examples.
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Manage IoT SIM cards, eSIMs, data plans, and wireless connectivity. Use when building IoT/M2M solutions. This skill provides REST API (curl) examples.
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Manage IoT SIM cards, eSIMs, data plans, and wireless connectivity. Use when building IoT/M2M solutions. This skill provides Python SDK examples.
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Manage IoT SIM cards, eSIMs, data plans, and wireless connectivity. Use when building IoT/M2M solutions. This skill provides JavaScript SDK examples.
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Manage IoT SIM cards, eSIMs, data plans, and wireless connectivity. Use when building IoT/M2M solutions. This skill provides Ruby SDK examples.
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Integration of advanced IoT protocols for Zephyr RTOS. Covers OpenThread mesh networking, Matter-over-Thread device development, Golioth Cloud SDK patterns, and LoRaWAN basics. Trigger when building smart home devices, wide-area sensor networks, or cloud-integrated hardware fleets.
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Summarizes biotech patent families and disputes into litigation-ready intelligence briefs. Trigger when the user provides patent applications, issued patents, PTAB filings, prosecution histories, licensing materials, or litigation documents in biotechnology domains and requests a summary, risk assessment, or FTO analysis.
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Detect and adjust for horizontal pleiotropy in two-sample Mendelian randomization by distinguishing uncorrelated (UHP) from correlated (CHP) pleiotropy and choosing among Egger, MR-PRESSO, MR-RAPS, CAUSE, LHC-MR, LCV, MR-Clust, MR-Mix, and contamination-mixture methods. Use when validating an MR causal claim, running the STROBE-MR sensitivity battery, suspecting a shared heritable confounder, working under weak-instrument or polygenic-exposure regimes, or reconciling discordant estimates across robust methods.
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Build and operate Python Azure IoT Edge modules with robust messaging, deployment manifests, observability, and production readiness checks. Use when writing, deploying, or hardening a Python module for Azure IoT Edge, including telemetry filtering and offline retries.
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Design and plan end-to-end Azure IoT and Smart City solutions: requirements, architecture, security, operations, cost, and a phased delivery plan with concrete implementation artifacts. Use when planning an IoT or Smart City platform on Azure (traffic, lighting, waste, sensors) from requirements to a delivery roadmap.
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Use when working with Aws Iot Core — aWS IoT Core management including things, thing groups, certificates, policies, rules, topic monitoring, device shadows, and fleet indexing. Covers device connectivity health, message throughput, rule action errors, certificate expiration, and shadow drift analysis.
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Expert en biotechnologie (bioinformatics, genomics, CRISPR, clinical trials, FDA)
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Expert en biotechnologies avancées (bioinformatics, genomics, CRISPR, drug discovery, DZ research)
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Detect and adjust for horizontal pleiotropy in two-sample Mendelian randomization by distinguishing uncorrelated (UHP) from correlated (CHP) pleiotropy and choosing among Egger, MR-PRESSO, MR-RAPS, CAUSE, LHC-MR, LCV, MR-Clust, MR-Mix, and contamination-mixture methods. Use when validating an MR causal claim, running the STROBE-MR sensitivity battery, suspecting a shared heritable confounder, working under weak-instrument or polygenic-exposure regimes, or reconciling discordant estimates across robust methods.
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Detect and adjust for horizontal pleiotropy in two-sample Mendelian randomization by distinguishing uncorrelated (UHP) from correlated (CHP) pleiotropy and choosing among Egger, MR-PRESSO, MR-RAPS, CAUSE, LHC-MR, LCV, MR-Clust, MR-Mix, and contamination-mixture methods. Use when validating an MR causal claim, running the STROBE-MR sensitivity battery, suspecting a shared heritable confounder, working under weak-instrument or polygenic-exposure regimes, or reconciling discordant estimates across robust methods.
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Expert firmware analyst specializing in embedded systems, IoT security, and hardware reverse engineering. Masters firmware extraction, analysis, and vulnerability research for routers, IoT devices, automotive systems, and industrial controllers. Use PROACTIVELY for firmware security audits, IoT penetration testing, or embedded systems research.
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Retrieve recorded protests, riots, strikes, and other civil unrest by country and time range. Review events sorted by severity and recency, with details such as location, reported fatalities, confidence, and source links.
Build voice skills for Amazon Alexa and plan an assistant that uses Claude for its intelligence. Covers integration with AWS services including Lambda, DynamoDB, Polly, Transcribe, and Lex, as well as Smart Home.